Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer

被引:4
作者
Zhu, Min [1 ]
Sali, Rasoul [1 ,2 ]
Baba, Firas [1 ]
Khasawneh, Hamdi [3 ]
Ryndin, Michelle [4 ]
Leveillee, Raymond J. [5 ]
Hurwitz, Mark [6 ,7 ]
Lui, Kin [8 ]
Dixon, Christopher [9 ]
Zhang, David Y. [1 ,10 ]
机构
[1] NovinoAI, Dept Computat Pathol, 1443 NE 4th Ave, Ft Lauderdale, FL 33304 USA
[2] Stanford Univ, Dept Radiat Oncol, Sch Med, Stanford, CA 94305 USA
[3] Princess Sumaya Univ Technol, King Hussein Sch Comp Sci, Amman 11855, Jordan
[4] Cornell Univ, Coll Agr & Life Sci, Ithaca, NY 14853 USA
[5] Florida Atlantic Univ, Bethesda Hosp East, Dept Surg, Div Urol, 2800 S Seacrest Dr, Boynton Beach, FL 33435 USA
[6] New York Med Coll, Dept Radiat Med, Valhalla, NY 10595 USA
[7] Westchester Med Ctr, Valhalla, NY 10595 USA
[8] Mt Sinai Hosp, Dept Urol, New York, NY 10029 USA
[9] Good Samaritan Hosp, Westchester Med Ctr Hlth Network, Dept Urol, Suffern, NY 10901 USA
[10] New York Harbor Healthcare Syst, Pathol & Lab Serv, Dept Vet Affairs, New York, NY 10010 USA
来源
AMERICAN JOURNAL OF CLINICAL AND EXPERIMENTAL UROLOGY | 2024年 / 12卷 / 04期
关键词
Artificial intelligence; machine learning; prostate cancer; pathology; diagnosis; grading; prognosis; prediction; treatment; ISUP CONSENSUS CONFERENCE; RADICAL PROSTATECTOMY; INTERNATIONAL SOCIETY; NEEDLE BIOPSIES; CARCINOMA; GRADE; SCORE;
D O I
10.62347/JSAE9732
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Histopathology, which is the gold-standard for prostate cancer diagnosis, faces significant challenges. With prostate cancer ranking among the most common cancers in the United States and worldwide, pathologists experience an increased number for prostate biopsies. At the same time, precise pathological assessment and classification are necessary for risk stratification and treatment decisions in prostate cancer care, adding to the challenge to pathologists. Recent advancement in digital pathology makes artificial intelligence and learning tools adopted in histopathology feasible. In this review, we introduce the concept of AI and its various techniques in the field of histopathology. We summarize the clinical applications of AI pathology for prostate cancer, including pathological diagnosis, grading, prognosis evaluation, and treatment options. We also discuss how AI applications can be integrated into the routine pathology workflow. With these rapid advancements, it is evident that AI applications in prostate cancer go beyond the initial goal of being tools for diagnosis and grading. Instead, pathologists can provide additional information to improve long-term patient outcomes by assessing detailed histopathologic features at pixel level using digital pathology and AI. Our review not only provides a comprehensive summary of the existing research but also offers insights for future advancements.
引用
收藏
页码:200 / 215
页数:16
相关论文
共 78 条
[1]   HETEROGENEITY OF PROSTATE-CANCER IN RADICAL PROSTATECTOMY SPECIMENS [J].
AIHARA, M ;
WHEELER, TM ;
OHORI, M ;
SCARDINO, PT .
UROLOGY, 1994, 43 (01) :60-66
[2]   Review of deep learning: concepts, CNN architectures, challenges, applications, future directions [J].
Alzubaidi, Laith ;
Zhang, Jinglan ;
Humaidi, Amjad J. ;
Al-Dujaili, Ayad ;
Duan, Ye ;
Al-Shamma, Omran ;
Santamaria, J. ;
Fadhel, Mohammed A. ;
Al-Amidie, Muthana ;
Farhan, Laith .
JOURNAL OF BIG DATA, 2021, 8 (01)
[3]   Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice [J].
