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PurposeTo develop an ultrasound (US)-based radiomics score for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).MethodsBetween January 1, 2012, and October 31, 2017, a total of 482 HCC patients who underwent contrast-enhanced ultrasound (CEUS) were retrospectively reviewed. The study population was divided into a training cohort (n = 341) and a validation cohort (n = 141) based on a cutoff time of January 1, 2016. Radiomics features were extracted from the grayscale US images of HCC. After features selection, a radiomics score was developed from the training cohort. The incremental value of the radiomics score to the clinic-pathological factors for MVI prediction was assessed in the validation cohort with respect to discrimination, calibration, and clinical usefulness.ResultsThe US-based radiomics score consisted of six selected features. Multivariate logistic regression analysis showed that the radiomics score, alpha-fetoprotein (AFP), and tumor size were independent predictors of MVI. The radiomics nomogram (based on the three factors) showed better performance for MVI detection (area under the curve [AUC] 0.731[0.647, 0.815] than the clinical nomogram (based on AFP and tumor size) (0.634 [0.543, 0.724]) (p = 0.015). Both nomograms showed good calibration. Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the clinical nomogram.ConclusionThe US-based radiomics score was an independent predictor of MVI in HCC. Combining the radiomics score with clinical factors improved the prediction efficacy.Key points• Radiomics can be applied in US images.• US-based radiomics score was an independent predictor of MVI.• Radiomics nomogram incorporated with the radiomics score showed good performance for MVI prediction.

Endoscopy-assisted breast surgery (EABS) performed through minimal axillary and/or periareolar incisions is a possible alternative to open surgery for certain patients with breast cancer. In this study, we report the early results of an EABS program in Taiwan. The medical records of patients who underwent EABS for breast cancer during the period May 2009 to December 2014 were collected from the Taiwan Endoscopic Breast Surgery Cooperative Group database. Data on clinicopathologic characteristics, type of surgery, method of breast reconstruction, complications and recurrence were analyzed to determine the effectiveness and oncologic safety of EABS in Taiwan. A total of 315 EABS procedures were performed in 292 patients with breast cancer, including 23 (7.8%) patients with bilateral disease. The number of breast cancer patients who underwent EABS increased initially from 2009 to 2012 and then stabilized during the period 2012-2014. The most commonly performed EABS was endoscopy-assisted total mastectomy (EATM) (85.4%) followed by endoscopy-assisted partial mastectomy (EAPM) (14.6%). Approximately 74% of the EATM procedures involved breast reconstruction, with the most common types of reconstruction being implant insertion and autologous pedicled TRAM flap surgery. During the six-year study period, there was an increasing trend in the performance of EABS for the management of breast cancer when total mastectomy was indicated. The positive surgical margin rate was 1.9%. Overall, the rate of complications associated with EABS was 15.2% and all were minor and wound-related. During a median follow-up of 26.8 (3.3-68.6) months, there were 3 (1%) cases of local recurrence, 1 (0.3%) case of distant metastasis and 1 (0.3%) death. The preliminary results from the EABS program in Taiwan show that EABS is a safe procedure and results in acceptable cosmetic outcome. These findings could help to promote this under-used surgical technique in the field of breast cancer.

Abstract Background and aim The distinction of intestinal fibrosis from inflammation in Crohn's disease (CD) associated strictures has important therapeutic implications. Ultrasound elastography is useful in evaluating the degree of fibrosis in liver, but there is little evidence whether it can assess fibrosis in the bowel. We determined whether shear-wave elastography (SWE), a novel modification of elastography, quantifying tissue stiffness, could differentiate between inflammatory and fibrotic components in strictures of patients with CD. Methods Consecutive CD patients with ileal/ileocolonic strictures who underwent SWE within 1 week to surgical resection were enrolled. The SWE value of the stenotic bowel wall was compared to the grade and severity of fibrosis and inflammation, respectively, in the resected bowel specimen. Results Thirty-five patients were enrolled. The mean SWE value of stenotic bowel wall was significantly higher in severe fibrosis (23.0 ± 6.3 Kpa) than that in moderate (17.4 ± 3.8 Kpa) and mild fibrosis (14.4 ± 2.1 Kpa)(P = 0.008). Using 22.55 KPa as the cutoff value in discriminating between mild/moderate and severe fibrosis, the sensitivity and specificity was 69.6 % and 91.7% with an area under the curve (AUC) of 0.822 (P = 0.002). However, no significant difference regarding mean SWE existed among different grades of inflammation. The sensitivity and specificity of bowel vascularization score on conventional ultrasound in differentiating severe inflammation from mild/moderate was 87.5 % and 57.9% with AUC of 0.811 (P = 0.002). Combining SWE and conventional ultrasound (bowel vascularization score), we propose a bowel ultrasound classification of intestinal strictures. A moderate agreement between ultrasound and pathological classification was observed (κ = 0.536, P＜0.001). Conclusions This pilot study suggests that SWE is feasible and accurate in detecting intestinal fibrosis in patients with CD. After validation, combing SWE and bowel vascularization on conventional ultrasound might be applied to guide a management strategy in CD patients through defining the type of intestinal stricture. 10.1093/ibd/izy115_video1 izy115.video1 5777734754001

