Transcript
Page 1: Indeterminate Pulmonary Nodules

Evaluation and Management ofIndeterminate PulmonaryNodules

Philip A. Hodnett, MDa,b,*, Jane P. Ko, MDa,b

KEYWORDS

� Solitary pulmonary nodule � Indeterminate � Computed tomography � Nodule characterization� Lung cancer � Management � Guidelines

KEY POINTS

� Pulmonary nodules are routinely detected on computed tomography of the chest.

� Once a pulmonary nodule is identified, the key question for management of pulmonary nodules istheir characterization.

� Management decisions should not be based on nodule size alone. Central, laminar, or dense diffusepatterns of calcification are indicators of benignancy.

� Increasing patient age generally correlates with increasing likelihood of malignancy.

INTRODUCTION nodules are benign, 1 in 13men and 1 in 16 women

Although several clinical and radiologic featuresmay suggest the diagnosis, many solitary pulmo-nary nodules remain indeterminate after conven-tional evaluation. If there are no definite benignmorphologic findings, the solitary pulmonarynodule is classified as an indeterminate, possiblymalignant lesion. The solitary pulmonary nodule(SPN) remains a frequently encountered findingon multidetector computed tomography (MDCT).1

Since the first instillation of a clinical CT scanner,repeated advances in CT technology have resultedin the rapid growth in the use of MDCT2 and,thus, significant increase in the detection of lungnodules.3

Lung nodules may be caused by a variety ofdisorders, including neoplasm, infection, inflam-mation, and vascular and congenital abnormalities.Although most incidentally discovered pulmonary

No grant funding or other support was provided for thia Thoracic Imaging Department of Radiology, New York UAvenue, New York, NY 10016, USA; b Division of ThorUniversity; School of Medicine, New York University LaNY 10016, USA* Corresponding author. Thoracic Imaging, DepartmentCenter; New York University School of Medicine, 560 FirE-mail address: [email protected]

Radiol Clin N Am 50 (2012) 895–914http://dx.doi.org/10.1016/j.rcl.2012.06.0050033-8389/12/$ – see front matter � 2012 Elsevier Inc. All

will be diagnosed with lung cancer, with an esti-mated 20% to 30% of these patients presentingwith an SPN.4

The occurrence of malignancy for an SPN, suchas in mass screening studies with both plain radi-ography and CT, low.5,6 This low and reflects thehigher sensitivity of CT for small lung nodulesthat have a lesser likelihood of malignancy.7 Thehigh mortality associated with lung cancer empha-sizes the need for detection and characterizationof SPNs so that benign lesions can be distin-guished from their malignant counterparts.

Options for nodule characterization includenoninvasive and minimally-invasive techniques.Many nodules remain indeterminate and requiresurveillance, further imaging evaluation, or tissuesampling for definitive diagnosis. This has prac-tical importance so that patients with a benignSPN are not referred for unnecessary surgical

s work.niversity Langone Medical Center, IRM 236, 560 Firstacic Imaging, Department of Radiology, New Yorkngone Medical Center, 560 First Avenue, New York,

of Radiology, New York University Langone Medicalst Avenue, New York, NY 10016.

rights reserved. radiologic.th

eclinics.com

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resection, while avoiding mischaracterization ofa small malignant SPN that may represent resect-able (ie, curable) early-stage lung cancer asbenign. The aims of this article are to review therole of imaging and to address and evaluate strat-egies for the evaluation and management of inde-terminate pulmonary nodules.

DEFINITION

According to the Nomenclature Committee ofthe Fleischner Society, a “pulmonary nodule” isdefined as a sharply-defined circular opacity thatis 2 to 30 mm in diameter.8 A micronodule isa discrete, small, round, focal opacity; a varietyof diameters have been used in the past to definea micronodule. Use of the term is most oftenlimited to a nodule with a diameter of less than5 mm9 or less than 3 mm.10 The term “nodule” isreserved for opacities less than 3 cm in diameter,based on the fact that most solitary lung lesionslarger than 3 cm in diameter (termed masses) aremalignant. First, when considering a radiographi-cally detected SPN, it is important to ascertain ifthe density in question is truly solitary, lies withinthe lung, and represents a nodule. Up to 50% ofpatients with suspected SPNs detected radio-graphically actually are proved to have multiplenodules on CT evaluation.11 This is particularlyimportant because multiple lung nodules mayrepresent, for example, either metastatic or gran-ulomatous disease, depending on the clinicalscenario.12 Multiple small incidental nodules in apatient are considered independently when lack-ing a distinctive relationship to structures withinthe secondary lobule.13

In contrast, multiple nodules distributed withinthe lungs in a pattern in relation to the secondarypulmonary lobule, such as centrilobular or perilym-phatic, are considered to be a single entity, withdifferent diagnostic considerations, of which anin-depth discussion is beyond the scope of thisarticle. Centrilobular nodules are round or ovoidpoorly-defined pulmonary opacities approximately5 to 8 mm in diameter and suggestive of entitiessuch as respiratory bronchiolitis and hypersensi-tivity pneumonitis. Perilymphatic nodules alignedin regions of the subpleural lung and bronchovas-cular bundles where lymphatics are prevalentimply diseases such as sarcoidosis, silicosis, andlymphangitic carcinomatosis.

FREQUENCY

The prevalence of noncalcified SPNs is largelybased on lung cancer screening studies, withnodules detected in selected individuals reported

in 8% to 51% of baseline screenings.14 The widevariation in the prevalence of SPNs may bepartially explained by the use of different imagingmethods (chest radiography, CT), varying radiog-raphy techniques, varying percentage of smokersand their degree of smoking (former, current, andheavy) included in each study population, andthe diverse geographic location of the studies(United States, Japan, Germany, and Italy). Otherfactors that may affect lung nodule prevalence oflung nodules include the technical quality of theimaging study and interobserver variation relatedto radiologists’ interpretation of the images. How-ever, the true prevalence of pulmonary nodulesmay be underestimated in these lung cancerscreening studies constrained by z-axis spatialresolution; not surprisingly, CT examinations using10-mm section thickness detect approximatelyhalf the number of nodules compared with thoseusing 1.25 to 5 mm.15 The latest MDCT systemshas isotropic spatial resolution with a pixel dimen-sion in 3 planes of 0.5 to 0.7 mm, which result inincreased pulmonary nodule detection.16 Pulmo-nary nodules tend to be less than 10 mm; up to96% of noncalcified nodules are <10mm; of these,72% are <5 mm.17

NODULE DETECTIONRadiography

Although chest radiography remains the mostcommonly ordered radiologic examination, it haslow sensitivity for demonstrating pulmonary nod-ules and a high false-positive rate.18 The EarlyLung Cancer Action Project (ELCAP)5 describeda detection rate for noncalcified nodules with low-dose CT that was 3 times greater than that withchest radiography. In general radiologic practice,bronchogenic carcinomas have been reported asmissed on chest radiography (ie, an undetectedlesion is evident retrospectively) in 19%of cases19;this rate has varied from 12% to 90%, dependingon study design.20 Potentially resectable non–small-cell lung cancer (NSCLC) lesions not identi-fied on chest radiography are predominantlyperipheral (85%) and upper lobe (72%) in loca-tion.21 This is particularly worrisome given thatNSCLC tends to progress from early-stage tolate-stage disease, especially if several years passbetween examinations. The detection of pulmo-nary nodules on screen-film radiographs is notori-ously unreliable, with Muhm and colleagues22

reporting that 90% of peripheral nodules and 75%of perihilar nodules identified during a lung cancerscreening program were visible in retrospect onan earlier radiograph. Missed nodules may reflectan incomplete visual survey by the evaluator23 or

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a nodule’s low conspicuity when located in theupper lung, centrally,24 or over other structuressuch as the clavicle or hilar vessels (Fig. 1).

Developments in image acquisition andcomputer-assisted image analysis techniques forchest radiography have been primarily driven byrecognized challenges and limitations of the tech-nique. Dual-energy subtraction (DES) reducesanatomic noise by subtracting bony structuresoverlying the lungs in a chest radiograph, andadvances in flat panel detector technology haveenabled improved DES imaging with digital radi-ography technology.25 DES technique is basedon imaging with differing peak kilovoltage valuesand aids in more clearly depicting calcification26

and potentially characterizing pulmonary nodulesas benign, as well as having improved sensitivityfor noncalcified nodules.27 Bone-subtraction tech-nology, based on postprocessing techniques thatenable removal of the overlying bony structures,has recently been introduced as an alternative toDES. Nodule detection may be improved on chestradiographs with temporal image subtraction, inwhich the aim is to selectively enhance areas ofinterval change, accomplished by subtracting apatient’s previous chest radiograph from thecurrent one.28 The quality of the technique is inher-ently dependent on the success of 2-dimensionalregistration.29 Computer-aided detection (CAD)and computer-aided diagnosis (CADx) technologyhas slowly made its way into the clinical arena. Theclinical role of radiography-based CAD and CADxtechnology is highly debated and continuouslyevolving.30 An early CAD programmarked approx-imately 40% of the lung cancers that were missed

Fig. 1. Perihilar lung cancer. On posteroanterior radiograbove the right hilum is difficult to visualize given the loappears as a vague density that projects over the spinelung nodules.

in a lung cancer screening program, but it made anaverage of 15 false-positive marks per image.31

This technology has a complementary role inclinical practice as a second opinion, possiblyenhancing accuracy and improving efficiency,although documented limitations of CAD includethe false-positive markings.32,33

