Diagnostic performance of preoperative CT in differentiating between benign and malignant origin of suspicious gallbladder lesions

Purpose: To determine diagnostic performance of preoperative CT in differentiating between benign and malignant suspicious gallbladder lesions and to develop a preoperative risk score. Method: All patients referred between January 2007 and September 2018 for suspicion of gallbladder cancer (GBC) or incidentally found GBC were retrospectively analyzed. Patients were excluded when preoperative CT or histopathologic examination was lacking. Two radiologists, blinded to histopathology results, independently reviewed CT images to differentiate benign disease from GBC. Multivariable analysis and internal validation were used to develop a risk score for GBC. Model discrimination, calibration, and diagnostic performance were assessed. Results: In total, 118 patients with 39 malignant (33 %) and 79 benign (67 %) lesions were included. Sensitivity of CT for diagnosing GBC was 90 % (95 % confidence interval [CI]: 76?97). Specificity rates were 61 % (95 % CI: 49?72) and 59 % (95 % CI: 48?70). Three predictors of GBC (irregular lesion aspect, absence of fat stranding, and locoregional lymphadenopathy) were included in the risk score ranging from -1 to 4. Adequate performance was found (AUC: 0.79, calibration slope: 0.89). In patients allocated >0 points, the model showed higher performance in excluding GBC than the radiologists (sensitivity 92 % [95 % CI: 79?98]). Moreover, when allocated >3 points, the risk score was superior in diagnosing GBC (specificity 99 % [95 % CI: 93?100]). Conclusions: Sensitivity rates of CT for differentiation between benign and malignant gallbladder lesions are high, however specificity rates are relatively low. The proposed risk score may facilitate differentiation between benign and malignant suspicious gallbladder lesions

Liver Volumetry Plug and Play: Do It Yourself with ImageJ

AB - BACKGROUND: A small remnant liver volume is an important risk factor for posthepatectomy liver failure and can be predicted accurately by computed tomography (CT) volumetry using radiologic image analysis software. Unfortunately, this software is expensive and usually requires support by a radiologist. ImageJ is a freely downloadable image analysis software package developed by the National Institute of Health (NIH) and brings liver volumetry to the surgeon's desktop. We aimed to assess the accuracy of ImageJ for hepatic CT volumetry. METHODS: ImageJ was downloaded from http://www.rsb.info.nih.gov/ij/ . Preoperative CT scans of 15 patients who underwent liver resection for colorectal cancer liver metastases were retrospectively analyzed. Scans were opened in ImageJ; and the liver, all metastases, and the intended parenchymal transection line were manually outlined on each slice. The area of each selected region, metastasis, resection specimen, and remnant liver was multiplied by the slice thickness to calculate volume. Volumes of virtual liver resection specimens measured with ImageJ were compared with specimen weights and calculated volumes obtained during pathology examination after resection. RESULTS: There was an excellent correlation between the volumes calculated with ImageJ and the actual measured weights of the resection specimens (r(2) = 0.98, p < 0.0001). The weight/volume ratio amounted to 0.88 +/- 0.04 (standard error) and was in agreement with our earlier findings using CT-linked radiologic software. CONCLUSION: ImageJ can be used for accurate hepatic CT volumetry on a personal computer. This application brings CT volumetry to the surgeon's desktop at no expense and is particularly useful in cases of tertiary referred patients, who already have a proper CT scan on CD-ROM from the referring institution. Most likely the discrepancy between volume and weight results from exsanguination of the liver after resectio

Effect of surgical volume on short-term outcomes of cytoreductive surgery for advanced-stage ovarian cancer:A population-based study from the Dutch Gynecological Oncology Audit

