Departments of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin.
Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin.
Lab Invest. 2023 Dec;103(12):100269. doi: 10.1016/j.labinv.2023.100269. Epub 2023 Oct 26.
Prostate cancer is the most commonly diagnosed cancer in men, accounting for 27% of the new male cancer diagnoses in 2022. If organ-confined, removal of the prostate through radical prostatectomy is considered curative; however, distant metastases may occur, resulting in a poor patient prognosis. This study sought to determine whether quantitative pathomic features of prostate cancer differ in patients who biochemically experience biological recurrence after surgery. Whole-mount prostate histology from 78 patients was analyzed for this study. In total, 614 slides were hematoxylin and eosin stained and digitized to produce whole slide images (WSI). Regions of differing Gleason patterns were digitally annotated by a genitourinary fellowship-trained pathologist, and high-resolution tiles were extracted from each annotated region of interest for further analysis. Individual glands within the prostate were identified using automated image processing algorithms, and histomorphometric features were calculated on a per-tile basis and across WSI and averaged by patients. Tiles were organized into cancer and benign tissues. Logistic regression models were fit to assess the predictive value of the calculated pathomic features across tile groups and WSI; additionally, models using clinical information were used for comparisons. Logistic regression classified each pathomic feature model at accuracies >80% with areas under the curve of 0.82, 0.76, 0.75, and 0.72 for all tiles, cancer only, noncancer only, and across WSI. This was comparable with standard clinical information, Gleason Grade Groups, and CAPRA score, which achieved similar accuracies but areas under the curve of 0.80, 0.77, and 0.70, respectively. This study demonstrates that the use of quantitative pathomic features calculated from digital histology of prostate cancer may provide clinicians with additional information beyond the traditional qualitative pathologist assessment. Further research is warranted to determine possible inclusion in treatment guidance.
前列腺癌是男性最常见的癌症,占 2022 年新诊断男性癌症的 27%。如果局限于器官,通过根治性前列腺切除术切除前列腺被认为是治愈性的;然而,可能会发生远处转移,导致患者预后不良。本研究旨在确定在手术后生化复发的患者中,前列腺癌的定量病理特征是否存在差异。对 78 例患者的全前列腺组织学进行了分析。共对 614 张载玻片进行了苏木精和伊红染色并数字化,以生成全玻片图像 (WSI)。由泌尿生殖系奖学金培训的病理学家对不同 Gleason 模式的区域进行了数字注释,并从每个注释的感兴趣区域提取了高分辨率瓦片以进行进一步分析。使用自动图像处理算法识别前列腺内的各个腺体,并在每个瓦片的基础上以及在 WSI 上计算组织形态计量学特征,并按患者平均计算。瓦片被组织成癌症和良性组织。使用逻辑回归模型评估计算的病理特征在瓦片组和 WSI 上的预测价值;此外,还使用包含临床信息的模型进行比较。逻辑回归以 >80%的准确率对每个病理特征模型进行分类,其曲线下面积分别为 0.82、0.76、0.75 和 0.72,适用于所有瓦片、仅癌症、仅非癌症和整个 WSI。这与标准临床信息、Gleason 分级组和 CAPRA 评分相当,这些评分的准确率相似,但曲线下面积分别为 0.80、0.77 和 0.70。本研究表明,使用从前列腺癌数字组织学中计算得出的定量病理特征可为临床医生提供超出传统病理学家评估的额外信息。需要进一步研究以确定是否可能纳入治疗指导。