MDCT

MDCT is typically performed for a nodule identifiedon chest radiography and not determined to bestable through comparison with prior radiographs.CT is considered the current gold standard for thedetection of lung nodules.34 The latest commer-cially released MDCT systems are increasinglycomplex, with 128 or more detectors-row configu-rations and temporal resolutions on the orderof 0.3 msec. The greater degree of spatial andcontrast resolution provided by MDCT affordsimproved sensitivity and specificity for pulmonarynodule detection.35 Since its introduction, MDCTtechnology continues to advance with an in-creasing number of detector rows and more rapidscan acquisition times. Given the low attenuationof the lungs, the evaluation of the lungs is tolerantto lower doses than for the soft tissues and medi-astinum. Therefore, to minimize patient irradiation,it has been suggested that low-dose CT beperformed for the follow-up of lung nodules.36

Tube current modulation techniques for maintain-ing a standard image quality throughout a CTexamination while adjusting for overall patientsize and varying thicknesses of the patient in thex, y, and z planes will also minimize irradiation,

aphy (A), the nodular density (arrow) projecting justcation close to the vasculature. The nodule (arrows)(B), another location that hinders identification of

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particularly for smaller patients.37–39 Consistencyof CT protocols across varying CT scanner modelsand manufacturers will also ensure standarddegrees of exposure to patients and can be as-sessed by comparing the volume CT dose index,which is a measure of the radiation output of theCTmachine to a scanned volume of a standardizedphantom.40

Parameters for chest CT are determined tomaximize temporal and spatial resolution. In termsof temporal resolution, MDCT chest CT typicallyentails a rapid gantry rotation time to decreasethe duration of the CT examination and minimizethe time required for sustained breathholding bythe patient. Typically, a 25- to 35-cm field of view(FOV) is used and adjusted according to a patient’ssize to maximize spatial resolution. Given the useof a standard 512 � 512 imaging matrix, smallerFOVs result in smaller pixel sizes (0.48–0.68 mmfor standard FOVs vs 0.20–0.29 mm for targetedFOVs) and thus improve spatial resolution.41

High-frequency reconstruction algorithms en-hance edges and spatial resolution but amplifyimage noise and therefore are best used for theassessment of the lung parenchyma and bones.Although reconstructions are typically in the orderof 3- to 5-mm section thickness for a nontargetedFOV, thin-section CT scans in the order of 2 mmand smaller in thickness through an area of interestgreatly improves nodule assessment, decreasingpartial volume effect and increasing spatial resolu-tion.42 A high-frequency algorithm increasesspatial resolution and is optimum for evaluationof a nodule’s borders, shape, and architecture.Soft-tissue algorithms in distinction facilitateassessment of attenuation by minimizing imagenoise and potentially high-attenuation pixels thatmight be interpreted as calcifications. Particularlyfor nodules with a complex nature, such as

Fig. 2. Nodule detected with use of CAD. On a 5-mm axiamediastinum is difficult to identify given the close proximiton a 1-mm axial section, indicates the nodule. The CAD canon the order of 1 mm.

ground-glass or mixed solid and ground-glassattenuation nodules, thin-section images on theorder of 1 mm may be beneficial for assessingthe morphology and change in these features, iffollow-up evaluation is performed.43 The thin-section volume data are beneficial for computer-assisted evaluation methods and provide valuableimages for planning transbronchial biopsy.Pulmonary nodule detection on 5-mm sections

is reported to be on the order of 69% for nodulessmaller than 6mm and 95% for nodules measuring6 mm or larger.44 Small nodule size was shown tobe a major factor contributing to difficulty in thedetection of nodules, as well as central or lowerlobe location, complex background of other dis-ease, or decreased nodule attenuation (Fig. 2).45

Ko and colleagues46 in a study evaluating theeffect of image compression on lung nodule detec-tion, confirmed that ground-glass nodules (GGNs)were detected less frequently than solid nodules(65% vs 83%); in addition, decreased sensitivityfor central compared with peripheral nodules wasrevealed (61% vs 80%). Nodules that were notlocated adjacent to the pleura were similarly not de-tected as well. Although detection of pulmonarynodules by MDCT is improved with reduced slicethickness,47 reader fatigue can be created by the5-fold increased number of images generated.48

The use of postprocessing techniques such asmaximum intensity projection (MIP) methodologyhas been shown to improve detection rates ofpulmonary nodules in comparisonwith axial imagesthat are not postprocessed. In the MIP algorithm,only the highest-attenuation voxels along lines pro-jected through the selected plane of volume dataare selected to create the final image. MIP imageswith a slab thickness of 8 mm has been reportedto be superior in the detection of pulmonarynodules to all other tested techniques.49

l CT section (A), a 6-mm nodule, located between they to vasculature. CAD marking (B), displayed as a circledidate marks are typically processed using image data

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Table 1Causes of solitary pulmonary nodules

Neoplasticmalignant

Primary lung malignancies(non–small cell, small cell,carcinoid, lymphoma);solitary metastasis

Benign Hamartoma; arteriovenousmalformation; hematoma;pulmonary venous varix

Infectious Granuloma; roundpneumonia; abscess; septic

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CAD

Given the challenges in nodule detection, CAD hasbeen primarily developed as a second reader andhas been shown to increase reader detection ofnodules (Fig. 2). A secondary interpreter roleaims at having CAD complement a radiologist’sinitial evaluation of a CT examination for nodules.CAD nodule candidate marks are viewed after aninitial radiologist read and accepted or rejected.CAD has been shown in multiple studies toincrease radiologist sensitivity in the detection ofpulmonary nodules, although often with a concom-itant increase in the number of false-positiveresults.50,51 The number of false-positive markspresented to the reader by CAD has decreasedas the quality of MDCT data for analysis by suchsystems has improved, in addition to further devel-opment of computer algorithms. A study com-paring the performance of radiologists and CADfor pulmonary nodule detection on thin-sectionthoracic CT scans demonstrated a substantiallyhigher detection of nodules (76%) compared withdouble reading (50%).52 Important in this study isthe reported low rate of false-positives (3%), typi-cally related to branching points of vessels, arti-fact, or central vessels. It is interesting that theexperience level of the radiologist may influencethe benefit of CAD. Awai and colleagues53 re-ported that radiology residents showed significantimprovement for nodule detection but there wasno significant improvement for board-certifiedradiologists.

However, most of the development of CADfor nodule detection has focused primarily onsolid nodules only. GGNs remain one of the majordifficulties encountered by nodule detection soft-ware development.54,55 In the literature, lung CADtechniques can be divided into 2 groups: intensity-based and model-based methods. Intensity-based detection methods use the assumption thatlung nodules have relatively higher intensity thanthose of the lung parenchyma. CAD techniquesfor identifying GGNs are therefore hindered by thereduced nodule contrast and lower attenuation.56

Future direction may involve shape (model)-basedtechniques to improved performance.57

embolus

Noninfectious Amyloidoma; intrapulmonarylymph nodule; rheumatoid(necrobiotic) nodule;Wegener granulomatosis;focal scarring; infarct;sarcoid

Congenital Sequestration; bronchogeniccyst; bronchial atresia withmucoid impaction

NODULE SIZE AND CAUSE

The smaller the nodule, the more likely it is to bebenign, with 80% of benign nodules measuringless than 2 cm in diameter.58–60 The prevalence ofmalignancy in nodules that measure less than 5mm is exceedingly low (range, 0%–1%), with theexception of one small retrospective study61 thatreported both of 2 nodules smaller than 5 mm in

diameter as malignant.15 However, small size alonedoes not exclude lung cancer. In a study by Gins-berg and colleagues62 of resected nodules onvideo-assisted thoracoscopy, 15% of malignantnodules are less than 1 cm in diameter and approx-imately 42% are less than 2 cm in diameter. In thisinvestigation, a resected SPN was more likely to bemalignant if the patient had a known cancer. Thus,the clinical context of the patient in whom a noduleis reported is important, particularly malignancy.The current knowledge relating to the significanceof small pulmonary nodules largely reflects datafrom lung cancer screening trials in patients withsignificant smoking histories.17,63,64 In the Fleisch-ner Society statement,36 even in high-risk patients,the likelihood that nodules measuring less than 5mm represented lethal cancers is described to beless than 1%.

The differential diagnosis for a solitary pulmo-nary nodule includes benign andmalignant causes(Table 1). More specifically, inflammation (infec-tious and noninfectious), neoplasia (both benignand malignant), and developmental (vascular andhamartomatous) causes are considerations. Mostbenign pulmonary nodules represent granulomas(80%), hamartomas (10%), and intrapulmonarylymph nodes.65

NODULE MORPHOLOGY, LOCATION,AND SHAPE

Evaluation of specific morphologic features of asolitary pulmonary nodule with MDCT imagingtechniques can help differentiate benign from

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malignant nodules. Several morphologic featuresmay help in determining the risk of malignancy ina nodule. In small nodules, location, shape, andgrouping may be used to predict benignity. Mostmalignant solitary pulmonary nodules occur inthe upper lobes,66 whereas benign nodules areequally distributed throughout both upper andlower lobes. Frequently, bilateral, apical seg-mental, subpleural nodules are identified withsomewhat irregular margins, likely reflecting post-inflammatory fibrosis.36 Perifissural nodules havea low likelihood of malignancy if in a patientwithout a history of preexisting malignancy. Thesenodules may represent lymphoid tissue and intra-parenchymal lymph nodes, which are increasinglyrecognized as a benign cause of a solitary pulmo-nary nodule identified.67 CT signs suggestive ofintraparenchymal lymph nodes (Fig. 3) includea subpleural location68 within 15 mm of a pleuralsurface and a coffee-bean shape with a fine, linearopacity connecting them to a pleural surface.69

Published data from the Nederlands-LeuvensLongkanker Screenings ONderzoek (NELSON)screening trial70 indicated no cancers originatingfrom smoothly marginated nodules or nodulesattached to fissures, pleura, or adjacent vesselswith many intrapulmonary lymph nodes meetingthese criteria. In a screening population, Ahn andcolleagues43 demonstrated that none of the 159perifissural nodules developed into lung cancer,thus suggesting a low-malignancy potential.Shape has also been investigated as a predictor.

