دورية أكاديمية
Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for Unprocessed Prostate Biopsies.
| العنوان: | Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for Unprocessed Prostate Biopsies. |
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| المؤلفون: | Mannas MP; Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada.; Vancouver Prostate Centre, Vancouver, British Columbia, Canada.; Department of Urology, NYU Langone Health, New York, New York., Deng FM; Department of Pathology, NYU Langone Health, New York, New York., Ion-Margineanu A; Invenio Imaging, Santa Clara, California., Jones D; Department of Pathology, NYU Langone Health, New York, New York., Hoskoppal D; Department of Pathology, NYU Langone Health, New York, New York., Melamed J; Department of Pathology, NYU Langone Health, New York, New York., Pastore S; Invenio Imaging, Santa Clara, California., Freudiger C; Invenio Imaging, Santa Clara, California., Orringer DA; Department of Neurosurgery, NYU Langone Health, New York, New York., Taneja SS; Department of Urology, NYU Langone Health, New York, New York.; Department of Radiology, NYU Langone Health, New York, New York.; Department of Biomedical Engineering, NYU Langone Health, New York, New York. |
| المصدر: | The Journal of urology [J Urol] 2024 Mar; Vol. 211 (3), pp. 384-391. Date of Electronic Publication: 2023 Dec 15. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Wolters Kluwer Country of Publication: United States NLM ID: 0376374 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1527-3792 (Electronic) Linking ISSN: 00225347 NLM ISO Abbreviation: J Urol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2019- : [Philadelphia, PA] : Wolters Kluwer Original Publication: Baltimore : Lippincott Williams & Wilkins |
| مواضيع طبية MeSH: | Artificial Intelligence* , Prostatic Neoplasms*/diagnosis , Prostatic Neoplasms*/pathology, Humans ; Male ; Prostate/pathology ; Feedback ; Biopsy |
| مستخلص: | Purpose: Stimulated Raman histology is an innovative technology that generates real-time, high-resolution microscopic images of unprocessed tissue, significantly reducing prostate biopsy interpretation time. This study aims to evaluate the ability for an artificial intelligence convolutional neural network to interpretate prostate biopsy histologic images created with stimulated Raman histology. Materials and Methods: Unprocessed, unlabeled prostate biopsies were prospectively imaged using a stimulated Raman histology microscope. Following stimulated Raman histology creation, the cores underwent standard pathological processing and interpretation by at least 2 genitourinary pathologists to establish a ground truth assessment. A network, trained on 303 prostate biopsies from 100 participants, was used to measure the accuracy, sensitivity, and specificity of detecting prostate cancer on stimulated Raman histology relative to conventional pathology. The performance of the artificial intelligence was evaluated on an independent 113-biopsy test set. Results: Prostate biopsy images obtained through stimulated Raman histology can be generated within a time frame of 2 to 2.75 minutes. The artificial intelligence system achieved a rapid classification of prostate biopsies with cancer, with a potential identification time of approximately 1 minute. The artificial intelligence demonstrated an impressive accuracy of 96.5% in detecting prostate cancer. Moreover, the artificial intelligence exhibited a sensitivity of 96.3% and a specificity of 96.6%. Conclusions: Stimulated Raman histology generates microscopic images capable of accurately identifying prostate cancer in real time, without the need for sectioning or tissue processing. These images can be interpreted by artificial intelligence, providing physicians with near-real-time pathological feedback during the diagnosis or treatment of prostate cancer. |
| التعليقات: | Comment in: J Urol. 2024 Mar;211(3):390-391. (PMID: 38100832) Comment in: J Urol. 2024 Mar;211(3):391. (PMID: 38329054) |
| فهرسة مساهمة: | Keywords: Raman spectroscopy; artificial intelligence; prostate cancer |
| تواريخ الأحداث: | Date Created: 20231215 Date Completed: 20240209 Latest Revision: 20240209 |
| رمز التحديث: | 20240209 |
| DOI: | 10.1097/JU.0000000000003811 |
| PMID: | 38100831 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1527-3792 |
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| DOI: | 10.1097/JU.0000000000003811 |