Model Based Iterative Reconstructions represent a paradigm ... · Philips Healthcare on CT imaging. iDose Iterative Reconstructions (IR) IMR Model Based Iterative Reconstructions

Jonas Rydberg, M.D.

Professor of Radiology

Indiana University School of Medicine

Indianapolis, Indiana

Medical Director

Radiology

IU Health Methodist Hospital

Model Based Iterative Reconstructions

represent a paradigm shift

- Imaging with almost no noise

Jonas Rydberg [email protected]

Disclaimer: IU Health Methodist Hospital collaborates with Philips Healthcare on CT imaging.

iDose Iterative Reconstructions (IR)

IMR Model Based Iterative Reconstructions (MBIR)

The experience shared in this presentation is based on work with iDose (IR) and IMR (MBIR) both Philips Healthcare. But, only the terms “IR” and “MBIR” will be used to name the two techniques.


Iterative reconstructions (IR)

- Radiation dose reduction 50% or more

Model Based Iterative Reconstructions (MBIR)

- More radiation dose reduction

- Improve the diagnostic image quality

Conclusions from body imaging

and CTA:


CTDIvol (mGy)

4.81

CTDIvol (mGy)

5.74

CTDIvol (mGy)

17.5

300 mAs 98 mAs 71 mAs

Iterative reconstructions (IR):

Same patient scanned using IR on different occasions with

different reference mAs. Significant dose reductions possible.


Radiation dose reduction Abdomen-Pelvis with IR

FBP: 120 kVp Ref mAs 300 19.6 mGy IR: 120 kVp Ref mAs 173 11.8 mGy

Radiation dose reduction

= 40 %

(More recently we have moved the Reference mAs to 154 = 50% radiation dose reduction.)


Radiation dose reduction Abd/Pel with MBIR

FBP: 120 kVp Ref mAs 300 19.6 mGy IR: 120 kVp Ref mAs 173 11.8 mGy MBIR: 100 kVp Ref mAs 154 6.7 mGy

Radiation dose reduction

= 66 %


There are no extreme cases of radiation dose reduction presented here. All cases in this presentation were scanned with our standard IR (iDose level 4) kVp = 120 kVp Reference mAs = 173 or higher The purpose was to explore if MBIR could add diagnostic quality instead of just reducing the radiation dose.


FBP / IR MBIR

MBIR – A challenge for radiologists

Hard to accept this look


Even tougher challenge with non-enhanced scans

MBIR

Bland

Water colors

“Monet effect”

FBP / IR

Radiologist reactions:

Not right

Waxy

Texture missing Jonas Rydberg [email protected]

MBIR FBP / IR

Can you handle the truth?

The difference is reduced noise!


Texture?!

Is there such a thing as “texture” in CT images?


“Texture”


Random page from Radiographics 2013

Please, take a few seconds to

review the “texture” of mets

and liver parenchyma.

Random page from Radiographics 2013

“Texture”

For the past 30 years I have been convinced that I have viewed the texture in both liver parenchyma and metastasis.

“Am I wrong?”


FBP IR MBIR Filtered back projection Iterative reconstructions

Model Based Iterative reconstructions

”Texture” of liver metastasis

Somewhat strangely the ”texture” decreases with MBIR. Likewise strangely the texture of the metastasis and the liver parenchyma seems to be the same on both FBP and IR.

Does fluid in urinary bladder have “texture”? Which image is closest to the truth?

IR MBIR

130167039

What shall fluid in the stomach look like? Like IR or MBIR?

The same question then regarding liver!

130167039

IR MBIR

What shall kidneys look like?

Maybe MBIR depiction is closest to truth?

130167039

IR MBIR

How about the air around the patient?

FBP IR MBIR


FBP IR MBIR

How about the air around the patient?


Texture?

There is no such thing as “texture” as we have always believed.

- It is just noise to varying degrees!


Texture of a renal cancer

CT140015501

IR MBIR

Cancer + noise There are multiple black and white noise pixels projecting over the tumor that we take

for texture of the mass.

Cancer


“Black noise” and “White noise” Reducing image noise has been one of the major goals for the CT development during the past 35 years. We are so used of seeing noise that we barely are aware of it. It has gone so far that the noise reduction with MBIR can creates confusion radiologists. Noise destroys the diagnostic quality of the images. To better understand the negative effect of noise in FBP and IR I think in terms of “Black noise” and “White noise”. That will be discussed in the following cases. Please, note that the black and white noise is an expression that I have adopted based on my own observations. You may see it expressed in other terms in the literature. The “noise” is typically quantified and expressed in standard deviations (SD).

MBIR improves diagnostic quality.

The following examples intend to show how MBIR improves the

diagnostic quality over FBP and IR.


8 mm cyst in liver

Depiction superior with MBIR

8 mm

IR MBIR


Unenhanced scan with slice thickness = 4 mm

IR - “White noise” degrades depiction of both the center and the border of the cyst

IR MBIR


Compare “Avg HU” and “SD”

If slice thickness is decreased to 1 mm noise hurts the IR technique

IR MBIR

MBIR is noise resilient even

at 1 mm slice thickness


IR MBIR

4 mm slice thickness depicts cyst better than

1 mm but there is a price to pay with

increased partial volume averaging.


FBP IR MBIR


IR MBIR FBP

Which technique depicts cysts the truest?


IR MBIR FBP


IR MBIR FBP



IR MBIR FBP

IR MBIR FBP


IR MBIR


IR MBIR


IR MBIR

4 mm 1 mm 4 mm 1 mm


Between yellow arrows clear border delineating higher and lower density tissues.





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Model Based Iterative Reconstructions represent a paradigm ... · Philips Healthcare on CT imaging. iDose Iterative Reconstructions (IR) IMR Model Based Iterative Reconstructions