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Seeking Ways to Improve Interpretation of Mammograms

2015· article· en· W3037059984 on OpenAlexaboutno aff
Peggy Eastman

Bibliographic record

VenueOncology Times · 2015
Typearticle
Languageen
FieldComputer Science
TopicAI in cancer detection
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)EpistemologyPsychologyComputer sciencePhilosophyProgramming language

Abstract

fetched live from OpenAlex

FigureWASHINGTON—In an effort to improve the interpretation of screening mammograms, the Institute of Medicine's National Cancer Policy Forum and the American Cancer Society hosted a comprehensive one and a half day workshop here. Speakers agreed that while the technical quality of mammography has improved since the national Mammography Quality Standards Act (MQSA) of 1992, the interpretation of mammograms remains variable, which limits the detection of early breast cancer. “Improving interpretive performance would have a large public health impact,” said Diana Buist, PhD, MPH, chair of the workshop planning committee and Senior Scientific Investigator at the Group Health Research Institute within the Group Health Cooperative in Washington State. A summary report of the workshop is expected to be published by the IOM in a few months. The committee's findings could be relevant to radiology more broadly and not just to mammography, said Patricia A. Ganz, MD, a member of the workshop planning committee, Vice Chair of the National Cancer Policy Forum, Distinguished Professor of Health Policy & Management and Medicine at the UCLA Fielding School of Public Health and David Geffen School of Medicine, and Director of Cancer Prevention and Control Research at UCLA's Jonsson Comprehensive Cancer Center. “We have to create a culture where evaluation of your performance is a matter of routine,” said another speaker, Robert A. Smith, PhD, Senior Director for Cancer Control for the ACS. “Now that women can depend on a high-quality image for mammography, they need to be able to depend on a high-quality interpretation,” he said in an interview. “We've been at this for a long time, but at this point in time we don't have a clear strategy for the average radiologist to know how well he is doing or how he can improve.” What is particularly needed is a way for radiologists to know how skilled they are at finding small breast cancers. Smith said that in some ways the workshop findings will update a 2005 IOM report, “Improving Breast Imaging Quality Standards” (he served on the committee that produced that report). Asked if he is concerned about underperforming mammography interpreters, he answered that yes, “there is a sizeable proportion of radiologists who aren't as good at this as they could be. We know there are low performers.”FigureWhile noting that “all screening tests have error rates,” he said the percentage of low performers interpreting mammograms is likely 20 percent or higher depending on the cut-points used. U.S. expenditures for false-positive mammograms and breast cancer over-diagnoses are estimated at $4 billion a year, according to a recent study in Health Affairs coauthored by Kenneth D. Mandl, MD, MPH, Professor at Harvard Medical School and holder of the Boston Children's Hospital Chair in Biomedical Informatics and Population Health (OT 5/10/15 issue), which concluded that most cases of ductal carcinoma in situ are probably over-diagnosed.DIANA BUIST, PHD, MPH. Workshop Planning Committee Chair DIANA BUIST, PHD, MPHSmith, however, said that although he considers that there are major methodological flaws in the study, the challenge undergirding the IOM/ACS workshop is right on target: how to ensure that women having mammograms can be certain that they are accurate. MQSA Reauthorization of the MQSA expired in 2007, noted Helen J. Barr, MD, Director of the Division of Mammography Quality Standards at the Food and Drug Administration. (Congress gave FDA authority to regulate the provisions of MQSA.) She said that Congressional reauthorization of the act presents an opportunity to add new requirements to the MQSA in order to improve mammography quality. Still, in practical terms, the lack of reauthorization doesn't affect day-to-day operation, she said. The act requires that each mammography facility be accredited and certified. Barr noted that by law each mammography facility must have a yearly inspection, much of which are conducted by FDA-trained state contractors. And while the FDA requires that each facility have a system to record medical outcomes audit data and checks that the audit has been done, the MQSA doesn't specify all the metrics that must be on it. “We need standardized metrics; we need some specifics for audits,” Barr said. One of the recommendations of the 2005 IOM report on mammography quality to improve image interpretation was to revise and standardize the required medical audit component of the MQSA. Some of the recommendations of the 2005 IOM report on mammography quality have been implemented by professional societies, not by the government, noted Etta D. Pisano, MD, a member of the workshop planning committee and Dean Emerita and Distinguished University Professor at Medical University of South Carolina. She said that while the recommendation for a voluntary advanced medical audit with feedback has not been carried out, the recommendation to designate specialized Breast Imaging Centers of Excellence has been implemented by the American College of Radiology (ACR), and currently there are about 1,225 such centers. “Most radiologists want to do a good job and will take CME to improve,” she said. The 2005 IOM report recommended further study of the effects of CME, along with reader volume and double reading, on improving mammography interpretation. Pisano, who served on the committee that wrote that report, hailed the replacement of film mammograms with digital mammograms since 2005: “If anything, it becomes easier to read mammograms... the quality of the images is