Impact of an enhanced recovery after surgery protocol on short-term outcomes in elderly patients undergoing pancreaticoduodenectomy

BackgroundTo determine whether the short-term benefits associated with an enhanced recovery after surgery programme (ERAS) following pancreaticoduodenectomy (PD) vary with age.Methods830 consecutive patients who underwent PD between January 2009 and March 2019 were divided according to age: elderly (≥75 years) vs. non-elderly patients (<75 years). Within each age group, cohort characteristics and outcomes were compared between patients treated pre- and post-ERAS (ERAS was systematically introduced in December 2012). Univariable and multivariable analysis were then performed, to assess whether ERAS was independently associated with length of hospital stay (LOS).ResultsOf the entire cohort, 577 of 830 patients (69.5%) were managed according to an ERAS protocol, and 170 patients (20.5%) were aged ≥75 years old. Patients treated post-ERAS were significantly more comorbid than those pre-ERAS, with a mean Charlson Comorbidity Index of 4.6 vs. 4.1 (p < 0.001) and 6.0 vs. 5.7 (p = 0.039) for the non-elderly and elderly subgroups, respectively. There were significantly fewer medical complications in non-elderly patients treated post-ERAS compared to pre-ERAS (12.4% vs. 22.4%; p = 0.002), but not in elderly patients (23.6% vs. 14.0%; p = 0.203). On multivariable analysis, ERAS was independently associated with reduced LOS in both elderly (14.8% reduction, 95% CI: 0.7–27.0%, p = 0.041) and non-elderly patients (15.6% reduction, 95% CI: 9.2–21.6%, p < 0.001), with the effect size being similar in each group.ConclusionERAS protocols can be safely applied to patients undergoing pancreaticoduodenectomy irrespective of age. Implementation of an ERAS protocol was associated with a significant reduction in postoperative LOS in both elderly and non-elderly patients, despite higher comorbidity in the post-ERAS period.     

Prognostic validity of the American joint committee on cancer eighth edition staging system for well-differentiated pancreatic neuroendocrine tumors

BackgroundThe American Joint Committee on Cancer (AJCC) made improvements for staging pancreatic neuroendocrine tumors (pNETs) in its 8th Edition; however, multicenter studies were not included.MethodsWe collected multicenter datasets (n = 1,086, between 2004 and 2018) to validate the value of AJCC 8 and other coexisting staging systems through univariate and multivariate analysis for well-differentiated (G1/G2) pNETs.ResultsCompared to other coexisting staging systems, AJCC 7 only included 12 (1.1%) patients with stage III tumors. Patients with European Neuroendocrine Tumor Society (ENETS) stage IIB disease had a higher risk of death than patients with stage IIIA (hazard ratio [HR]: 4.376 vs. 4.322). For the modified ENETS staging system, patients with stage IIB disease had a higher risk of death than patients with stage III (HR: 6.078 vs. 5.341). According to AJCC 8, the proportions of patients with stage I, II, III, and IV were 25.7%, 40.3%, 23.6%, and 10.4%, respectively. As the stage advanced, the median survival time decreased (NA, 144.7, 100.8, 72.0 months, respectively), and the risk of death increased (HR: II = 3.145, III = 5.925, and IV = 8.762).ConclusionThese findings suggest that AJCC 8 had a more reasonable proportional distribution and the risk of death was better correlated with disease stage.     

Anomaly segmentation in retinal images with poisson-blending data augmentation

Diabetic retinopathy (DR) is one of the most important complications of diabetes. Accurate segmentation of DR lesions is of great importance for the early diagnosis of DR. However, simultaneous segmentation of multi-type DR lesions is technically challenging because of 1) the lack of pixel-level annotations and 2) the large diversity between different types of DR lesions. In this study, first, we propose a novel Poisson-blending data augmentation (PBDA) algorithm to generate synthetic images, which can be easily utilized to expand the existing training data for lesion segmentation. We perform extensive experiments to recognize the important attributes in the PBDA algorithm. We show that position constraints are of great importance and that the synthesis density of one type of lesion has a joint influence on the segmentation of other types of lesions. Second, we propose a convolutional neural network architecture, named DSR-U-Net++ (i.e., DC-SC residual U-Net++), for the simultaneous segmentation of multi-type DR lesions. Ablation studies showed that the mean area under precision recall curve (AUPR) for all four types of lesions increased by >5% with PBDA. The proposed DSR-U-Net++ with PBDA outperformed the state-of-the-art methods by 1.7%-9.9% on the Indian Diabetic Retinopathy Image Dataset (IDRiD) and 67.3% on the e-ophtha dataset with respect to mean AUPR. The developed method would be an efficient tool to generate large-scale task-specific training data for other medical anomaly segmentation tasks.     

Useful histopathologic features for diagnosing focal liver lesions with spindle cell morphology: A clinicopathologic study

BackgroundFocal liver lesions with spindle cell morphology are rare in the daily practice of pathology. The differential diagnosis is broad, including both tumors and tumor-like lesions. Initial radiologic assessment is sometimes inaccurate. Histopathology is needed to arrive at the correct diagnosis. This study analyzed discrepancies between histopathology and radiologic findings of focal liver lesions with spindle cell morphology.MethodsA six-year retrospective analysis was conducted at a tertiary hospital in Thailand. All focal liver lesions with spindle cell morphology were retrieved. Clinicopathologic features of these cases were analyzed. The pathological diagnosis was rendered primarily based on routine histopathology, using other ancillary studies as an adjunct.Results287 biopsies and 151 resection specimens with focal liver lesions were identified. In 12 (2.7%) cases, tumors or tumor-like lesions with spindle cell morphology were retrieved. A total of five cases had discrepancies between histopathology and radiologic findings. These lesions encompassed primary liver tumors (EBV-associated smooth muscle tumor and leiomyosarcoma); metastatic tumors (gastrointestinal stromal tumor, small cell neuroendocrine carcinoma); and a tumor-like lesion (endometriosis). Several morphologic findings (i.e., cytologic grades, dense and loose areas, intratumoral lymphocytes, distinct perinuclear vacuoles, and hemosiderin) are important clues to diagnose these spindle cell lesions.ConclusionsPathologists play a critical role in diagnosing focal liver lesions with spindle cell morphology, particularly those with limited clinical data at the initial presentation. A thorough evaluation of histomorphology on routine hematoxylin and eosin-stained slides is essential for correct diagnosis.