Polygonal shape (concave surfaces on all sidesand straight border at points of pleural contact) ishighly specific for benign disease.3 Nodules withthis appearance tended to be focal condensationsor nodules of fibrosis. The ratio of the maximumtransverse dimension to the maximum perpendic-ular length (3-dimensional ratio) of a nodule wasfound to be significantly larger in benign nodulesthan in malignant nodules. Round nodules aretherefore more likely to be malignant than aretubular or flat-shaped nodules, which may repre-sent intrapulmonary lymph nodes, granulomas, or

Fig. 3. Perifissural nodule (arrow) with a coffee beanshape. Lesions in this region are frequently relatedto intraparenchymal lymph nodes.

nodular fibrosis. When combining 3 nodule fea-tures, Takashima and colleagues60 reported thata predominantly solid attenuation and subpleurallocation or polygonal shape or 3-dimensional ratiowas associated with the highest sensitivity (63%and 60%) for 2 reviewers.

NODULE CONTOUR

Nodule margins and contours can be classified assmooth, lobulated, irregular, or spiculated. Lobula-tion (Fig. 4) is attributed to differing growth rateswithin both primary and secondary malignancies,whereas spiculated margins are usually thought tobe reflective of malignant infiltration along the inter-stitium.71 Lobular nodules have a higher likelihoodfor malignancy.72 There is, however, significantoverlap regarding nodule margins and lobulation,with up to 25% of benign nodules having lobularmorphology (Fig. 5). Pulmonary nodules in biopsy-proved lung cancer and nodule metastases mayalsomanifest smooth, well-definedmargins; Siegel-manandcolleagues73 reported21%ofnoduleswitha well-defined and smooth border as malignant.Smooth borders and the presence of a pleural tailare seen in a range of benign and malignant entitiesand are therefore of little practical assistance.74

Although spiculation has a high predictive value formalignancy75 (90%), infection and inflammationnodule causes can have a similar appearance.Concavemargins had100%specificity for benignityand 43% to 48% sensitivity, respectively.60

CAVITATION

Cavitation can occur in both benign and malig-nant nodules secondary to infectious and other

Fig. 4. AxialCTscan shows the lobulationand spiculatedmargin features of an adenocarcinoma. A pleural tailextends to the pleural surface, in addition to the irreg-ular spiculations on the lateral aspect of the nodule.

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Fig. 5. Lobulated hamartoma. Axial lung window 1.0-mm image reconstructed using a high-frequency recon-struction filter (A) demonstrates a slightly lobulated nodule border. The nodule on thin-section low-frequencyreconstruction axial 1.0-mm section (B) shows low-attenuation areas consistent with macroscopic fat. No calcifi-cation is identified in this lesion.

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inflammatory conditions as well as in primary andmetastatic tumors. Cavitation in primary lungmalignancies is more commonly associated withsquamous cell histology.76 Malignant nodulestypically have thick, irregular inner cavity walls,whereas benign cavitary nodules generally havesmooth, thin walls, although considerable overlaplimits discrimination (Fig. 6). Cavity wall thicknesscannot reliably differentiate benign from malignantnodules; of cavitary nodules with a wall thicknessbetween 5 and 15 mm, 51% were found to bebenign and 49% were malignant.77 Nodules witha wall thickness greater than 15mm aremore likelyto be malignant, whereas those with a wall thick-ness of 4mm or less are usually benign. Irregularityof the inner cavity wall is identified more frequentlyin malignant as opposed to benign cavitarynodules.78 Notching of the outer wall, similarly, ismore common in malignant cavitary nodules.

Fig. 6. Wegener granulomatosis. Shown is a benigncavitary right upper lobe nodule with a smooth, thininner cavity wall.

Irregularity of the outer cavitary wall is identified,similarly, in both benign and malignant lesions inone investigation.78

AIR BRONCHOGRAMS, AIRBRONCHIOLOGRAMS, OR “BUBBLY”LUCENCIES

A study comparing the internal features of in-determinate pulmonary GGNs on CT with theircharacteristics suggestive of malignancy evaluatedthe presence of cavitation, air bronchograms, andpseudocavitation (Fig. 7). Pseudocavitation, orspherical areas of air attenuation, may be presentincasesofbronchioalveolar cell (BAC)carcinoma,79

representing lucencies that mimic cavitationcaused by distended alveoli and bronchi sparedfrom involvement of tumor cells surrounding yetnot obliterating these structures (lepidic growth).The presence of air bronchograms or cystic or“bubbly” lucencies within an SPN is highly sugges-tive of pulmonary carcinoma including BAC andmucinous adenocarcinoma, although lymphomaand occasional benign lesions, such as organizingpneumonia and mass-like sarcoidosis, can haveair bronchograms.

NODULE ATTENUATION AND SUBSOLIDNODULES

Patterns of calcification may be helpful in discrim-inating benign from malignant pulmonary nodules.When CT section thickness is 5mm, partial volumeeffect may render detection of calcification withinnodules difficult. CT, particularly thin-sectionCT, allows objective, qualitative assessment of

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Fig. 7. Air bronchograms and pseudocavitation inknown mucinous adenocarcinoma of the lung.Lucencies are present in 2 lower lobe soft tissue largenodules with irregular margins.

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calcification.65 There are 4 benign patterns of calci-fication: central, diffuse solid, laminated, and“popcorn like.” These patterns, not frequentlydetected, are specific for benign disease, with cen-tral, concentric or lamellated (Fig. 8), or completelyhomogeneous calcification typically reflecting

Fig. 8. Lamellated pattern of calcification associatedwith granulomatous disease. The “target” patternof calcification is manifested by central calcifica-tion with concentric rings and a peripheral rim ofcalcification.

granulomatous response to prior infection.80

Dense, uniform calcification is a strong indicatorof benign disease and present in 14% of sub-centimeter nodules detected at baseline in onelung cancer screening study.81 Popcorn calcifica-tion is typical of hamartomas and is caused bychondroid calcification.82 Another classic featureof hamartomas is the presence of fat with internaldensity ranging between�40 and�120Hounsfieldunits (HU) (Figs. 5 and 8), allowing this diagnosis tobe made with confidence in a smooth nodulemeasuring less than 2.5 cm in diameter. Hamarto-mas, however, are relatively rare, andat least a thirdof hamartomas contain neither fat nor calcium.Stippled, amorphous, or eccentric calcifications(Fig. 9) are indeterminate patterns in an SPN andmay be seen in malignancy.83 Patients with adocumented history of osteosarcoma or chon-drosarcoma may present with lung metastasesdemonstrating “benign” patterns of calcification.84

Intratumoral calcifications may be seen in lungcancer; however, these tend to occur in larger,more centrally located lesions.85 Last, althoughfat content typically suggests a hamartoma, othercauses of nodular densities with fat include liposar-coma and focal lipoid pneumonia.Pulmonary subsolid nodules are defined as

“rounded” areas of homogeneous or heteroge-neous “increased” ground-glass attenuation in CTscans, which are lower in density with regard tosurrounding soft tissue structures such as ves-sels.86 Subsolid nodules can be classified furtheras either part-solid (Fig. 10), when areas of paren-chymal architecture are obscured completelywithin the nodule, or nonsolid, when the nodule ispure ground-glass attenuation and harbors noareas of soft tissue density.87 In the Early LungCancer Action Program study,86 pure GGNshad an 18% incidence of malignancy, with partly

Fig. 9. Eccentric calcification. Lobulated nodule withlow attenuation areas correlate with macroscopic fatindicating a hamartoma. A small eccentric solitarycalcification is also present, which is an indeterminatepattern that is nonspecific.

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Fig. 10. Part-solid nodule: adenocarcinoma. Nodulewith ground-glass attenuation has an eccentric solidcomponent (white arrow) in the lesion. There isa dilated airway (arrowhead) in the periphery of thisnodule. This lesion proved to be a lung cancer on resec-tion and was mutation positive for epidermal growthfactor receptor, correlating with responsiveness totyrosine kinase inhibitor therapy for lung cancer.

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solid nodules having the highest incidence ofmalignancy (63%). Solid nodules, on the otherhand, hadan incidence rate of 7%.86 Thepersistentpresence of a solitary GGN usually supports thediagnosis of BAC or mixed adenocarcinoma withBAC, atypical adenomatous hyperplasia (AAH)(which is now believed to be a precursor to adeno-carcinoma), and, less frequently, inflammatorycauses such as organizing pneumonia and focalinterstitial fibrosis.88 Pulmonary lymphoprolifera-tive disorder is another, although less commoncause, of aGGN.Whenmultiple GGNs are present,multiple synchronous adenocarcinomas are a con-sideration including other causes such as eosino-philic lung disease.89

Adenocarcinoma is composed of a spectrum ofentities with varying malignant behavior rangingfrom preneoplasia of AAH to BAC to invasiveadenocarcinoma. The development of collapsefibrosis and ultimately invasion is a result of thecontinuum of pathologic changes that leads tostepwise progression for some but not all adeno-carcinomas.90 Recently, the pathologic classifica-tion of adenocarcinoma has changed, developedby the International Association for the Study ofLung Cancer.91 The changes include an end to

the use of the term “BAC,” to be replaced by“adenocarcinoma in situ,” representing tumorswith lepidic growth without invasive features.92

Minimally invasive carcinoma refers to any lesion3 cm or smaller in which there is 5 mm or less ofinvasive areas, not necessarily in one location.

