Haimo Liu: haimo.liu@fda.hhs.gov

Evaluation of clinical Full Field Digital

Mammography with the Task-Specific-

System-Model-Based Fourier (TSMF)

SNR

Haimo Liu

Fischell Department of Bioengineering

University of Maryland-College Park

FDA CDRH OSEL/DIAM

Haimo Liu: haimo.liu@fda.hhs.gov

Task specific evaluation methodologyDevelopmentBenefits of using phantom for FFDM image quality assessment

Application on clinical systemsGE Senographe DS

Comparison between two image acquisition modesValidation of the method

Hologic Selenia

Conclusion

2

Outline

Haimo Liu: haimo.liu@fda.hhs.gov

Background: current FFDM evaluation

FFDM system

performance

Mean pixel value,

standard deviationClinical trials

Human observers:

radiologists

Expensive,

time consuming

3

Suffer from

reader’s variability

Pixel SNR

Limitations:

background

variability, signal

shape and size

Fourier based

method

Does not account

for scatter, focal

spot unsharpness

Detector based:

MTF, NPS

DQE

Image based

method

Hotelling SNR

Large number

of images

Diff. signal

Cov. matrix

No system

model

Haimo Liu: haimo.liu@fda.hhs.gov

Motivation

4

X-ray tube

Detector

Compression paddle

Computer console

Develop Fourier based evaluation methodology for clinical FFDM systems

Entire FFDM image acquisition

With phantom that models breast attenuation

Objective, task based

Practical, collection of limited number of images

Empirical model of the system, results not limited to specific settings

Haimo Liu: haimo.liu@fda.hhs.gov

Linear system

No non-linear/adaptive image processing

Cyclostationary system

Stationary noise

Shift-invariant system transfer function

Infinite detector area

5

Assumptions

Haimo Liu: haimo.liu@fda.hhs.gov6

Phantom assembly

Inspired by the CDMAM phantom

Same uniform background

Same HVL

Simulated signals

Uniform PMMA plates

Four 1 cm plates

Aluminum plate

0.5 mm thick

Model the Aluminum base (where signals are attached to) of the CDMAM phantom

Haimo Liu: haimo.liu@fda.hhs.gov

Clinical systems

7

System GE SenograheDS

Hologic Selenia

Detector Indirect Direct

Pixel size 0.1mm ×0.1mm 0.07mm ×0.07mm

Kvp 30 30

Target/Filter

Mo/Mo Mo/Mo

Image acquisitionmode

A:Fine View ModeB:Standard Mode

Phantom Mode

Grid Linear Cross-hatch grid

Haimo Liu: haimo.liu@fda.hhs.gov8

System schematic

Haimo Liu: haimo.liu@fda.hhs.gov9

Generalized Modulation Transfer Function (GMTF)

GMTFThe modulus of the Fourier transformation of the line response function measured within the breast phantom

Five images of a copper edge placed between the PMMA plates

Three detector entrance exposuresConvert to mean glandular doses

2D GMTFSpline interpolation between 1D profiles along the two axesX direction: parallel to chest wall Y direction: perpendicular to chest wall

Haimo Liu: haimo.liu@fda.hhs.gov10

Evaluation of scatter removal method (GE)

MTF (x direction)100 mAs, x-direction

Without phantom

System without grid gives better performance

GMTF(x direction)100 mAs, x-direction

With phantom placed in

the FOV

System with grid gives

better performance

Haimo Liu: haimo.liu@fda.hhs.gov

GMTF (x direction) for two clinical systems

11

GE

Haimo Liu: haimo.liu@fda.hhs.gov12

GMTF along the two axes

Haimo Liu: haimo.liu@fda.hhs.gov13

Generalized Normalized Noise Power Spectrum (GNNPS)

GNNPS

The square of the Fourier transformation of the system

noise measured at the center of the breast phantom

Five images of the background phantom

Three detector entrance exposures

Convert to mean glandular doses

Haimo Liu: haimo.liu@fda.hhs.gov14

GNNPS (x direction) for two clinical systems

Haimo Liu: haimo.liu@fda.hhs.gov

Simulated gold

disc signals

inspired by the

CDMAM phantom

15

Hotelling observer SNR

SNR² =

2 2GMTF2

GNNPS

Difference signal2

Haimo Liu: haimo.liu@fda.hhs.gov

Phantom Image based method

(image based signal: SI):

16

Methodology validation – comparison between methods

T -1

I ISNR = ΔS K ΔS

2 2

sFT[ ]SNR

GMTF ΔS=

GNNPS

2

I

19 19

FT[ ]SNR

ΔS=

GNNPS

2

I

256 256

FT[ ]SNR

ΔS=

GNNPS

Fourier based method with

simulated signals (Ss):

Fourier based method with

phantom image based signals,

GNNPS ROI size 19×19:

Fourier based method with

phantom image based signals,

GNNPS ROI size 256×256:

Haimo Liu: haimo.liu@fda.hhs.gov17

Methodology validation

Haimo Liu: haimo.liu@fda.hhs.gov

Contrast-Detail

(CD) curveFour alternative forced choice (4 AFC) task

Link SNR to detection probability

62.5% detection probability as the threshold

Threshold thicknessGenerate CD curve

18

Contrast-Detail curve

Haimo Liu: haimo.liu@fda.hhs.gov19

Contrast-Detail curve: system performance prediction

CD curve at unit doseSNR2 is linearly proportional to dose

Normalize SNR by dose

Normalize CD curve by dose

Can be used to predict system performance

Two clinical systemsDifferent noise and deterministic properties

Identical CD curves

Haimo Liu: haimo.liu@fda.hhs.gov

Human performance prediction (GE Senographe DS)

TSMF CD curve at 51 μGy

TSMF CD curve (adjusted by human efficiency) at 51 μGy

Human CD curve at 70 μGy (GE Senographe 2000D)

Human CD curve at 140 μGy (GE Senographe 2000D)

20

Contrast-Detail curve: human performance prediction

2

HumanHuman 2

TSMF

SNRF 30% 5%

SNR

Haimo Liu: haimo.liu@fda.hhs.gov

Fourier based evaluation methodology for clinical FFDMProvide more information of the system using phantom

Scatter from the phantom

Focal spot unsharpness

Magnification

Create a model of the systemNot limited to specific system settings

Predict system performance

Get closer to link image quality to diagnostic performance of the system

Clinical applicationGE Senographe

Hologic Selenia

21

Conclusions