Digital Mammography and Clinical Applications (Live Simulcast)

Oct 17th, 2015Dec 31st, 1969
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Learn how to recognize digital mammography artifacts and what causes them. Brush up on your pathology recognition skills and round out the day learning about clinical applications from positioning to mechanical to software issues.
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Images of a 39-year-old who underwent screening mammography. Right craniocaudal (left) and mediolateral oblique (middle) views from preoperative mammography show suspicious grouped fine pleomorphic calcifications (arrows). After biopsy showed ductal carcinoma of situ (DCIS), patient underwent breast-conserving surgery, yielding final diagnosis of ductal carcinoma in situ (intermediate grade, hormone receptor positive). (Right) Screenshot of an output of a commercial AI tool applied to preoperative mammography. AI detected right breast lesion with score of 95% on both views (concentric colored circles). Present study’s reviewing radiologist deemed AI marking to correspond with site of DCIS.
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Axial contrast-enhanced CT scan in a 28-year-old premenopausal woman shows an incidentally detected solid-appearing left ovarian lesion (solid arrow) anterior to the uterus (U), associated with trace ascites in the right adnexa and cul de sac (dashed arrows). At pathologic analysis, this was shown to be ovarian dysgerminoma. Two readers misdiagnosed this lesion, one as a leiomyoma and one as an ovarian fibroma.
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An AI model showed associations with recurrence after DCIS surgery and performed comparably to established clinical risk models.
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Images of a 39-year-old who underwent screening mammography. Right craniocaudal (left) and mediolateral oblique (middle) views from preoperative mammography show suspicious grouped fine pleomorphic calcifications (arrows). After biopsy showed ductal carcinoma of situ (DCIS), patient underwent breast-conserving surgery, yielding final diagnosis of ductal carcinoma in situ (intermediate grade, hormone receptor positive). (Right) Screenshot of an output of a commercial AI tool applied to preoperative mammography. AI detected right breast lesion with score of 95% on both views (concentric colored circles). Present study’s reviewing radiologist deemed AI marking to correspond with site of DCIS.
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Axial contrast-enhanced CT scan in a 28-year-old premenopausal woman shows an incidentally detected solid-appearing left ovarian lesion (solid arrow) anterior to the uterus (U), associated with trace ascites in the right adnexa and cul de sac (dashed arrows). At pathologic analysis, this was shown to be ovarian dysgerminoma. Two readers misdiagnosed this lesion, one as a leiomyoma and one as an ovarian fibroma.
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Images from two representative cases. (A-C) Images in an 82-year-old man with a calcified plaque in the proximal segment of the left anterior descending artery. (A, B) Curved planar reconstruction images from CCTA with (A) hybrid iterative reconstruction (HIR) and (B) super-resolution deep learning reconstruction (SR-DLR) show that the measured PDS was 66% for the HIR image and 42% for the SR-DLR image. (C) Quantitative analysis of the invasive coronary angiography (ICA) image (reference standard) revealed a PDS of 34% (arrow). (D-F) Images in a 37-year-old woman with a noncalcified plaque in the middle segment of the left circumflex artery. (D, E) Curved planar reconstruction images from CCTA with (D) HIR and (E) SR-DLR show that the measured PDS was 47% for the HIR image and 80% for the SR-DLR image. (F) Quantitative analysis of the ICA image revealed a PDS of 72% (arrow). Blue, red, and yellow lines in A, B, D, and E represent the proximal reference point, stenosed lesion, and distal reference point, respectively, and the insets show the corresponding cross-sectional images.
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