When CT imaging is compared to pathology,investigation has demonstrated that subsolid nod-ules containing some solid components correlatewith lesions demonstrating collapse fibrosis,active fibroblast proliferation, and invasive fea-tures seen with higher grades of adenocarci-noma.90,93 Lesions greater than 1 cm are morelikely to represent adenocarcinoma than AAH.Nodular sphericity and internal air bronchogramshave been described as findings on thin-sectionhelical CT that can differentiate between BACand AAH,79 although there is overlap in theirimaging appearance. A large number of studieshave compared CT to the previous Noguchi andWorld Health Organization pathologic classifica-tion systems. Thus, with the new InternationalAssociation for the Study of Lung Cancer classifi-cation, it is unclear in terms of the correlation ofCT with the newer classification.

In terms of differentiating benign from malignantsubsolid nodules, Li and colleagues94 reportedthat the margin characteristics and the sizes ofGGNs were not useful in differentiating betweenbenign and malignant lesions. Round shape wasfound more frequently in pure ground-glass malig-nant lesions rather than in benign lesions. MixedGGNs with central solid attenuation and peripheralground-glass regions were associated more oftenwith malignant entities. In their evaluation of per-sistent nodules,88 Kim and colleagues also didnot find any significant differences in morphologicfeatures among benign and malignant causes ofpersistent GGNs. However, Lee and colleagues95

identified a size greater than 8 mm and a lobulatedborder for pure GGNs as being predictive ofmalignancy.

CT HALO SIGN

The halo sign is identified as an ill-defined rim ofground-glass attenuation surrounding a pulmonarynodule.96 The finding is nonspecific and may re-present BAC, hemorrhage, or inflammation, ini-tially described in the setting of invasive fungalAspergillus infection (Fig. 11). Inflammatory andinfectious causes, particularly organizing pneu-monia, can sometimes demonstrate a reverse-halosign, where a central focal area of ground-glassattenuation is surrounded by a peripheral rim ofconsolidation.97

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Fig. 11. Evolving pulmonary infarct. A well-circumscribed nodular peripheral density abuttingthe lingular visceral pleura lacked air bronchogramson axial CT section. Three weeks earlier, the findinghad ground-glass opacity in the periphery withpoorly-defined margins and a broad base of contactwith the pleura.

Fig. 12. Increasing small peripheral carcinoid. The well-cilower lobe on axial CT scan (A) grew from a small noduletained 5.5 years earlier (B).

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NODULE GROWTH

An important and cost-effective step in the evalu-ation of a solitary pulmonary nodule is determiningwhether growth has occurred by comparing itssize on a current image with that on prior images.Assessment is performed visually and can bequantified. Doubling time, representing the timerequired for a nodule to double in volume, formost malignant nodules is between 30 and 400days.98 Nodules that double more rapidly than 30days are typically benign and related to infection,although lymphoma andmetastases may on occa-sion demonstrate rapid growth. Doubling timesgreater than 400 days have been associated withbenign entities such as hamartomas (Fig. 12). In-terestingly, however, Hasegawa and colleagues99

conducted a growth rate analysis of small lungcancers detected during a 3-year mass screeningprogram. They classified nodules as ground-glassopacity, as ground-glass opacity with a solid com-ponent, or as solid. Mean volume doubling timeswere 813, 457, and 149 days, respectively, forthese 3 types, all of which were significantlydifferent (Fig. 13). Thus, GGNs that are lung cancercan exhibit very long doubling times (Fig. 14).Persistent GGNs that represent lung cancer mayalso progress by increasing density with or withoutconcomitant size increase. GGNs have been infre-quently described as decreasing in size, reflecting

rcumscribed, smoothly marginated nodule in the left(arrow) as shown in an axial image from a study ob-

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Fig. 13. Air space and ground-glass nodule: adenocarcinoma, mixed bronchoalveolar and acinar features. Axial(A) chest CT scan demonstrates a lesion showing branching on the axial projection, whereas the coronal view(B) demonstrates the rounded nature, thus supporting the utility of including multiple planes in the evaluation.Axial CT sections for studies at 11 months (C) and 22 months (D) later showed an increase in the lesion in terms ofsize and density. Malignancy was proven by resection and pathologic examination.

Management of Indeterminate Pulmonary Nodules 905

increasing fibrosis. Thus, continued interval chestCT follow-up is warranted in this setting.100

Additionally, it can be difficult to reliably detectgrowth in small nodules of less than 1 cm.101

Traditionally, pulmonary nodule measurementhas involved 2-dimensional caliper measurementof the largest nodule diameter, its perpendicularbreadth, and the average of the largest lengths.Significant intrareader and interreader variability

has been reported using 2-dimensional measure-ments and electronic caliper placement, particu-larly in lesions with spiculated margins.102,103

For example, a 5-mm nodule can double involume during a 6-month period (malignantgrowth rate), but its diameter will increase byonly 1.25 to 6.25 mm. For a nodule to double involume, the change in nodule diameter is approx-imately 26%.104

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Fig. 14. Increased nodule size and density. A small nodule increased slowly over time in terms of size and density.Note the change in the border morphology in addition to one with a more lobulated appearance. Adenocarci-noma with lepidic components can increase in density without a large appreciable change in overall size.

Hodnett & Ko906

VOLUMETRIC ANALYSIS

To overcome these limitations, volume measure-ment has been suggested as a more reproducibleand reliable means for assessing growth. Althoughmanual volumetry is time consuming, automatedtechniques are increasingly available. Variabilityin volumetric analysis may particularly affect mea-surement of perivascular, speculated, and pleura-based nodules105 and also may vary depending onwhether intravenous contrast is administered.106

Volumetric techniques, however, are also suscep-tible to error. Variability of lung nodule volume soft-ware in patients scanned 3 times in the samesession has been reported to have an interscanvolumetric variation of �20%.107 Applications ofvolumetric 3-dimensional measurement tools in-clude characterization of lung nodules in additionto measurement of known malignancy/whetherexpressed in the longest dimension or in volume.Increasing use of volumetric software will be facil-itated by integration with clinical workflow viapicture archiving and communication systems.

NODULE ENHANCEMENT

Contrast-enhanced CT can be used to further non-invasively assess lung nodules. This has beeninvestigated as a method to differentiate benignand malignant nodules, with the degree of en-hancement directly related to the likelihood ofmalignancy and the vascularity of the nodule.108

Enhancement of a nodule of less than 15 HU aftercontrast material administration is strongly pre-dictive of a benign lesion, whereas enhancementof more than 20 HU typically indicates malignancy(sensitivity, 98%; specificity, 73%; accuracy,85%).109 Regions of interest placed to measureattenuation measurements should comprise ap-proximately 70% of the nodule diameter withmeasurement performed on mediastinal window

settings to reduce partial volume averaging. Thistechnique is performed so that contiguous thinsections are reviewed. Application of this tech-nique should not be performed on lesions withcalcium, areas of fluid attenuation representingobvious necrosis on precontrast CT scans, orground-glass opacity.Dual-energy CT allows material differentiation of

iodine and thus simultaneously provides a virtualnon–contrast-enhanced (VNC) and an iodine-enhanced image from a single image acquisitionafter the administration of iodine contrast material(Fig. 15).110 Technology for dual-energy CT imag-ing includes dual- and single-source systems. Thistechnique may eliminate the need to acquire non-enhanced CT before scanning with intravenouscontrast, thus reducing patient’s radiation expo-sure.111 Chae and colleagues111 investigated theaccuracy of both VNC and iodine-enhancedimages for the evaluation of pulmonary nodule. Intheir study, the VNC image demonstrated 85% ofthe calcifications in nodules that were visibleon a true non–contrast-enhanced CT. Diagnosticquality for VNC images was the same as for truenoncontrast imaging in 77.6% or inferior yet diag-nostic in 16.3%, respectively. HU differencesbetween VNC and true non–contrast-enhancedevaluation was 4.3 on average with a 95% confi-dence interval of –14.6 to 23.3 HU. In terms ofiodine-enhanced images in comparison to tradi-tional nodule enhancement, the average differ-ence was –0.5 HU (95% confidence interval of–17.6 to 16.5 HU). Sensitivity for malignancy usingiodine-enhanced images using 20 HU as a cutoffwas 92%, whereas specificity was 70%.

PET CT EVALUATION

Positron emission tomography (PET) providesin vivo functional mapping of 2-deoxy-2[18F]

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Fig. 15. Nodular metastasis with enhancement. Dual-energy CT imaging performed with intravenous contrastwith subsequent material decomposition reveals iodine distributed in a small nodule on iodine-enhanced image(A). Nodule is shown in the VNC image in the right middle lobe (B). The VNC image is generated during the sameprocess as the iodine-enhanced image. An overlay of the iodine-enhanced and VNC (C) images can be performedfor better correlation of iodine and anatomic information.

