Controlling Variability in Lung Cancer Response AssessmentRicardo S. AvilaMay 13, 2010

Therapy AssessmentCharacteristics Late stage Thick Slice CT

Assessment Tumor response ID new lesions ?

Tumor Size

4 cm lesion

t ? TimeStart Therapy Assess Response

RECIST8mm D, 13 pixels 73% Volume

Target Lesion Measurement RECIST: Sum of LD

Progressive Disease

D = +20%Unaided Interpretation

Stable Diseaseweeks

4cm lesion

D = -30%

Partial Response

TimeBaseline & Treat

Complete Response

Erasmus et. al., JCO 2003 Intra-observer error PD: 9.5% of tumors PR:3% of tumors Inter-observer error PD: 30% of tumors PR: 14% of tumors

Assess Response

We Can Do BetterTarget Lesion Measurement RECIST: Sum of LDProgressive Disease

Improve Accurac y Precisio n To Improve Interval (Dt) Study NAided 3D Interpretation

t TimeEarly Detection & Nodule Sizing

Complete Response

Partial Response

Stable Disease

4cm lesion

Detecting a 50 Micron Displacement

Patton and Byron Nature Reviews Drug Discovery 2007

Computed TomographySiemens Emotion 16 16 Slice Scanner 1.00mm Slice Thickness

B30s Kernel

B60s Kernel

GE LightSpeed Ultra 8 Slice Scanner 1.25mm Slice Thickness

Very Low Dose

Low Dose

Measurement Challenges

Patient/Lesion Presentation Size Complexity Changes over time (necrosis)

Scanners Hardware (collimation) Software (releases)

Protocols ScanRx Contrast Patient position

Observer Seed points/ROI Data Interpretation5mm 2.5mm

Volumetric Algorithm ChallengesBoundary Identification ChallengesNo/Small I

Vascular network (Ev) Bronchial network (Eb) Pleura (Ep) Sub-voxel edge (Es)

Errors at 2 time points

Ev

Volumetric error strongly depends on lesion size and slice thickness

Ep EsPl e ur a

Technical Focus Areas Open Image Archives LCAs Give-A-Scan Project OSAs Interactive Science Publishing RSNAs Ad Hoc Committee on Open Image Archives

Understanding Measurement Performance Benchmarks: NIST Biochange and Volcano QIBA: Phantom Data Studies QIBA: Measurement Performance on Clinical Data Kitware Pocket Phantom

Open Source Algorithms and Models Lesion Sizing Toolkit COPD Modeling and Quantification

Establishing Standards for Clinical Trials QIBA: Volumetric CT Profiles

Quantitative Identification of Patient Sub-Populations

Analysis of imaging and clinical data can potentially identify patient populations that respond more favorably to lung cancer therapy

Drug Efficacy Lung Damage Assessment COPD impacts aerosolized drug delivery Lung Cancer Risk

Safety Cardiovascular damage

Lung Cancer Alliances Give-A-Scan Project

A Lung Cancer Alliance Project Pilot project started in 2008 Process and procedures were created for accepting and anonymizing datasets ~30 individuals expressed interest in participating 17 scans received, but 2 were not readable Over 6 GB of image and meta data was collected 9 patient scans have been prepared for public dissemination on a LCA website.

Give-A-Scan WebsiteDataset includes: Age Gender Cancer Type Cancer Stage Family History

4 of the 9 subjects are never smo

Legal DocumentsA large amount of effort spent on developing the legal framework Informed Consent End User License

An open set of legal resources for open image archives would benefit many projects

New CT Pocket Phantom

New CT Pocket Phantom

Goal: To characterize the fundamental imaging characteristics of CT acquisitions performed in the Roche ABIGAIL study 3D Resolution & Sampling Rate Noise Characteristics X-ray Attenuation Performance

Acrylic

Delrin

Teflon

Urethane

New CT Pocket Phantom Manufactured 21 phantoms and deployed them into the Abigail phase II clinical trial

Fully Automated Phantom Analysis

Several Studies UnderwayResolution vs. Distance to IsocenterIn-Plane PSF = 0.53 mm D = 112 mm = 0.45 mm = 0.47 mm = 0.54 mm D = 49 mm D = 62 mm D = 118 mm

= 0.53 mm = 0.45 mm = 0.44 mm = 0.51 mm D = 114 mm D = 43 mm D = 32 mm D = 104 mm

Standard Kernel Bone Kernel Lung Kernel

Comparison of the New Pocket Phantom with a Catphan Phantom

Calibration Study Siemens Sensation 64 CT Scanner 6 pocket phantoms placed in/near an anthropomorphic chest phantom Catphan phantom also scanned Varied slice thickness, mA, kVp, and pitch

Pearsons Correlation Coefficients CT Density = 0.999 (P < 0.001) Noise = 0.940 (P < 0.001) Resolution = 0.929 (P < 0.001)

Open Source Lesion Sizing Toolkit

The Lesion Sizing Toolkit

http://public.kitware.com/LesionSizingKit/

The Lesion Sizing Toolkit (LST) is a free and open source software architecture designed to accelerate the development and evaluation of quantitative lesion sizing algorithms.