more standardized.” (Barr told OT that just four percent of U.S. mammography facilities operating today are film-only, and that all military mammography facilities are totally digital.)ROBERT A SMITH, PHD. ROBERT A SMITH, PHD: “Now that women can depend on a high-quality image for mammography, they need to be able to depend on a high-quality interpretation.”Variability Variability in interpretation of mammograms has been an ongoing problem, but realistically it cannot be solved by double reading, emphasized Barbara Monsees, MD, a member of the IOM/ACS workshop planning committee; the Ronald and Hanna Evens Professor of Women's Health at Washington University Medical Center; founder of the Breast Imaging Section at Mallinckrodt Institute of Radiology; a member of the Board of Chancellors of the American College of Radiology; and Chair of the ACR's Breast Imaging Commission. “Double reading is really not feasible,” she said, because there simply isn't the workforce to carry it out. What has occurred to improve the quality of mammogram interpretation is that “there are now more specialists who are dedicated breast imaging radiologists,” she said. In addition, the digitization of mammography has made the centralized interpretation of screening mammograms feasible; screening exams can be more easily transferred; and there are fewer lost exams. Nonetheless, the issue of correctly interpreting mammograms, especially for women with dense breasts remains. ‘Big Conundrum’ Monsees praised the availability of additional procedures such as ultrasound and MRI to help clarify findings on mammograms that raise questions, noting that supplemental screening can detect occult cancers. But, she said, the question of who should receive this supplemental screening “is a big conundrum these days.” Unfortunately, computer aided detection “has not turned out to be what we had hoped it would,” she said, pointing to, though, the value and promise of digital breast tomosynthesis (DBT, or 3D mammography), which she said helps across screening parameters (different densities). Diffusion and uptake of new breast screening technologies are uneven, however, and they may not be available to women everywhere, said Tracy Onega, PhD, Associate Professor in the Section of Biostatistics & Epidemiology at Dartmouth Medical School. Threshold Volume Speakers at the workshop generally agreed that mammography interpretation is better if the reader meets a threshold volume for the number of mammograms read yearly. Isabelle Theberge, PhD, Scientific Coordinator of the Evaluation Team of the Quebec Breast Cancer Screening Program, said that Canadian provinces have specific minimum volume requirements for mammogram interpreters. She said the data show that radiologists who read fewer than 500 mammograms a year have much higher false-positive rates than those with greater volumes.ETTA D. PISANO, MD. ETTA D. PISANO, MD, was enthusiastic about near-universal move to digital mammograms since 2005: “If anything, it becomes easier to read mammograms... the quality of the images is more standardized.”“The more you do, the more you see,” said Matthew Wallis, MB, ChB, Director of the Cambridge and Huntington Breast Screening Service in the U.K. Buist agree: “Experience actually does matter.” Breast Imaging Fellowships & Mentors Several speakers also stressed the importance of breast imaging fellowships during a radiologist's training, and of mentors who can help train breast imaging specialists. “It really does take two to three months to feel confident to work as part of a team,” Wallis said. And, it takes about nine months for a mammography interpreter to feel comfortable working on his/her own. I don't think we should underestimate how much time it takes... the training is really important.” Screening simulations can help radiologists improve their performance, said Patricia A. Carney, PhD, a member of the workshop planning committee; Professor of Family Medicine and of Public Health and Preventive Medicine at Oregon Health & Science University; and a member of the IOM committee that wrote the 2005 report on mammography quality. She said that to improve the quality of mammogram interpretation, there is a need for “master adaptive learners,” not just radiologists who are lifelong learners. Innovative CME can help in that area. Centralized Repository Speakers also mentioned the value of a centralized repository for mammograms done in MQSA-certified centers—cloud storage for mammograms and other breast images. This centralized repository would allow access to prior images so that a mammogram reader could better interpret a current image through comparison to previous ones, thus potentially avoiding false positives, Barr said.BARBARA MONSEES, MD. BARBARA MONSEES, MD: “Double reading is really not feasible, because there simply isn't the workforce to carry it out.”In that regard, Kathryn Pearson Peyton, MD, founder and Chief Medical Officer of Mammosphere, commented at the workshop that during her years as a breast imaging radiologist she continually saw women who didn't know where their previous mammograms were or could not get them transferred to a new physician. So in late 2012, she founded Mammosphere, a nonprofit mammography cloud storage and image-sharing network (www.mammosphere.org). Peyton said that all of her family, going back three generations, has been affected by breast cancer, and that she wants to keep Mammosphere nonprofit so that physicians will be encouraged to pull mammogram records down from the cloud and compare a current mammogram to a woman's previous mammograms. While hospitals store images in the cloud, there is little connection between them. So she, like Barr, believes strongly in the need for a centralized cloud storage repository for mammograms to improve the quality of mammography interpretation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.293
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2015
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