Management of Indeterminate Pulmonary Nodules 907

fluoro-D-glucose (FDG) uptake, which is elevatedin neoplastic lesions (Fig. 16).112,113 The value ofPET CT in the diagnosis of pulmonary nodules iswell documented with meta-analysis–reportedsensitivity of 90% and specificity of 83% for diag-nosing malignancy.114 The high specificity of FDGPET for the diagnosis of benign lesions has impor-tant clinical utility. Lesions with low FDG uptakemay be considered benign; however; these lesionsshould be followed radiologically because of false-

Fig. 16. Carcinoid tumor with FDG PET uptake. A well-cnodule in the lingula (A) had increased FDG uptake onhave abnormal uptake.

negative results.115 Certain histologic types suchas low-grade adenocarcinoma, BAC,116 and carci-noid tumors may give rise to false-negative FDGevaluations. In addition, the diagnostic perfor-mance of PET decreases considerably for lesionsof less than 6 mm. False-positive results mayalso be seen with infectious or inflammatoryprocesses and granulomatous disorders suchas granulomatosis with polyangiitis (Wegener gran-ulomatosis) or sarcoidosis. In some circumstances,

ircumscribed, smoothly marginated mildly lobulatedfused PET CT image (B). Carcinoid lesions may not

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FDG PET can be used to direct tissue biopsy and toidentify which lesions or portions of lesions aremetabolically active and most likely to yield a defin-itive tissue result.117

NODULE BIOPSY

In pursuing a tissue diagnosis of a suspected lungcancer, there is a range of procedures fromwhich to choose. Transthoracic needle aspirationand biopsy, bronchoscopy, video-assisted thora-coscopic surgery, or thoracotomy may be per-formed. The method of diagnosis depends onthe type of lung cancer, the size and location ofthe primary tumor, the presence of metastasis,and the overall clinical status of the patient.Studies have shown that the diagnostic sensitivityof bronchoscopy for peripheral lung cancer is 78%but only 34% for lesions with a diameter of lessthan 2 cm.118 The decision of whether to pursuea diagnostic bronchoscopy for a lesion that issuspicious for lung cancer largely depends onthe location of the lesion in terms of whether it iscentral or peripheral.119,120

For peripheral lung lesions, the sensitivity oftransthoracic needle aspiration biopsy (TNAB) ishigher than that of bronchoscopy. Percutaneousfine-needle biopsy is accurate for diagnosingmalignancy, with reported sensitivities varyingfrom 70% to 100%121–123 Nodules that are idealfor percutaneous sampling are accessible withoutcrossing major vascular structures and fissures.124

In patients who have lung cancer, TNAB samplinghas approximately a 90% chance of providingconfirmation of the diagnosis with a low false-positive rate rendering a positive finding for cancerreliable. The confirmation of a benign diagnosis ismore problematic when performing needle aspira-tion alone. Acquiring a biopsy sample at time ofTNAB after the acquisition aspiration increasesthe diagnostic yield for benign diagnosis from12% to 75%.125

TNAB is generally regarded as a safe proce-dure with limited morbidity and extremely raremortality.126 Complications, most notably pneu-mothorax, occur in approximately 5% to 30% ofpatients.127–129 A recent study confirms previousreports that older age and the presence ofchronic obstructive pulmonary disease increasecomplication rates,130 with more than 6% ofCT-guided biopsies that result in pneumothoraxrequiring a chest tube, a clinically importantcomplication.Thoracotomy remains the most invasive but

effective means to obtain a histologic diagnosis.The operative mortality of thoracotomy is 3% to7% for malignant nodules and less than 1%

for benign nodules.131,132 Decreased periopera-tive mortality and hospital stays have beenachieved with the development of video-assistedthoracoscopy.61

PULMONARY NODULE MANAGEMENTSTRATEGIESPretest Probability of Malignancy

The approach to managing pulmonary nodules ismultidisciplinary, with input from pulmonologists,surgeons, and radiologists. The evaluation of apulmonary nodule has been summarized by theAmerican College of Chest Physicians ClinicalPractice Guidelines.14 Specific clinical featuresdetermined to be significant predictors of malig-nancy are older age, smoking history, andpersonal history of cancer greater than 5 or moreyears prior to nodule detection.The clinical probability of malignancy in patients

with SPNs assists in directing appropriate man-agement strategies. Current quantitative modelsfor the risk of malignancy incorporate the patient’spersonal risk factors for lung cancer as well ascharacteristics of the lung lesion itself. Bayesiantheory and neural network–based methods usingfactors such as smoking history and age havebeen studied.59,133,134 A multiple logistic regres-sion model135 identified 4 independent risk factorsfor predicting malignancy: positive smokinghistory, older patient age, larger nodule diameter,and time since smoking cessation. The respectiveodds ratios for these factors were 7.9, 2.2 (for eachdecade of life), 1.1 (for each mm), and 0.6 (for eachdecade since stopping smoking).135

Decision-analysis models have suggested thatmost effective management strategies for solitarypulmonary nodules depend on the probability ofan SPN being malignant. The most pertinentstrategy in terms of cost-effectiveness was simplesurveillance for nodules with a low probability ofmalignancy (<5%), immediate surgical resectionfor those with a high probability of malignancy(�60%), and biopsy or noninvasive imaging evalu-ation with FDG PET or nodule enhancement CT forthose with a probability of malignancy between5% and 60%.136

Fleischner Society Guidelines

On the basis of collective evidence that suggeststhat a substantial number of solitary pulmonarynodules are benign,13,137 the Fleischner Societyissued a set of guidelines in 2005 for the man-agement of indeterminate nodules incidentallydetected during CT examinations performed forclinical purposes other than lung cancer screen-ing.36 Their development was in response to a

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Management of Indeterminate Pulmonary Nodules 909

perceived need for guidance in the managementand follow-up of small nodules that are frequentlydetected with MDCT technology. Of note, theFleischner guidelines do not apply to patientswith a history of malignancy, those younger than35 years unless there is a known primary cancer,and those with a fever, in whom the nodules mayhave an infectious cause. For pulmonary nodulea follow-up noncontrast, thin-collimation, low-dose CT scan is recommended by the FleischnerSociety. Risk factors are considered in theseguidelines and include smoking, family history oflung cancer, and environmental exposures.

Given that 99% of all nodules that measure 4mm or less are benign and that these small opac-ities are seen very frequently on thin-section CTexaminations, systematic CT reassessment is nolonger recommended for those with low risk. Asingle CT examination can be performed at 12months in high-risk individuals. For nodules mea-suring between 4 and 8 mm, surveillance is themost appropriate strategy, with 2-year stabilityconsidered an indicator of benignity. The timingof these examinations varies according to thenodule size (4–6 or 6–8 mm) and type of patientwhether low or high risk for having malignancy.Different management options apply to nodulesgreater than 8 mm, including study of enhance-ment on CT, PET CT, percutaneous needle biopsy,or video-assisted thoracoscopic resection. Inhigh-risk patients, the optimal strategy probablyremains that of biopsy or nodule resection.

GGN Management

Proposed interim management guidelines forground-glass and subsolid pulmonary noduleshave been proposed by Godoy and Naidich.89 Itis currently debated whether pure GGNs that areless than 5 mm necessarily require follow-up CTstudies given their association with AAH; for thoselarger than 5 mm, follow-up is requisite pendingbetter definition of their true nature.

Nodules with pure ground-glass attenuationthat are larger than 5 mm represent AAH or BACand initially assessed, such as at 3 months withsubsequent annual evaluation, to identify anyinvasive adenocarcinomas presenting as a pureGGN. The duration of surveillance at this pointhas not been established but probably is longerthan that for solid counterparts given the slowgrowth rates associated with pure GGNs. Itshould be noted that 20% to 25% will proveto be benign at resection; surgery should beconsidered especially if the nodule is enlargingor if there is an increase in attenuation or develop-ment of a solid component. Persistent lesions with

mixed solid component and ground-glass attenu-ation should also be presumed malignant, andfurther evaluation with FDG PET and surgicalresection should be considered, particularly forthose with solid components comprising morethan half of the nodule. TNAB can also be con-sidered in accessible lesions. High-resolutionthin-section evaluation of ground-glass–containinglesions will assist in characterizing the degree ofsoft tissue and interval change in solid andground-glass components.

Adherence to Guidelines

A recent study138 assessing adherence to Fleisch-ner Society guidelines for management of smalllung nodules reported that surveyed radiologists,when given potential nodule management sce-narios, made management selections that wereconsistent with the Fleischner guidelines in34.7% to 60.8% of responses. A significantly high-er rate of concordance occurred in those whowere aware of the Fleischner guidelines (77.8%),had written policies based on them, were workingin a teaching practice setting, practiced in a groupwith at least one member having fellowshiptraining in thoracic radiology, and had fewer than5 years of experience practicing radiology. Eventhough the respondents reported high awarenessand use of the Fleischner guidelines, conformancevaried. There are many reasons offered for thisapparent inconsistent approach.139 The AmericanCollege of Chest Physicians systematic review ofevidence-based clinical guidelines regarding themanagement of pulmonary nodules concludesthat assessment of risk factors, including risks/benefits of biopsy, surgery, and further observa-tion, is critical, and patient preference plays arole.14 Additionally, there is interreader variabilityin 2-dimensional measurements involving elec-tronic caliper placement when measuring non-calcified pulmonary nodules.140 Similarly, CTmeasurement of a nodule has limitations with awell-described “zone of transition” of the distancebetween nonaerated solid tumor and surroundingnonneoplastic pulmonary parenchyma.141 Theauthors stress that this consideration is especiallya limitation for radiologic assessment of sub-centimeter subsolid nodules.

SUMMARY

With the use of MDCT as a diagnostic modality,the incidental detection of solitary subcentimeterpulmonary nodules has increased substantially. Ifthere are no definite benign morphologic findings,the solitary pulmonary nodule must be classifiedas an indeterminate, possibly malignant lesion.

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Many solitary pulmonary nodules have similarfeatures, and malignant nodules may be in-accurately classified as benign after radiologicassessment of size, margins, contour, and internalcharacteristics. Patients with an indeterminatepulmonary nodule should be evaluated withknowledge of expert consensus-based recom-mendations for performing follow-up CT scansand tissue sampling. Clinical management ofthese incidental nodules relies not only on imagingcharacteristics but also on patient risk factors formalignancy, the weighing of the risks and benefitsof further investigation, and consideration ofpatient preference.

