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Background Among treatment options for fecal incontinence, none are curative. Adipose-derived stem cells (ADSCs) have emerged as promising therapeutic agents, but most preclinical studies of their effectiveness for anal function have used autologous or allogeneic ADSCs. Here, we investigated the effectiveness, timing of administration, and required dosage of human (h)ADSCs for clinical application. Methods A 10-mm balloon catheter was used to induce anal sphincter injury in immunodeficient mice in three groups: ADSC (hADSCs injected after injury), phosphate-buffered saline (PBS; injected after injury), and control (uninjured). The effects of different timing and number of hADSCs administered was compared among groups using defecation status and pathological evaluation. Results In terms of defecation status, groups receiving ≥ 1 × 104 hADSCs immediately after injection showed improvement. Pathological images showed that compared with the PBS group, the thinnest part of the sphincter was thicker for animals that received ≥ 1 × 104 hADSCs, and fibrosis of the sphincter was notable in those treated with 1 × 103 hADSCs or PBS. Furthermore, although administration of hADSCs at 30 days following injury yielded no pathological signs of improvement, defecation status was improved. Conclusions hADSC administration in a mouse model of anal sphincter injury was effective. Injection of ≥ 1 × 104 hADSCs was necessary to improve defecation status, an effect detected in both the acute and chronic phases.

The submucosal invasion depth predicts prognosis in early colorectal cancer. Although colorectal cancer with shallow submucosal invasion can be treated via endoscopic resection, colorectal cancer with deep submucosal invasion requires surgical colectomy. However, accurately diagnosing the depth of submucosal invasion via endoscopy is difficult. We developed a tool to diagnose the depth of submucosal invasion in early colorectal cancer using artificial intelligence. We reviewed data from 196 patients who had undergone a preoperative colonoscopy at the Osaka University Hospital and Osaka International Cancer Institute between 2011 and 2018 and were diagnosed pathologically as having shallow submucosal invasion or deep submucosal invasion colorectal cancer. A convolutional neural network for predicting invasion depth was constructed using 706 images from 91 patients between 2011 and 2015 as the training dataset. The diagnostic accuracy of the constructed convolutional neural network was evaluated using 394 images from 49 patients between 2016 and 2017 as the validation dataset. We also prospectively tested the tool from 56 patients in 2018 with suspected early-stage colorectal cancer. The sensitivity, specificity, accuracy, and area under the curve of the convolutional neural network for diagnosing deep submucosal invasion colorectal cancer were 87.2% (258/296), 35.7% (35/98), 74.4% (293/394), and 0.758, respectively. The positive predictive value was 84.4% (356/422) and the sensitivity was 75.7% (356/470) in the test set. The diagnostic accuracy of the constructed convolutional neural network seemed to be as high as that of a skilled endoscopist. Thus, endoscopic image recognition by deep learning may be able to predict the submucosal invasion depth in early-stage colorectal cancer in clinical practice.

Purpose Inflammation and nutritional status are known to be associated with the prognosis of several malignancies. Herein, we attempted to develop inflammation–nutrition scores and predict the prognosis of stage III colorectal cancer (CRC). Methods This retrospective study included 262 patients with stage III CRC who underwent curative surgery and were divided into two groups: a training set (TS) of 162 patients and a validation set (VS) of 100 patients. In the TS, clinicopathological factors were tested using a Cox regression model, and the Kansai prognostic score (KPS) was assessed by 1 point each for 450 monocyte counts, and 5 platelet counts, which were associated with disease-free survival (DFS). Using KPS, DFS and overall survival (OS) were validated in VS. Results The C-indices of KPS to predict DFS and OS in TS were 0.707 and 0.772. It was validated in VS that the C-indices of KPS to predict DFS and OS were 0.618 and 0.708, respectively. A high KPS was a significant predictor of DFS and OS. Conclusion KPS serves as a new model for the prognosis of patients with stage III CRC.

Background Local recurrence is common after curative resections for rectal cancer. Surgical intervention is among the best treatment choices. However, achieving a negative resection margin often requires extensive pelvic organ resections; thus, the postoperative complication rate is quite high. Recent studies have reported that the inflammatory index could predict postoperative complications. This study aimed to validate the correlation between clinical factors, including inflammatory markers, and severe complications after surgery for local recurrent rectal cancer. Methods This retrospective study included 99 patients that underwent radical resections for local recurrences of rectal cancer. Postoperative complications were graded according to the Clavien-Dindo classification. Grades ≥3 were defined as severe complications. Risk factors for severe complications were identified with univariate and multivariate logistic regression models and assessed with receiver-operating characteristic curves. Results Severe postoperative complications occurred in 38 patients (38.4%). Analyses of correlations between inflammatory markers and severe postoperative complications revealed that the strongest correlation was found between the prognostic nutrition index and severe postoperative complications. The receiver-operating characteristic analysis showed that the optimal prognostic nutrition index cut-off value was 42.2 (sensitivity: 0.790, specificity: 0.508). In univariate and multivariate analyses, a prognostic nutrition index ≤44.2 (Odds ratio: 3.007, 95%CI:1.171–8.255, p = 0.02) and a blood loss ≥2850 mL (Odds ratio: 2.545, 95%CI: 1.044–6.367, p = 0.04) were associated with a significantly higher incidence of severe postoperative complications. Conclusions We found that a low preoperative prognostic nutrition index and excessive intraoperative blood loss were risk factors for severe complications after surgery for local recurrent rectal cancer.

Background The presence of lateral pelvic lymph node (LLN) metastasis is an essential prognostic factor in rectal cancer patients. Thus, preoperative diagnosis of LLN metastasis is clinically important to determine the therapeutic strategy. The aim of this study was to evaluate the efficacy of preoperative positron emission tomography/computed tomography (PET/CT) in the diagnosis of LLN metastasis. Methods Eighty-four patients with rectal cancer who underwent LLN dissection at Osaka University were included in this study. The maximum standardized uptake value (SUVmax) of the primary tumor and LLN were preoperatively calculated using PET/CT. Simultaneously, the short axis of the lymph node was measured using multi-detector row computed tomography (MDCT). The presence of metastases was evaluated by postoperative pathological examination. Results Of the 84 patients, LLN metastases developed in the left, right, and both LLN regions in 6, 7, and 2 patients, respectively. The diagnosis of the metastases was predicted with a sensitivity of 82%, specificity of 93%, positive predictive value of 58%, negative predictive value of 98%, false positive value of 7%, and false negative value of 18% when the cutoff value of the LLN SUVmax was set at 1.5. The cutoff value of the short axis set at 7 mm on MDCT was most useful in diagnosing LLN metastases, but SUVmax was even more useful in terms of specificity. Conclusions The cutoff value of 1.5 for lymph node SUVmax in PET is a reasonable measure to predict the risk of preoperative LLN metastases in rectal cancer patients.