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1 History and Lessons from FDA Regulation of Digital Radiology Kyle J. Myers, Ph.D. Division of Imaging and Applied Mathematics OSEL/CDRH/FDA October 22,

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Presentation on theme: "1 History and Lessons from FDA Regulation of Digital Radiology Kyle J. Myers, Ph.D. Division of Imaging and Applied Mathematics OSEL/CDRH/FDA October 22,"— Presentation transcript:

1 1 History and Lessons from FDA Regulation of Digital Radiology Kyle J. Myers, Ph.D. Division of Imaging and Applied Mathematics OSEL/CDRH/FDA October 22, 2009

2 2 From film-based to digital radiological imaging systems 1890s Roentgen discovers x-rays (film) 1970s Rare-earth phosphor screens 1976Medical device amendments 1990s Solid state flat panel detectors

3 3 Digital Radiography –510(k) for all applications other than mammography No new types of safety or effectiveness questions –PMA required for full-field digital mammography For imaging entire breast at once Not small detectors used for local, diagnostic views

4 4 Full-field digital mammography –FDA assumed device would be used for screening; barred diagnostic-only claim –Target population is ALL women over 50 –Sensitivity and specificity impact safety and effectiveness, with potentially large consequences to public health Missed cancers will not be screened again for 1 yr Increase in false positives comes with additional exams, biopsy, patient anxiety

5 5 Why full-field digital mammography raised new questions: –High demand for resolution Impact of discrete image pixels on visibility of microcalcifications and lesion margins? –Dynamic range of digital >> film Potential for higher doses (not “self-limiting” like film) –Large image formats Image stitching? Other artifacts? E.g., dead pixels, rows, blocks, etc.

6 6 PMA data requirements for full-field digital mammography Laboratory measurements Preclinical images (phantoms) Clinical study to determine diagnostic performance for screening

7 7 Lab Performance Data Detailed engineering description Spatial resolution: Modulation Transfer Function Noise analysis: Noise Power Spectrum Sensitometry: Gray scale transfer Defect characteristics (# dead pixels, etc.) Repeated exposure tests –Image erasure, fading, charge traps, etc. Subject of international standards and consensus

8 8 Exposure at detector close to optimum for film-based ( 11 mR) Image of spiculated mass at center of breast Comparing analog mammography to digital Digital Nyquist frequency Film-based Detective Quantum Efficiency

9 9 Imaging Phantoms Used for premarket analysis as well as post-market quality assurance –Subjective evaluation is standard –More sophisticated tests under development ACR/MAP detectability phantom 6 fibers 5 speck groups 5 masses

10 10 CDMAM contrast detail phantom 4 Alternative Forced Choice Signal size and shape known Location unknown – one of four corners Quantitative phantom evaluations: predicting human performance Observer predictions from lab measurements Human performance °+

11 11 Automated reading of phantom images Quantitative data in terms of model observer SNR 2 for objects in ACR/MAP Note relative magnitude of SNR 2 (group 3 and group 2)

12 12 Phantom design considerations Involvement of professional societies Mimic relevant clinical structures –Fibers  spiculations –Specks  microcalcifications –Disks  masses Need to be made in quantities, with reliability of structures for fair comparisons Field moving toward automated phantom scoring Next challenge: phantoms for 3D systems

13 13 Why paired image interpretations failed to demonstrate substantial equivalence Side-by-side comparisons of film-based and digital images of same patients? –Differences in images because of variability in images from patient repositioning –Same would be true for film-based images of same patient –2D image of 3D object: variation in realization of overlapping tissues Agreement of paired clinical interpretations? –Approach failed because of reader variability

14 14 PMA approvals required studies of diagnostic accuracy Reader studies using Multiple-reader Multiple-case ROC analysis –See ICRU Report #79: Receiver Operating Characteristic Analysis in Medical Imaging Multiple readers to sample range of reader skill and aggressiveness (5 in first approval) Multiple cases (44 cancers, >600 cases in first approval) to sample range of case difficulty –Masses of different sizes, microcalcifications –Allowed inclusion of some diagnostic cases (case enrichment) to reduce sponsor’s burden only 2-4 cancers per 1000 in screening cohort –MRMC ROC accounts for reader variability and differences in reader threshold from use of case enrichment

15 15 10 years later Five full-field digital mammography systems approved since 1999, with many supplements for engineering updates Large NCI-funded prospective trial data released (>40,000 patients) –Demonstrated equivalence or better performance of FFDM relative to film Moving toward down-classification from Class III to Class II with Special Controls Pisano, NEJM, 2005

16 16 Expected class II paradigm Lab measurements Phantom data Clinical data –Demonstrate adequate patient positioning –Visibility of clinical structures –Evaluate artifacts Radiological Devices Panel on 11/17/09

17 17 Major components in modern digital medical imaging Image Display Computer-aided Diagnosis Image Acquisition Image Processing Picture Archiving and Communication System (PACS) Reader Accessories: separate premarket applications

18 18 Image Compression Medical image storage and communications devices (892.2010 and 892.2020) –Class I exempt –May apply irreversible compression with labeling PACS systems (892.2050) –Class II –May apply irreversible compression with labeling Mammography Quality Standards Act prohibits lossy compression for primary interpretation –Lossy compression can be applied to mammogram used for comparison (prior) –Primary read must use full data set

19 19 Summary It has taken ten years for experience with full- field digital mammography to accumulate to support reclassification Special controls for digital mammography will consist of a combination of bench measurements, phantom images, and clinical data Lack of standardization of acquisition systems, processing software, and display devices can present issues


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