REFERENCES

1. Brandman S, Ko JP. Pulmonary nodule detection,

characterization, and management with multide-

tector computed tomography. J Thorac Imaging

2011;26(2):90–105.

2. Huppmann MV, Johnson WB, Javitt MC. Radiation

risks from exposure to chest computed tomog-

raphy. Semin Ultrasound CT MR 2010;31(1):14–28.

3. Edey AJ, Hansell DM. Incidentally detected small

pulmonary nodules on CT. Clin Radiol 2009;64(9):

872–84.

4. Truong MT, Sabloff BS, Ko JP. Multidetector CT

of solitary pulmonary nodules. Thorac Surg Clin

2010;20(1):9–23.

5. Henschke CI, McCauley DI, Yankelevitz DF, et al.

Early lung cancer action project: a summary of

the findings on baseline screening. Oncologist

2001;6(2):147–52.

6. Good CA, Wilson TW. The solitary circumscribed

pulmonary nodule; study of seven hundred five

cases encountered roentgenologically in a period

of three and one-half years. JAMA 1958;166(3):

210–5.

7. Midthun DE. Solitary pulmonary nodule: time to

think small. Curr Opin Pulm Med 2000;6(4):364–70.

8. Hansell DM, Bankier AA, MacMahon H, et al.

Fleischner Society: glossary of terms for thoracic

imaging. Radiology 2008;246(3):697–722.

9. Remy-Jardin M, Remy J, Wallaert B, et al.

Subacute and chronic bird breeder hypersensi-

tivity pneumonitis: sequential evaluation with CT

and correlation with lung function tests and bron-

choalveolar lavage. Radiology 1993;189(1):111–8.

10. Brauner MW, Lenoir S, Grenier P, et al. Pulmonary

sarcoidosis: CT assessment of lesion reversibility.

Radiology 1992;182(2):349–54.

11. Costello P, Anderson W, Blume D. Pulmonary

nodule: evaluation with spiral volumetric CT. Radi-

ology 1991;179(3):875–6.

12. Hanamiya M, Aoki T, Yamashita Y, et al. Frequency

and significance of pulmonary nodules on thin-

section CT in patients with extrapulmonary malig-

nant neoplasms. Eur J Radiol 2012;81(1):152–7.

13. Henschke CI, McCauley DI, Yankelevitz DF, et al.

Early Lung Cancer Action Project: overall design

and findings from baseline screening. Lancet

1999;354(9173):99–105.

14. Gould MK, Fletcher J, Iannettoni MD, et al. Evalua-

tion of patients with pulmonary nodules: when is

it lung cancer? ACCP evidence-based clinical

practice guidelines (2nd edition). Chest 2007;

132(Suppl 3):108S–30S.

15. Wahidi MM, Govert JA, Goudar RK, et al. Evidence

for the treatment of patients with pulmonary

nodules: when is it lung cancer? ACCP evidence-

based clinical practice guidelines (2nd edition).

Chest 2007;132(Suppl 3):94S–107S.

16. Boone JM. Multidetector CT: opportunities, chal-

lenges, and concerns associated with scanners

with 64 or more detector rows. Radiology 2006;

241(2):334–7.

17. Swensen SJ, Jett JR, Sloan JA, et al. Screening for

lung cancer with low-dose spiral computed tomog-

raphy. Am J Respir Crit Care Med 2002;165(4):

508–13.

18. Austin JH, RomneyBM,Goldsmith LS. Missed bron-

chogenic carcinoma: radiographic findings in 27

patients with a potentially resectable lesion evident

in retrospect. Radiology 1992;182(1):115–22.

19. Quekel LG, Kessels AG, Goei R, et al. Miss rate of

lung cancer on the chest radiograph in clinical

practice. Chest 1999;115(3):720–4.

20. Turkington PM, Kennan N, Greenstone MA. Misin-

terpretation of the chest x ray as a factor in the

delayed diagnosis of lung cancer. Postgrad Med

J 2002;78(917):158–60.

21. Shah PK, Austin JH, White CS, et al. Missed non-

small cell lung cancer: radiographic findings of

potentially resectable lesions evident only in retro-

spect. Radiology 2003;226(1):235–41.

22. Muhm JR, Miller WE, Fontana RS, et al. Lung

cancer detected during a screening program using

four-month chest radiographs. Radiology 1983;

148(3):609–15.

23. Samuel S, Kundel HL, Nodine CF, et al. Mechanism

of satisfaction of search: eye position recordings in

the reading of chest radiographs. Radiology 1995;

194(3):895–902.

24. Kundel HL, Nodine CF, Toto L. Searching for lung

nodules. The guidance of visual scanning. Invest

Radiol 1991;26(9):777–81.

25. Tagashira H, Arakawa K, Yoshimoto M, et al.

Detectability of lung nodules using flat panel

detector with dual energy subtraction by two shot

method: evaluation by ROC method. Eur J Radiol

2007;64(2):279–84.

26. Fischbach F, Freund T, Rottgen R, et al. Dual-

energy chest radiography with a flat-panel digital

Page 17: Indeterminate Pulmonary Nodules

Management of Indeterminate Pulmonary Nodules 911

detector: revealing calcified chest abnormalities.

AJR Am J Roentgenol 2003;181(6):1519–24.

27. Balkman JD, Mehandru S, DuPont E, et al. Dual

energy subtraction digital radiography improves

performance of a next generation computer-aided

detection program. J Thorac Imaging 2010;25(1):

41–7.

28. Kano A, Doi K, MacMahon H, et al. Digital image

subtraction of temporally sequential chest images

for detection of interval change. Med Phys 1994;

21(3):453–61.

29. Ishida T, Ashizawa K, Engelmann R, et al. Applica-

tion of temporal subtraction for detection of interval

changes on chest radiographs: improvement of

subtraction images using automated initial image

matching. J Digit Imaging 1999;12(2):77–86.

30. McAdams HP, Samei E, Dobbins J 3rd, et al.

Recent advances in chest radiography. Radiology

2006;241(3):663–83.

31. Matsumoto T, Yoshimura H, Giger ML, et al. Poten-

tial usefulness of computerized nodule detection in

screening programs for lung cancer. Invest Radiol

1992;27(6):471–5.

32. MacMahon H, Engelmann R, Behlen FM, et al.

Computer-aided diagnosis of pulmonary nodules:

results of a large-scale observer test. Radiology

1999;213(3):723–6.

33. Johkoh T, Kozuka T, Tomiyama N, et al. Temporal

subtraction for detection of solitary pulmonary

nodules on chest radiographs: evaluation of a com-

mercially available computer-aided diagnosis sys-

tem. Radiology 2002;223(3):806–11.

34. Sieren JC, Ohno Y, Koyama H, et al. Recent

technological and application developments in

computed tomography and magnetic resonance

imaging for improved pulmonary nodule detection

and lung cancer staging. J Magn Reson Imaging

2010;32(6):1353–69.

35. Fischbach F, Knollmann F, Griesshaber V, et al.

Detection of pulmonary nodules by multislice com-

puted tomography: improved detection rate with

reduced slice thickness. Eur Radiol 2003;13(10):

2378–83.

36. MacMahonH, Austin JH,GamsuG, et al. Guidelines

for management of small pulmonary nodules de-

tected on CTscans: a statement from the Fleischner

Society. Radiology 2005;237(2):395–400.

37. Angel E, Yaghmai N, Jude CM, et al. Monte Carlo

simulations to assess the effects of tube current

modulation on breast dose for multidetector CT.

Phys Med Biol 2009;54(3):497–512.

38. Angel E, Yaghmai N, Jude CM, et al. Dose to radio-

sensitive organs during routine chest CT: effects of

tube current modulation. AJR Am J Roentgenol

2009;193(5):1340–5.

39. McCollough CH, Bruesewitz MR, Kofler JM Jr. CT

dose reduction and dose management tools:

overview of available options. Radiographics

2006;26(2):503–12.

40. McCollough CH, Primak AN, Braun N, et al. Strate-

gies for reducing radiation dose in CT. Radiol Clin

North Am 2009;47(1):27–40.

41. Moses DA, Ko JP. Multidetector CT of the solitary

pulmonary nodule. Semin Roentgenol 2005;40(2):

109–25.

42. Swensen SJ, Morin RL, Aughenbaugh GL, et al. CT

reconstruction algorithm selection in the evaluation

of solitary pulmonary nodules. J Comput Assist

Tomogr 1995;19(6):932–5.

43. Ahn MI, Gleeson TG, Chan IH, et al. Perifissural

nodules seen at CT screening for lung cancer.

Radiology 2010;254(3):949–56.

44. Diederich S, Semik M, Lentschig MG, et al. Helical

CT of pulmonary nodules in patients with extra-

thoracic malignancy: CT-surgical correlation. AJR

Am J Roentgenol 1999;172(2):353–60.

45. Gurney JW. Missed lung cancer at CT: imaging

findings in nine patients. Radiology 1996;199(1):

117–22.

46. Ko JP, Rusinek H, Naidich DP, et al. Wavelet

compression of low-dose chest CT data: effect

on lung nodule detection. Radiology 2003;228(1):

70–5.

47. ParkEA,GooJM,LeeJW,et al. Efficacyof computer-

aided detection system and thin-slab maximum

intensity projection technique in the detection of

pulmonary nodules in patients with resected metas-

tases. Invest Radiol 2009;44(2):105–13.

48. Rubin GD. Data explosion: the challenge of

multidetector-row CT. Eur J Radiol 2000;36(2):

74–80.