Developed in 2008 Focused on Dissemination in 2009RSNA Quantitative Reading Room of the Future Showcase Open Source Medical Imaging Software Course Benchmarks Volcano 2009

OSA ISP Special Issue on Imaging for Early Lung Cancer Detection

Lung Cancer Risk

Lung Cancer Formation Significant tissue damage occurs as a result of particulate matter (PM) deposition

Hyaline Cartilage

Deposition is a function of air flow dynamics and PM characteristics Histology and CFD has shown up to a 100x greater PM deposition at: Airway bifurcations

[Broday, Aerosol Science and Tech. 2004]

Respiratory bronchioles

[Churg & Brauer, Ultrastructural Path. 2000]

Bifurcation and peripheral lung tissues likely exhibit some of the earliest preneoplastic changes in response to PM exposure

Balashazy et al., J Appl Physiol 2003.

Bifurcation Calcification in HRCT

Bifurcation Calcification Open Image Archive

1.25mm Slice Thickness w/ Bone K

Lung Cancer Risk Index (LCRI)

Features1. Bifurcation Damage Index (BDI) HRCT w/ B60f edge enhancing kernel Mean of 5 airway bifurcations(~20min)

2. FEV1/FVC Decline associated with lung cancer risk Follow ATS spirometry guidelines

BD

CD

ClassifierMethod is Independent of Age, Gender, Pack Years

Linear

BDI vs. FEV1/FVCHi gh er

Hi gh er

Regression line is for cancer cases scanned at 1mm slice thickness and FEV1/FVC > 55%

Lo w er

Lo we r

Initial Performance AnalysisDataset Conditional Logistic Regression Cochran-Mantel-Haenszel(Odds ratio for a 0.033 in LCRI with (crude estimate) 1:3 matching )

108 Cases Full Dataset

OR = 1.84 CI: 1.18-2.85 p-value = 0.0067 OR = 2.89 CI: 1.02-8.19 p-value = 0.0467

67% sensitive 72% specific

79 Cases 1mm Only

100% sensitive 74% specific

Conclusion: Individuals with higher LCRI are more likely to have lung cancer

Data on 21 Cancers and 121 ControlsCOPDPr ox im al

Di st al

Lu ng

COPD

Ca nc er

Lung Cancer Risk Findings Investigating a new quantitative imaging biomarker Airway bifurcations are calcifying in a relationship with FEV1/FVC In control cases, a significant trend observed between LCRI and age*pack years (P = 0.006) Odds Ratio for LCRI is better than FEV1/FVC LCRI = 2.73 (CI: 1.35-5.51, P = 0.005) = 0.44 (CI: 0.24-0.83, P = 0.005)

FEV1/FVC

Opportunities exist to identify new lung cancer patient sub-populations

Give-A-Scan Patient Donated Dataset Never Smoker, Cancer at 62, FEV1/FVC=84%

Right

2.5mm Scan Standard Kernel

Left

Measuring ProgressInterim Meetings

7 Workshops since 2004 1 Interim COPD Meeting Annual Workshop PCF/Cornell Database NCIA Give-A-Scan COPDGene? Large Open Image Databases

QIBA FDA NIST Standards & FDA Approval

Reproducibil ity & Comparison Early Clinical Trials BioChange & Volcano QIBA Studies

Accelerate Developme nt of Therapy Assessmen t Methods

Algorithms & Reference Methods Open Source Lesion Sizing Toolkit CT COPD Algorithms

Publications

Oncology Workshop Reports Quantitative CT Monograph ISP Oncology Special Issue

Thank You

Lung Cancer Risk Index Cancers and Age & PY Matched Controls (+/-10)

PY = Age =

5 64

15 51

20 59

28 51

30 57

40 48

45 58

59 60

60 69

63 54

66 64

68 57

72 68 74

75 62

92

Cancer Subjects Sorted by Increasing Pack Years A control case was permitted to be used for more than 1 cancer case

Lung Cancer Risk Index Cancers and Age & PY Matched Controls

1.0 mm CT Thickness Threshold

1.25 mm CT Thickness Threshold

PY = Age =

5 64

15 51

20 59

28 51

30 57

40 48

45 58

59 60

60 69

63 54

66 64

68 57

72 68 74

75 62

92

Cancer Subjects Sorted by Increasing Pack Years A control case was permitted to be used for more than 1 cancer case

(We are now using FEV1/FVC before bronchodilator)

New Study Results

(We are now using FEV1/FVC before bronchodilator)Thymom a

New Study Results

Carcinoid of the Thymus

AAH