Objective: Despite lacking clinical data, the Dutch government is considering increasing the minimum annual surgical volume per center from twenty to fifty cytoreductive surgeries (CRS) for advanced-stage ovarian cancer (OC). This study aims to evaluate whether this increase is warranted. Methods: This population-based study included all CRS for FIGO-stage IIB-IVB OC registered in eighteen Dutch hospitals between 2019 and 2022. Short-term outcomes included result of CRS, length of stay, severe complications, 30-day mortality, time to adjuvant chemotherapy, and textbook outcome. Patients were stratified by annual volume: low-volume (nine hospitals, &lt;25), medium-volume (four hospitals, 29–37), and high-volume (five hospitals, 54–84). Descriptive statistics and multilevel logistic regressions were used to assess the (case-mix adjusted) associations of surgical volume and outcomes. Results: A total of 1646 interval CRS (iCRS) and 789 primary CRS (pCRS) were included. No associations were found between surgical volume and different outcomes in the iCRS cohort. In the pCRS cohort, high-volume was associated with increased complete CRS rates (aOR 1.9, 95%-CI 1.2–3.1, p = 0.010). Furthermore, high-volume was associated with increased severe complication rates (aOR 2.3, 1.1–4.6, 95%-CI 1.3–4.2, p = 0.022) and prolonged length of stay (aOR 2.3, 95%-CI 1.3–4.2, p = 0.005). 30-day mortality, time to adjuvant chemotherapy, and textbook outcome were not associated with surgical volume in the pCRS cohort. Subgroup analyses (FIGO-stage IIIC-IVB) showed similar results. Various case-mix factors significantly impacted outcomes, warranting case-mix adjustment. Conclusions: Our analyses do not support further centralization of iCRS for advanced-stage OC. High-volume was associated with higher complete pCRS, suggesting either a more accurate selection in these hospitals or a more aggressive approach. The higher completeness rates were at the expense of higher severe complications and prolonged admissions.</p

Do we need to distance ourselves from the distance concept? Why home and host country context might matter more than (cultural) distance

We scrutinize the explanatory power of one of the key concepts in International Business: the concept of (cultural) distance. Here we focus on its effect on entry mode choice, one of the most researched fields in international business strategy. Our findings might, however, be equally be relevant for the field of International Business as a whole. Our analysis is based on a review of 92 prior studies on entry mode choice, as well as an empirical investigation in over 800 subsidiaries of MNCs, covering nine host and fifteen home countries across the world. We conclude that the explanatory power of distance is highly limited once home and host country context are accounted for, and that any significant effects of cultural distance on entry mode choice might simply be caused by inadequate sampling. Entry mode studies in particular, and International Business research in general, would do well to reconsider its fascination with distance measures, and instead, focus first and foremost on differences in home and host country context. We argue that serious engagement with deep contextualization is necessary in International Business research to pose new and relevant questions and develop new and innovative theories that explain empirical phenomena

Effects of climate change on exposure to coastal flooding in Latin America and the Caribbean

This study considers and compares several of the most important factors contributing to coastal flooding in Latin American and the Caribbean (LAC) while accounting for the variations of these factors with location and time. The study assesses the populations, the land areas and the built capital exposed at present and at the middle and end of the 21st century for a set of scenarios that include both climatic and non-climatic drivers. Climatic drivers include global mean sea level, natural modes of climate variability such as El Niño, natural subsidence, and extreme sea levels resulting from the combination of projected local sea-level rise, storm surges and wave setup. Population is the only human-related driver accounted for in the future. Without adaptation, more than 4 million inhabitants will be exposed to flooding from relative sea-level rise by the end of the century, assuming the 8.5 W m&#8722;2 trajectory of the Representative Concentration Pathways (RCPs), or RCP8.5. However, the contributions from El Niño events substantially raise the threat in several Pacific-coast countries of the region and sooner than previously anticipated. At the tropical Pacific coastlines, the exposure by the mid-century for an event similar to El Niño 1998 would be comparable to that of the RCP4.5 relative sea-level rise by the end of the century. Furthermore, more than 7.5 million inhabitants, 42,600 km2 and built capital valued at 334 billion USD are currently situated at elevations below the 100-year extreme sea level. With sea levels rising and the population increasing, it is estimated that more than 9 million inhabitants will be exposed by the end of the century for either of the RCPs considered. The spatial distribution of exposure and the comparison of scenarios and timeframes can serve as a guide in future adaptation and risk reduction policies in the region

The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change

Future sea-level rise projections are characterized by both quantifiable uncertainty and unquantifiable structural uncertainty. Thorough scientific assessment of sea-level rise projections requires analysis of both dimensions of uncertainty. Probabilistic sea-level rise projections evaluate the quantifiable dimension of uncertainty; comparison of alternative probabilistic methods provides an indication of structural uncertainty. Here we describe the Framework for Assessing Changes To Sea-level (FACTS), a modular platform for characterizing different probability distributions for the drivers of sea-level change and their consequences for global mean, regional, and extreme sea-level change. We demonstrate its application by generating seven alternative probability distributions under multiple emissions scenarios for both future global mean sea-level change and future relative and extreme sea-level change at New York City. These distributions, closely aligned with those presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report, emphasize the role of the Antarctic and Greenland ice sheets as drivers of structural uncertainty in sea-level change projections.</p