Interobserver reproducibility of Gleason grading of prostatic carcinoma: general pathologist. FIGURE 19-10a. Link, Google Scholar 13. Multiple testing was accounted for by using Bonferroni correction. Despite its good results, our CAD system had some limitations. Transition zones (TZs) were biopsied only if they contained lesions suspicious for malignancy on multiparametric MR images. Prostate-cancer mortality at 11 years of follow-up. We have also used it for patients with limited intermediate-risk features who are adamant about undergoing a seed implant. for Gleason grading and could potentially contribute to prostate cancer diagnosis. • A number of models have been advanced for prediction of outcome after definitive treatment.58,59 The National Comprehensive Cancer Network (NCCN) has adopted a similar model to that delineated in Table 19-1 to allow basic stratification of patients without metastases into risk groups. Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning. • A capsule encases the prostate except at the apex of the gland, where the prostate blends into the urogenital diaphragm. Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. A total of 129 patients met the inclusion criteria (Fig 1). In this test population, CAD and Likert scores were assessed by using three levels of analysis. Targeted lesions were not prospectively outlined at the time of biopsy, but were typically marked by an arrow stored on the images of our picture archiving and communication system. At least two targeted biopsies were obtained from each MR lesion by using cognitive guidance. • Soft tissue metastases, such as to the liver, lung, or brain, can rarely occur late in the disease course. U-Net: convolutional networks for biomedical image segmentation. Interestingly, despite this difference, the CAD performed well in the test population. 19-6).99,104 In this trial, the dose was prescribed to the isocenter. • The Gleason scoring system is the most frequently used grading system. The CAD yielded higher AUCs than did the Likert score at all three levels of analysis in the overall population and all subgroups (Tables 3–5), except in the transition zone (Table E2 [online]). • The seminal vesicles are located superior and posterior to the base of the prostate. Automated gleason grading of prostate biopsies using deep learning. Although the PI-RADS version 2 score has shown good results in characterizing prostate lesions (25), early evaluations have also pointed out some limitations (26). CAD = computer-aided diagnosis. Note.—Data in parentheses are 95% confidence intervals. 5, No. • Many patients with prostate cancer present with urinary obstructive symptoms. Only patients imaged after January 31, 2014, were taken into consideration to ensure that no patient of the training population was included in the test population. FIGURE 19-1. When several MR lesions were present in the lobe or patient, the highest Likert and CAD scores in the lobe or patient were taken into account. published online Feb 26. These tight margins can be used because the patients undergo daily pretreatment imaging using the onboard kilovoltage CT imaging on the Varian Trilogy linear accelerator (Varian Medical Systems, Palo Alto, CA) to correct for interfractional motion.96, • Patients are also treated after daily placement of a rectal balloon (Radiadyne, Houston, TX). Interobserver reproducibility of Gleason grading of prostatic carcinoma: urologic pathologists. Biopsies were performed under guidance of transrectal ultrasonography (US) (Aixplorer; SuperSonic Imagine, Aix-en-Provence, France). A CAD combining the 10th percentile of the apparent diffusion coefficient and the time to peak of enhancement was trained to detect cancers in the PZ with a Gleason score of at least 7 in 106 patients from database 1. The presacral lymph nodes are also at risk.15,16.