Retrospectively assessing evaluation and management of artificial-intelligence detected nodules on uninterpreted chest radiographs in the era of radiologists shortage.

PURPOSE: High volumes of chest radiographs (CXR) remain uninterpreted due to severe shortage of radiologists. These CXRs may be informally reported by non-radiologist physicians, or not reviewed at all. Artificial intelligence (AI) software can aid lung nodule detection. Our aim was to assess evaluation and management by non-radiologists of uninterpreted CXRs with AI detected nodules, compared to retrospective radiology reports. MATERIALS AND METHODS: AI detected nodules on uninterpreted CXRs of adults, performed 30/6/2022-31/1/2023, were evaluated. Excluded were patients with known active malignancy and duplicate CXRs of the same patient. The electronic medical records (EMR) were reviewed, and the clinicians' notes on the CXR and AI detected nodule were documented. Dedicated thoracic radiologists retrospectively interpreted all CXRs, and similarly to the clinicians, they had access to the AI findings, prior imaging and EMR. The radiologists' interpretation served as the ground truth, and determined if the AI-detected nodule was a true lung nodule and if further workup was required. RESULTS: A total of 683 patients met the inclusion criteria. The clinicians commented on 386 (56.5%) CXRs, identified true nodules on 113 CXRs (16.5%), incorrectly mentioned 31 (4.5%) false nodules as real nodules, and did not mention the AI detected nodule on 242 (35%) CXRs, of which 68 (10%) patients were retrospectively referred for further workup by the radiologist. For 297 patients (43.5%) there were no comments regarding the CXR in the EMR. Of these, 77 nodules (11.3%) were retrospectively referred for further workup by the radiologist. CONCLUSION: AI software for lung nodule detection may be insufficient without a formal radiology report, and may lead to over diagnosis or misdiagnosis of nodules.

Pelvic Peritonectomy Poorly Affects Outcomes in Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy for Colorectal Metastases.

BACKGROUND: Constraints of pelvic anatomy render complete cytoreduction (CRS) challenging. The aim of this study is to investigate the impact of pelvic peritonectomy during CRS/HIPEC on colorectal peritoneal metastasis (CRPM) patients' outcomes. METHODS: This is a retrospective analysis of a prospectively maintained CRS/hyperthermic intraperitoneal chemotherapy (HIPEC) database. The analysis included 217 patients with CRPM who had a CRS/HIPEC between 2014 and 2021. We compared perioperative and oncological outcomes of patients with pelvic peritonectomy (PP) (n = 63) to no pelvic peritonectomy (non-PP) (n = 154). RESULTS: No differences in demographics were identified. The peritoneal cancer index (PCI) was higher in the PP group with a median PCI of 12 vs. 6 in the non-PP group (p < 0.001). Operative time was 4.9 vs. 4.3 h in the PP and non-PP groups, respectively (p = 0.63). Median hospitalization was longer in the PP group at 12 vs. 10 days (p = 0.007), and the rate of complications were higher in the PP group at 57.1% vs. 39.6% (p = 0.018). Pelvic peritonectomy was associated with worse disease-free (DFS) and overall survival (OS) with 3-year DFS and OS of 7.3 and 46.3% in the PP group vs. 28.2 and 87.8% in the non-PP group (p = 0.028, p .> 0.001). The univariate OS analysis identified higher PCI (p = 0.05), longer surgery duration (p = 0.02), and pelvic peritonectomy (p < 0.001) with worse OS. Pelvic peritonectomy remained an independent prognostic variable, irrespective of PCI, on the multivariate analysis (p < 0.001). CONCLUSIONS: Pelvic peritonectomy at the time of CRS/HIPEC is associated with higher morbidity and worse oncological outcomes. These findings should be taken into consideration in the management of patients with pelvic involvement.