Objective The main aim of this study was to analyze the performance of different artificial intelligence (AI) models in endoscopic colonic polyp detection and classification and compare them with doctors with different experience. Methods We searched the studies on Colonoscopy, Colonic Polyps, Artificial Intelligence, Machine Learning, and Deep Learning published before May 2020 in PubMed, EMBASE, Cochrane, and the citation index of the conference proceedings. The quality of studies was assessed using the QUADAS-2 table of diagnostic test quality evaluation criteria. The random-effects model was calculated using Meta-DISC 1.4 and RevMan 5.3. Results A total of 16 studies were included for meta-analysis. Only one study (1/16) presented externally validated results. The area under the curve (AUC) of AI group, expert group and non-expert group for detection and classification of colonic polyps were 0.940, 0.918, and 0.871, respectively. AI group had slightly lower pooled specificity than the expert group (79% vs. 86%, P  < 0.05), but the pooled sensitivity was higher than the expert group (88% vs. 80%, P  < 0.05). While the non-experts had less pooled specificity in polyp recognition than the experts (81% vs. 86%, P  < 0.05), and higher pooled sensitivity than the experts (85% vs. 80%, P  < 0.05). Conclusion The performance of AI in polyp detection and classification is similar to that of human experts, with high sensitivity and moderate specificity. Different tasks may have an impact on the performance of deep learning models and human experts, especially in terms of sensitivity and specificity.

It is undoubtedly true that ports can modify aspects of the regions where they are inserted in many different ways. Scholars have presented various perspectives on the influence of ports in society, including their roles according to their purpose. Surprisingly, in the age of sustainable development, the social roles of ports have not been explored in depth, and this offers an opportunity to increase the knowledge of this sector. This paper aims to investigate how managers in ports perceive their roles in the social dimension and why they think they should exist, presenting opportunities to align business objectives with the expectations of other stakeholders. Applying the content analysis technique, 28 interviews were conducted with managers in Brazilian ports and themes were developed to represent their views on social roles (5) and the reasons for adopting them (6). Overall, managers perceive social roles as part of the strategic business plan and present reasons to adopt them, ranging from compulsory to voluntary. Conclusions suggest that more needs to be done to expand the understanding of a pragmatic approach to social roles and to develop more focused actions according to the reasons for adopting social roles.

Wound size measurement is an important indicator of wound healing. Nurses measure wound size in terms of length × width in wound healing assessment, but it is easy to overestimate the extent of the wound due to irregularities around it. Using hyperspectral imaging (HIS) to measure the area of a pressure injury could provide more accurate data than manual measurement, ensure that the same tool is used for standardized assessment of wounds, and reduce the measurement time. This study was a pilot cross-sectional study, and a total of 30 patients with coccyx sacral pressure injuries were recruited to the rehabilitation ward after approval by the human subjects research committee. We used hyperspectral images to collect pressure injury images and machine learning (k-means) to automatically classify wound areas in combination with the length × width rule (LW rule) and image morphology algorithm for wound judgment and area calculation. The results calculated from the data were compared with the calculations made by the nursing staff using the length × width rule. The use of hyperspectral images, machine learning, the length × width rule (LW rule), and an image morphology algorithm to calculate the wound area yielded more accurate measurements than did nurses, effectively reduced the chance of human error, reduced the measurement time, and produced real-time data. HIS can be used by nursing staff to assess wounds with a standardized approach so as to ensure that proper wound care can be provided.

With the growing global popularity of Android apps, ensuring their quality and reliability has become increasingly important, as low-quality apps can lead to poor user experiences and potential business losses. A common approach to testing Android apps involves automatically generating event sequences that interact with the app’s graphical user interface (GUI) to detect crashes. To support this, we developed ACE (Android Crawler), a tool that systematically generates events to test Android apps by automatically exploring their GUIs. However, ACE’s original heuristic-driven exploration can be inefficient in complex application states. To address this, we extend ACE with a deep reinforcement learning-based crawling strategy, called Reinforcement Learning Strategy (RLS), which tightly integrates with ACE’s GUI exploration process by learning to intelligently select GUI components and interaction actions. RLS leverages the Proximal Policy Optimization (PPO) algorithm for stable and efficient learning and incorporates an action mask to filter invalid actions, thereby reducing training time. We evaluate RLS on 15 real-world Android apps and compare its performance against the original ACE and three state-of-the-art Android testing tools. Results show that RLS improves code coverage by an average of 2.1% over ACE’s Nearest unvisited event First Search (NFS) strategy and outperforms all three baseline tools in terms of code coverage. Paired t-test analyses further confirm that these improvements are statistically significant, demonstrating its effectiveness in enhancing automated Android GUI testing.

