Can a totally different approach to soft tissue computer aided detection (CADe) result in affecting radiologists' decisions?

David Gur

doi:10.1117/12.2301251

7 March 2018 Can a totally different approach to soft tissue computer aided detection (CADe) result in affecting radiologists' decisions?

David Gur

Author Affiliations +

Proceedings Volume 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment; 105771B (2018) https://doi.org/10.1117/12.2301251
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

We tested whether a case based CADe scheme, developed only on negatively interpreted screening mammograms, has predictive value for cancer detection during subsequent screening and how this approach may affect radiologists’ performances when alerting them to a small subset (~15%) of exams on which radiologists tend to miss cancers. A series of six parameters case based CADe schemes, using 200 negative mammograms (800 images 100 women with breast cancer at subsequent screening and 100 women who remained negative), carefully matched by age and breast density, were optimized. CADe alone schemes performed at AUC=0.68 (+/- 0.01). Five radiologists and 4 residents interpreted the same cases and performed at AUC =0.71 (experienced radiologists) and AUC= 0.61 (residents). With the “CADe warnings” shown to the interpreters only if they did not recall one of 24 highest CADe scoring cases, assisted performance of radiologists and residents respectively, were 0.71 and 0.63 (p>0.05). However, when the CADe alone performance was raised to an AUC=0.78, by artificially increasing the number of possible warnings from 16 to 24, radiologists’ performances significantly improved from an AUC of 0.68 to 0.72 (p<0.05). In conclusion, the use case based information other than breast density could highlight a small fraction of women whose cancers are more likely to be missed by radiologists and later detected during subsequent mammograms, thereby, leading to an assisted approach that improves radiologists’ performances. However, to be effective, the performance of the CADe alone should be substantially higher (e.g. ΔAUC ≥0.07) than that of the un-assisted radiologist.

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David Gur "Can a totally different approach to soft tissue computer aided detection (CADe) result in affecting radiologists' decisions?", Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 105771B (7 March 2018); https://doi.org/10.1117/12.2301251

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KEYWORDS

Computer aided diagnosis and therapy

Cancer

Mammography

Tissues

Breast

Computer aided design

Breast cancer

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