Atallah, Nehal M. ;
Toss, Michael S. ;
Verrill, Clare ;
Salto-Tellez, Manuel ;
Snead, David ;
Rakha, Emad A. .
MODERN PATHOLOGY, 2022, 35 (07) :903-910
[4]   Artificial intelligence applications in prostate cancer [J].
Baydoun, Atallah ;
Jia, Angela Y. Y. ;
Zaorsky, Nicholas G. G. ;
Kashani, Rojano ;
Rao, Santosh ;
Shoag, Jonathan E. E. ;
Vince, Randy A. A. ;
Bittencourt, Leonardo Kayat ;
Zuhour, Raed ;
Price, Alex T. T. ;
Arsenault, Theodore H. H. ;
Spratt, Daniel E. E. .
PROSTATE CANCER AND PROSTATIC DISEASES, 2024, 27 (01) :37-45
[5]   2022 Update on Prostate Cancer Epidemiology and Risk Factors-A Systematic Review [J].
Bergengren, Oskar ;
Pekala, Kelly R. ;
Matsoukas, Konstantina ;
Fainberg, Jonathan ;
Mungovan, Sean F. ;
Bratt, Ola ;
Bray, Freddie ;
Brawley, Otis ;
Luckenbaugh, Amy N. ;
Mucci, Lorelei ;
Morgan, Todd M. ;
Carlsson, Sigrid, V .
EUROPEAN UROLOGY, 2023, 84 (02) :191-206
[6]   Optimization of Initial Prostate Biopsy in Clinical Practice: Sampling, Labeling and Specimen Processing [J].
Bjurlin, Marc A. ;
Carter, H. Ballentine ;
Schellhammer, Paul ;
Cookson, Michael S. ;
Gomella, Leonard G. ;
Troyer, Dean ;
Wheeler, Thomas M. ;
Schlossberg, Steven ;
Penson, David F. ;
Taneja, Samir S. .
JOURNAL OF UROLOGY, 2013, 189 (06) :2039-2046
[7]   Harnessing multimodal data integration to advance precision oncology [J].
Boehm, Kevin M. ;
Khosravi, Pegah ;
Vanguri, Rami ;
Gao, Jianjiong ;
Shah, Sohrab P. .
NATURE REVIEWS CANCER, 2022, 22 (02) :114-126
[8]   GLEASON GRADING OF PROSTATIC NEEDLE BIOPSIES - CORRELATION WITH GRADE IN 316 MATCHED PROSTATECTOMIES [J].
BOSTWICK, DG .
AMERICAN JOURNAL OF SURGICAL PATHOLOGY, 1994, 18 (08) :796-803
[9]   The CAPRA Score at 10 Years: Contemporary Perspectives and Analysis of Supporting Studies [J].
Brajtbord, Jonathan S. ;
Leapman, Michael S. ;
Cooperberg, Matthew R. .
EUROPEAN UROLOGY, 2017, 71 (05) :705-709
[10]   Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge [J].
Bulten, Wouter ;
Kartasalo, Kimmo ;
Chen, Po-Hsuan Cameron ;
Strom, Peter ;
Pinckaers, Hans ;
Nagpal, Kunal ;
Cai, Yuannan ;
Steiner, David F. ;
van Boven, Hester ;
Vink, Robert ;
Hulsbergen-van de Kaa, Christina ;
van der Laak, Jeroen ;
Amin, Mahul B. ;
Evans, Andrew J. ;
van der Kwast, Theodorus ;
Allan, Robert ;
Humphrey, Peter A. ;
Gronberg, Henrik ;
Samaratunga, Hemamali ;
Delahunt, Brett ;
Tsuzuki, Toyonori ;
Hakkinen, Tomi ;
Egevad, Lars ;
Demkin, Maggie ;
Dane, Sohier ;
Tan, Fraser ;
Valkonen, Masi ;
Corrado, Greg S. ;
Peng, Lily ;
Mermel, Craig H. ;
Ruusuvuori, Pekka ;
Litjens, Geert ;
Eklund, Martin .
NATURE MEDICINE, 2022, 28 (01) :154-+