Background Neoadjuvant chemotherapy is a promising treatment option for potential resectable gastric cancer, but patients’ responses vary. We aimed to develop and validate a radiomics score (rad_score) to predict treatment response to neoadjuvant chemotherapy and to investigate its efficacy in survival stratification. Methods A total of 106 patients with neoadjuvant chemotherapy before gastrectomy were included (training cohort: n  = 74; validation cohort: n  = 32). Radiomics features were extracted from the pre-treatment portal venous-phase CT. After feature reduction, a rad_score was established by Randomised Tree algorithm. A rad_clinical_score was constructed by integrating the rad_score with clinical variables, so was a clinical score by clinical variables only. The three scores were validated regarding their discrimination and clinical usefulness. The patients were stratified into two groups according to the score thresholds (updated with post-operative clinical variables), and their survivals were compared. Results In the validation cohort, the rad_score demonstrated a good predicting performance in treatment response to the neoadjuvant chemotherapy (AUC [95% CI] =0.82 [0.67, 0.98]), which was better than the clinical score (based on pre-operative clinical variables) without significant difference (0.62 [0.42, 0.83], P  = 0.09). The rad_clinical_score could not further improve the performance of the rad_score (0.70 [0.51, 0.88], P  = 0.16). Based on the thresholds of these scores, the high-score groups all achieved better survivals than the low-score groups in the whole cohort (all P  < 0.001). Conclusion The rad_score that we developed was effective in predicting treatment response to neoadjuvant chemotherapy and in stratifying patients with gastric cancer into different survival groups. Our proposed strategy is useful for individualised treatment planning.

The introduction of dry ports to transport networks facilitates trade, allows containers to be distributed between transport modes and ensures optimal use of networks. However, dry ports face several challenges, which have a significant impact on their operations, often reducing the benefits from developing dry ports in national or regional freight transport systems. In this regard, this paper investigates the influential factors of dry port operations. We firstly identify five categories of influencing factors and their respective sub-factors. Subsequently, we conduct an empirical study through a web-based survey of Malaysian dry port stakeholders. Multiple regression is employed for data analysis. Findings suggest 12 factors of significant importance to Malaysian dry port operations, including the need for sufficient information sharing; accurate freight forecasting, customs clearance, value-added services, adequate highway infrastructure; existence of appropriate operational equipment and sufficient space for current and future container storage; implementation of public–private partnerships; impact of seaport and short sea shipping policy; road connectivity and the location itself of dry ports. The paper is expected to be of managerial value to dry port operators, when developing strategies to enhance operational efficiency.

Abstract Background Early changes in bowel behavior during anti-tumor necrosis factor (anti-TNF) induction therapy in Crohn’s disease (CD) are relatively unknown. We determined (1) the onset of changes in bowel behavior in CD patients receiving anti-TNF therapy by ultrasound and (2) the feasibility of shear wave elastography (SWE) in predicting early response to anti-TNF therapy. Methods Consecutive ileal or ileocolonic CD patients programmed to initiate anti-TNF therapy were enrolled. Bowel ultrasound was performed at baseline and at weeks 2, 6, and 14. Changes in bowel wall thickness, Doppler signals of the bowel wall (Limberg score), and SWE values were compared using a linear mixed model. Early response to anti-TNF therapy was based on a composite strategy of clinical and colonoscopy assessment at week 14. Results Of the 30 patients enrolled in this study, 20 patients achieved a response to anti-TNF therapy at week 14. The bowel wall thickness and SWE value of the response group showed a significant downward trend compared with the nonresponse group (P = .003 and P = .011, respectively). Bowel wall thickness, the Limberg score, and SWE values were significantly reduced as early as week 2 compared with baseline (P < .001, P < .001, and P = .003, respectively) in the response group. Baseline SWE values (21.3 ± 8.7 kPa vs 15.3 ± 4.7 kPa; P = .022) and bowel wall thickness (8.5 ± 2.3 mm vs 6.9 ± 1.5 mm; P = .027) in the nonresponse group were significantly higher than in the response group. Conclusions This pilot study suggested that changes in bowel ultrasound behavior could be assessed as early as week 2 after starting anti-TNF therapy. Bowel ultrasound together with elasticity imaging could predict early response to anti-TNF therapy. Lay Summary This pilot study suggested that changes in bowel ultrasound behavior could be assessed as early as 2 weeks after anti-tumor necrosis factor therapy in patients with Crohn’s disease. Bowel ultrasound together with elasticity imaging could predict early response to anti-tumor necrosis factor therapy.