AI: Can It Make a Difference to the Predictive Value of Ultrasound Breast Biopsy?

(1) Background: This study aims to compare the ground truth (pathology results) against the BI-RADS classification of images acquired while performing breast ultrasound diagnostic examinations that led to a biopsy and against the result of processing the same images through the AI algorithm KOIOS DS...

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Bibliographic Details
Published in:	Diagnostics (Basel) Vol. 13; no. 4; p. 811
Main Authors:	Browne, Jean L, Pascual, Maria Ángela, Perez, Jorge, Salazar, Sulimar, Valero, Beatriz, Rodriguez, Ignacio, Cassina, Darío, Alcázar, Juan Luis, Guerriero, Stefano, Graupera, Betlem
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01-02-2023 MDPI
Subjects:	Artificial intelligence Biopsy Breast breast biopsy Breast cancer breast ultrasound Cellular biology Classification computer-aided diagnosis Diagnosis, Ultrasonic Health aspects Hyperplasia Mammography Pathology Software Technology application Ultrasonic imaging Spain United States > US breast cancer breast ultrasound computer-aided diagnosis artificial intelligence breast biopsy
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Summary:	(1) Background: This study aims to compare the ground truth (pathology results) against the BI-RADS classification of images acquired while performing breast ultrasound diagnostic examinations that led to a biopsy and against the result of processing the same images through the AI algorithm KOIOS DS (KOIOS). (2) Methods: All results of biopsies performed with ultrasound guidance during 2019 were recovered from the pathology department. Readers selected the image which better represented the BI-RADS classification, confirmed correlation to the biopsied image, and submitted it to the KOIOS AI software. The results of the BI-RADS classification of the diagnostic study performed at our institution were set against the KOIOS classification and both were compared to the pathology reports. (3) Results: 403 cases were included in this study. Pathology rendered 197 malignant and 206 benign reports. Four biopsies on BI-RADS 0 and two images are included. Of fifty BI-RADS 3 cases biopsied, only seven rendered cancers. All but one had a positive or suspicious cytology; all were classified as suspicious by KOIOS. Using KOIOS, 17 B3 biopsies could have been avoided. Of 347 BI-RADS 4, 5, and 6 cases, 190 were malignant (54.7%). Because only KOIOS suspicious and probably malignant categories should be biopsied, 312 biopsies would have resulted in 187 malignant lesions (60%), but 10 cancers would have been missed. (4) Conclusions: KOIOS had a higher ratio of positive biopsies in this selected case study vis-à-vis the BI-RADS 4, 5 and 6 categories. A large number of biopsies in the BI-RADS 3 category could have been avoided.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2075-4418 2075-4418
DOI:	10.3390/diagnostics13040811