49. Kawel N, Seifert B, Luetolf M, et al. Effect of slab

thickness on the CT detection of pulmonary

nodules: use of sliding thin-slab maximum intensity

projection and volume rendering. AJR Am J Roent-

genol 2009;192(5):1324–9.

50. Hirose T, Nitta N, Shiraishi J, et al. Evaluation of

computer-aided diagnosis (CAD) software for the

detection of lung nodules on multidetector row

computed tomography (MDCT): JAFROC study

for the improvement in radiologists’ diagnostic

accuracy. Acad Radiol 2008;15(12):1505–12.

51. White CS, Pugatch R, Koonce T, et al. Lung nodule

CAD software as a second reader: a multicenter

study. Acad Radiol 2008;15(3):326–33.

52. Rubin GD, Lyo JK, Paik DS, et al. Pulmonary

nodules on multi-detector row CT scans: perfor-

mance comparison of radiologists and computer-

aided detection. Radiology 2005;234(1):274–83.

53. Awai K, Murao K, Ozawa A, et al. Pulmonary

nodules: estimation of malignancy at thin-section

helical CT-effect of computer-aided diagnosis on

performance of radiologists. Radiology 2006;

239(1):276–84.

Page 18: Indeterminate Pulmonary Nodules

Hodnett & Ko912

54. Kim KG, Goo JM, Kim JH, et al. Computer-aided

diagnosis of localized ground-glass opacity in the

lung at CT: initial experience. Radiology 2005;

237(2):657–61.

55. Jacobs C, Sanchez CI, Saur SC, et al. Computer-

aided detection of ground glass nodules in tho-

racic CT images using shape, intensity and context

features. Med Image Comput Comput Assist Interv

2011;14(Pt 3):207–14.

56. Okada T, Iwano S, Ishigaki T, et al. Computer-aided

diagnosis of lung cancer: definition and detection

of ground-glass opacity type of nodules by high-

resolution computed tomography. Jpn J Radiol

2009;27(2):91–9.

57. Ye X, Lin X, Beddoe G, et al. Efficient computer-

aided detection of ground-glass opacity nodules

in thoracic CT images. Conf Proc IEEE Eng Med

Biol Soc 2007;2007:4449–52.

58. Zwirewich CV, Vedal S, Miller RR, et al.

Solitary pulmonary nodule: high-resolution CT and

radiologic-pathologic correlation. Radiology 1991;

179(2):469–76.

59. Gurney JW, Swensen SJ. Solitary pulmonary

nodules: determining the likelihood of malignancy

with neural network analysis. Radiology 1995;

196(3):823–9.

60. Takashima S, Sone S, Li F, et al. Small solitary

pulmonary nodules (< or 51 cm) detected at

population-based CT screening for lung cancer:

reliable high-resolution CT features of benign

lesions. AJR Am J Roentgenol 2003;180(4):

955–64.

61. Suzuki K, Nagai K, Yoshida J, et al. Video-assisted

thoracoscopic surgery for small indeterminate

pulmonary nodules: indications for preoperative

marking. Chest 1999;115(2):563–8.

62. Ginsberg MS, Griff SK, Go BD, et al. Pulmonary

nodules resected at video-assisted thoracoscopic

surgery: etiology in 426 patients. Radiology 1999;

213(1):277–82.

63. Gohagan J, Marcus P, Fagerstrom R, et al. Baseline

findings of a randomized feasibility trial of lung

cancer screeningwith spiral CTscan vs chest radio-

graph: the Lung Screening Study of the National

Cancer Institute. Chest 2004;126(1):114–21.

64. Church TR. Chest radiography as the comparison

for spiral CT in the National Lung Screening Trial.

Acad Radiol 2003;10(6):713–5.

65. Zerhouni EA, Spivey JF, Morgan RH, et al. Factors

influencing quantitative CT measurements of soli-

tary pulmonary nodules. J Comput Assist Tomogr

1982;6(6):1075–87.

66. Swensen SJ, Silverstein MD, Ilstrup DM, et al.

The probability of malignancy in solitary pulmo-

nary nodules. Application to small radiologically

indeterminate nodules. Arch Intern Med 1997;

157(8):849–55.

67. Bankoff MS, McEniff NJ, Bhadelia RA, et al.

Prevalence of pathologically proven intrapulmo-

nary lymph nodes and their appearance on CT.

AJR Am J Roentgenol 1996;167(3):629–30.

68. Sykes AM, Swensen SJ, Tazelaar HD, et al.

Computed tomography of benign intrapulmonary

lymph nodes: retrospective comparison with sar-

coma metastases. Mayo Clin Proc 2002;77(4):

329–33.

69. Hyodo T, Kanazawa S, Dendo S, et al. Intrapulmo-

nary lymph nodes: thin-section CT findings, patho-

logical findings, and CT differential diagnosis from

pulmonary metastatic nodules. Acta Med Okayama

2004;58(5):235–40.

70. Xu DM, van der Zaag-Loonen HJ, Oudkerk M, et al.

Smooth or attached solid indeterminate nodules

detected at baseline CT screening in the NELSON

study: cancer risk during 1 year of follow-up. Radi-

ology 2009;250(1):264–72.

71. Heitzman ER, Markarian B, Raasch BN, et al.

Pathways of tumor spread through the lung: radio-

logic correlations with anatomy and pathology.

Radiology 1982;144(1):3–14.

72. Xu DM, van Klaveren RJ, de Bock GH, et al.

Limited value of shape, margin and CT density in

the discrimination between benign and malignant

screen detected solid pulmonary nodules of the

NELSON trial. Eur J Radiol 2008;68(2):347–52.

73. Siegelman SS, Zerhouni EA, Leo FP, et al. CTof the

solitary pulmonary nodule. AJR Am J Roentgenol

1980;135(1):1–13.

74. Girvin F, Ko JP. Pulmonary nodules: detection,

assessment, and CAD. AJR Am J Roentgenol

2008;191(4):1057–69.

75. Winer-Muram HT. The solitary pulmonary nodule.

Radiology 2006;239(1):34–49.

76. Onn A, Choe DH, Herbst RS, et al. Tumor

cavitation in stage I non-small cell lung cancer:

epidermal growth factor receptor expression and

prediction of poor outcome. Radiology 2005;

237(1):342–7.

77. Woodring JH, Fried AM. Significance of wall thick-

ness in solitary cavities of the lung: a follow-up

study. AJR Am J Roentgenol 1983;140(3):473–4.

78. Honda O, Tsubamoto M, Inoue A, et al. Pulmonary

cavitary nodules on computed tomography: differ-

entiation of malignancy and benignancy. J Comput

Assist Tomogr 2007;31(6):943–9.

79. Oda S, Awai K, Liu D, et al. Ground-glass opacities

on thin-section helical CT: differentiation between

bronchioloalveolar carcinoma and atypical adeno-

matous hyperplasia. AJR Am J Roentgenol 2008;

190(5):1363–8.

80. Erasmus JJ, Connolly JE, McAdams HP, et al. Soli-

tary pulmonary nodules: part I. Morphologic evalu-

ation for differentiation of benign and malignant

lesions. Radiographics 2000;20(1):43–58.

Page 19: Indeterminate Pulmonary Nodules

Management of Indeterminate Pulmonary Nodules 913

81. Diederich S, Wormanns D, Semik M, et al. Screen-

ing for early lung cancer with low-dose spiral CT:

prevalence in 817 asymptomatic smokers. Radi-

ology 2002;222(3):773–81.

82. Hamper UM, Khouri NF, Stitik FP, et al. Pulmonary

hamartoma: diagnosis by transthoracic needle-

aspiration biopsy. Radiology 1985;155(1):15–8.

83. Mahoney MC, Shipley RT, Corcoran HL, et al. CT

demonstration of calcification in carcinoma of the

lung. AJR Am J Roentgenol 1990;154(2):255–8.

84. Seo JB, Im JG, Goo JM, et al. Atypical pulmonary

metastases: spectrum of radiologic findings.

Radiographics 2001;21(2):403–17.

85. Grewal RG, Austin JH. CT demonstration of calcifi-

cation in carcinoma of the lung. J Comput Assist

Tomogr 1994;18(6):867–71.

86. Henschke CI, Yankelevitz DF, Mirtcheva R, et al. CT

screening for lung cancer: frequency and signifi-

cance of part-solid and nonsolid nodules. AJR

Am J Roentgenol 2002;178(5):1053–7.

87. Ko JP. Lung nodule detection and characterization

with multi-slice CT. J Thorac Imaging 2005;20(3):

196–209.

88. Kim HY, Shim YM, Lee KS, et al. Persistent pulmo-

nary nodular ground-glass opacity at thin-section

CT: histopathologic comparisons. Radiology 2007;

245(1):267–75.

89. Godoy MC, Naidich DP. Subsolid pulmonary

nodules and the spectrum of peripheral adenocar-

cinomas of the lung: recommended interim guide-

lines for assessment and management. Radiology

2009;253(3):606–22.

90. Noguchi M, Shimosato Y. The development

and progression of adenocarcinoma of the lung.

Cancer Treat Res 1995;72:131–42.

91. Travis WD, Brambilla E, Noguchi M, et al. Interna-

tional Association for the Study of Lung Cancer/

American Thoracic Society/European Respiratory

Society international multidisciplinary classification

of lung adenocarcinoma. J Thorac Oncol 2011;

6(2):244–85.

92. Travis WD, Brambilla E, Noguchi M, et al. Interna-

tional Association for the Study of Lung Cancer/

American Thoracic Society/European Respiratory

Society: international multidisciplinary classifica-

tion of lung adenocarcinoma: executive summary.

Proc Am Thorac Soc 2011;8(5):381–5.

