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Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI
(AMER ROENTGEN RAY SOC, 2020-01-01) Mehralivand, Sherif; Harmon, Stephanie A.; Shih, Joanna H.; Smith, Clayton P.; Lay, Nathan; Argun, Burak; Bednarova, Sandra; Baroni, Ronaldo Hueb; Canda, Abdullah Erdem; Ercan, Karabekir; Girometti, Rossano; Karaarslan, Ercan; Kural, Ali Riza; Pursyko, Andrei S.; Rais-Bahrami, Soroush; Tonso, Victor Martins; Magi-Galluzzi, Cristina; Gordetsky, Jennifer B.; Silvestre e Silva Macarenco, Ricardo; Merino, Maria J.; Gumuskaya, Berrak; Saglican, Yesim; Sioletic, Stefano; Warren, Anne Y.; Barrett, Tristan; Bittencourt, Leonardo; Coskun, Mehmet; Knauss, Chris; Law, Yan Mee; Malayeri, Ashkan A.; Margolis, Daniel J.; Marko, Jamie; Yakar, Derya; Wood, Bradford J.; Pinto, Peter A.; Choyke, Peter L.; Summers, Ronald M.; Turkbey, Baris
OBJECTIVE. The purpose of this study was to evaluate in a multicenter dataset the performance of an artificial intelligence (AI) detection system with attention mapping compared with multiparametric MRI (mpMRI) interpretation in the detection of prostate cancer. MATERIALS AND METHODS. MRI examinations from five institutions were included in this study and were evaluated by nine readers. In the first round, readers evaluated mpMRI studies using the Prostate Imaging Reporting and Data System version 2. After 4 weeks, images were again presented to readers along with the AI-based detection system output. Readers accepted or rejected lesions within four AI-generated attention map boxes. Additional lesions outside of boxes were excluded from detection and categorization. The performances of readers using the mpMRI-only and AI-assisted approaches were compared. RESULTS. The study population included 152 case patients and 84 control patients with 274 pathologically proven cancer lesions. The lesion-based AUC was 74.9\% for MRI and 77.5\% for AI with no significant difference (p = 0.095). The sensitivity for overall detection of cancer lesions was higher for AI than for mpMRI but did not reach statistical significance (57.4\% vs 53.6\%, p = 0.073). However, for transition zone lesions, sensitivity was higher for AI than for MRI (61.8\% vs 50.8\%, p = 0.001). Reading time was longer for AI than for MRI (4.66 vs 4.03 minutes, p < 0.001). There was moderate interreader agreement for AI and MRI with no significant difference (58.7\% vs 58.5\%, p = 0.966). CONCLUSION. Overall sensitivity was only minimally improved by use of the AI system. Significant improvement was achieved, however, in the detection of transition zone lesions with use of the AI system at the cost of a mean of 40 seconds of additional reading time.
Magnetic Resonance - Transrectal Ultrasound Fusion Guided Prostate Biopsy
(GALENOS YAYINCILIK, 2016-01-01) Argun, Omer Burak; Obek, Can; Kural, Ali Riza
Prostate has remained as the single solid organ for which biopsy cannot be performed from a lesion for decades. Lately, the groundbreaking magnetic resonance imaging (MRI) techniques have emerged to scan prostate cancer and have become an important diagnostic tool in the diagnosis of prostate cancer. Efforts to improve the accuracy of the standard biopsy methods have led to the emergence of target-oriented biopsy methods. Today, MRI-transrectal ultrasound (TRUS) fusion guided biopsy methods are being used increasingly, especially for patients with an increasing prostate specific antigen level after a previous negative biopsy result and for patients under follow-up with active surveillance protocols. Even though it is not yet suggested in guidelines, our view and practice are in line with the fact that MRI-TRUS fusion guided biopsy is the most ideal biopsy method in any patient scheduled for a prostate biopsy with a significant lesion on MRI.
Can We Accomplish Better Oncological Results with Robot-Assisted Radical Prostatectomy?
(MARY ANN LIEBERT, INC, 2017-01-01) Kural, Ali Riza; Obek, Can; Doganca, Tunkut
Surgical removal with radical prostatectomy has been a cornerstone for the treatment of prostate cancer and is associated with level 1 evidence for survival advantage compared with watchful waiting. Since the first structured robotic program was launched in 2000, robot-assisted radical prostatectomy (RARP) has had a rapid diffusion and surpassed its open radical prostatectomy (ORP) and laparoscopic radical prostatectomy (LRP) counterparts in the United States and is progressively expanding in other countries. Interestingly, this common acceptance of RARP was initially driven in the paucity of robust clinical evidence. There is still lack of level 1 evidence with prospective randomized trials on the oncologic outcomes of RARP. In that scenario, the clinician has to rely on retrospective data and systemic and meta-analyses. In comparison with ORP and LRP, RARP has proven to reach at least equivalent oncological outcomes. Lower rate of positive surgical margins may probably be achieved with RARP in pT2 patients. Although urologists were initially reluctant to embrace RARP in highrisk patients and lymph node yield was low, contemporary series have revealed that RARP and extended lymphadenectomy may be safely performed with obtaining similar (or better) nodal yields compared with ORP. Surgeon experience is universally of utmost importance in obtaining good outcomes. We will need to wait for long-term results of contemporary series to comprehend the impact of RARP on cancer-specific survival and overall survival. Using novel imaging before surgery and frozen section analysis during surgery may allow for superior oncological outcomes.

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