93. Aoki T, Nakata H, Watanabe H, et al. Evolution

of peripheral lung adenocarcinomas: CT findings

correlated with histology and tumor doubling

time. AJR Am J Roentgenol 2000;174(3):763–8.

94. Li F, Sone S, Abe H, et al. Malignant versus benign

nodules at CT screening for lung cancer: compar-

ison of thin-section CT findings. Radiology 2004;

233(3):793–8.

95. Lee HJ, Goo JM, Lee CH, et al. Predictive CT find-

ings of malignancy in ground-glass nodules on

thin-section chest CT: the effects on radiologist

performance. Eur Radiol 2009;19(3):552–60.

96. Georgiadou SP, Sipsas NV, Marom EM, et al. The

diagnostic value of halo and reversed halo signs

for invasive mold infections in compromised hosts.

Clin Infect Dis 2011;52(9):1144–55.

97. Kim SJ, Lee KS, Ryu YH, et al. Reversed halo sign

on high-resolution CT of cryptogenic organizing

pneumonia: diagnostic implications. AJR Am J

Roentgenol 2003;180(5):1251–4.

98. Lillington GA, Caskey CI. Evaluation and manage-

ment of solitary and multiple pulmonary nodules.

Clin Chest Med 1993;14(1):111–9.

99. Hasegawa M, Sone S, Takashima S, et al. Growth

rate of small lung cancers detected on mass CT

screening. Br J Radiol 2000;73(876):1252–9.

100. Kakinuma R, Ohmatsu H, Kaneko M, et al. Progres-

sion of focal pure ground-glass opacity detected

by low-dose helical computed tomography screen-

ing for lung cancer. J Comput Assist Tomogr 2004;

28(1):17–23.

101. Yankelevitz DF, Henschke CI. Does 2-year stability

imply that pulmonary nodules are benign? AJR Am

J Roentgenol 1997;168(2):325–8.

102. Zhao B, Yankelevitz D, Reeves A, et al. Two-dimen-

sional multi-criterion segmentation of pulmonary

nodules on helical CT images. Med Phys 1999;

26(6):889–95.

103. Yankelevitz DF, Gupta R, Zhao B, et al. Small

pulmonary nodules: evaluation with repeat CT–

preliminary experience. Radiology 1999;212(2):

561–6.

104. Erasmus JJ, McAdams HP, Connolly JE. Solitary

pulmonary nodules: part II. Evaluation of the

indeterminate nodule. Radiographics 2000;20(1):

59–66.

105. Wang Y, de Bock GH, van Klaveren RJ, et al. Volu-

metric measurement of pulmonary nodules at low-

dose chest CT: effect of reconstruction setting on

measurement variability. Eur Radiol 2010;20(5):

1180–7.

106. Rampinelli C, De Fiori E, Raimondi S, et al. In vivo

repeatability of automated volume calculations of

small pulmonary nodules with CT. AJR Am J Roent-

genol 2009;192(6):1657–61.

107. Goodman LR, Gulsun M, Washington L, et al.

Inherent variability of CT lung nodulemeasurements

in vivo using semiautomated volumetric mea-

surements. AJR Am J Roentgenol 2006;186(4):

989–94.

108. Swensen SJ. Functional CT: lung nodule evalua-

tion. Radiographics 2000;20(4):1178–81.

109. Swensen SJ. Lung nodules: enchantment with en-

hancement. J Thorac Imaging 1995;10(2):89–90.

110. Johnson TR, Krauss B, Sedlmair M, et al. Material

differentiation by dual energy CT: initial experience.

Eur Radiol 2007;17(6):1510–7.

Page 20: Indeterminate Pulmonary Nodules

Hodnett & Ko914

111. Chae EJ, Song JW, Seo JB, et al. Clinical utility of

dual-energy CT in the evaluation of solitary pulmo-

nary nodules: initial experience. Radiology 2008;

249(2):671–81.

112. Lowe VJ, Fletcher JW, Gobar L, et al. Prospective

investigation of positron emission tomography in

lung nodules. J Clin Oncol 1998;16(3):1075–84.

113. Patz EF Jr, Lowe VJ, Hoffman JM, et al. Focal

pulmonary abnormalities: evaluation with F-18 fluo-

rodeoxyglucose PET scanning. Radiology 1993;

188(2):487–90.

114. Rohren EM, Turkington TG, Coleman RE. Clinical

applications of PET in oncology. Radiology 2004;

231(2):305–32.

115. Erasmus JJ, McAdams HP, Patz EF Jr, et al. Evalu-

ation of primary pulmonary carcinoid tumors using

FDG PET. AJR Am J Roentgenol 1998;170(5):

1369–73.

116. Higashi K, Ueda Y, Seki H, et al. Fluorine-18-FDG

PET imaging is negative in bronchioloalveolar

lung carcinoma. J Nucl Med 1998;39(6):1016–20.

117. Hain SF, Curran KM, Beggs AD, et al. FDG-PET as

a "metabolic biopsy" tool in thoracic lesions with

indeterminate biopsy. Eur J Nucl Med 2001;28(9):

1336–40.

118. Rivera MP, Mehta AC. Initial diagnosis of lung

cancer: ACCP evidence-based clinical practice

guidelines (2nd edition). Chest 2007;132(Suppl 3):

131S–48S.

119. Saita S, Tanzillo A, Riscica C, et al. Bronchial

brushing and biopsy: a comparative evaluation in

diagnosing visible bronchial lesions. Eur J Cardio-

thorac Surg 1990;4(5):270–2.

120. Cox ID, Bagg LR, Russell NJ, et al. Relationship of

radiologic position to the diagnostic yield of fiber-

optic bronchoscopy in bronchial carcinoma. Chest

1984;85(4):519–22.

121. Flower CD, Verney GI. Percutaneous needle biopsy

of thoracic lesions—an evaluation of 300 biopsies.

Clin Radiol 1979;30(2):215–8.

122. Klein JS, Zarka MA. Transthoracic needle biopsy.

Radiol Clin North Am 2000;38(2):235–66, vii.

123. Klein JS, Salomon G, Stewart EA. Transthoracic

needle biopsy with a coaxially placed 20-gauge

automated cutting needle: results in 122 patients.

Radiology 1996;198(3):715–20.

124. Moore EH. Technical aspects of needle aspiration

lung biopsy: a personal perspective. Radiology

1998;208(2):303–18.

125. Boiselle PM, Shepard JA, Mark EJ, et al. Routine

addition of an automated biopsy device to fine-

needle aspiration of the lung: a prospective assess-

ment. AJR Am J Roentgenol 1997;169(3):661–6.

126. Geraghty PR, Kee ST, McFarlane G, et al. CT-

guided transthoracic needle aspiration biopsy of

pulmonary nodules: needle size and pneumo-

thorax rate. Radiology 2003;229(2):475–81.

127. Miller JA, PramanikBK, LavenharMA.Predicting the

rates of success and complications of computed

tomography-guided percutaneous core-needle

biopsies of the thorax from the findings of the pre-

procedure chest computed tomography scan.

J Thorac Imaging 1998;13(1):7–13.

128. Westcott JL, Rao N, Colley DP. Transthoracic nee-

dle biopsy of small pulmonary nodules. Radiology

1997;202(1):97–103.

129. Westcott JL. Percutaneous transthoracic needle

biopsy. Radiology 1988;169(3):593–601.

130. Wiener RS, Schwartz LM, Woloshin S, et al. Popu-

lation-based risk for complications after transtho-

racic needle lung biopsy of a pulmonary nodule:

an analysis of discharge records. Ann Intern Med

2011;155(3):137–44.

131. Daly BD, Faling LJ, Diehl JT, et al. Computed

tomography-guided minithoracotomy for the resec-

tion of small peripheral pulmonary nodules. Ann

Thorac Surg 1991;51(3):465–9.

132. Krasna MJ, Deshmukh S, McLaughlin JS. Compli-

cations of thoracoscopy. Ann Thorac Surg 1996;

61(4):1066–9.

133. Gurney JW. Determining the likelihood of malig-

nancy in solitary pulmonary nodules with Bayesian

analysis. Part I. Theory. Radiology 1993;186(2):

405–13.

134. Gurney JW, Lyddon DM, McKay JA. Determining

the likelihood of malignancy in solitary pulmonary

nodules with Bayesian analysis. Part II. Applica-

tion. Radiology 1993;186(2):415–22.

135. Gould MK, Ananth L, Barnett PG. A clinical model

to estimate the pretest probability of lung cancer

in patients with solitary pulmonary nodules. Chest

2007;131(2):383–8.

136. Cummings SR, Lillington GA, Richard RJ. Esti-

mating the probability of malignancy in solitary

pulmonary nodules. A Bayesian approach. Am

Rev Respir Dis 1986;134(3):449–52.

137. Swensen SJ. CTscreening for lung cancer. AJR Am

J Roentgenol 2002;179(4):833–6.

138. Eisenberg RL, Bankier AA, Boiselle PM. Com-

pliance with Fleischner Society guidelines for

management of small lung nodules: a survey of

834 radiologists. Radiology 2010;255(1):218–24.

139. MacMahon H. Compliance with Fleischner

Society guidelines for management of lung nod-

ules: lessons and opportunities. Radiology 2010;

255(1):14–5.

140. Revel MP, Bissery A, Bienvenu M, et al. Are two-

dimensional CT measurements of small noncalci-

fied pulmonary nodules reliable? Radiology 2004;

231(2):453–8.

141. Zhang L, Yankelevitz DF, Henschke CI, et al.

Zone of transition: a potential source of error in

tumor volume estimation. Radiology 2010;256(2):

633–9.


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