Fatigue after Liver Transplantation

Liver transplantation (LTx) has developed from an experimental procedure in the 1960’s to the preferred treatment for end-stage liver disease nowadays. The first human LTx was performed by Starlz and his team in 1963 in Colorado.[1] Unfortunately, this patient died within a few days. The first successful LTx was performed in 1967 by the same team; this patient survived one year. The most prevalent indications for LTx in Europe are virus-related cirrhosis (22%), alcoholic cirrhosis (19%), cancer (18%), cholestatic liver diseases (11%), acute hepatic failure (9%) and metabolic disease (6%).[2] The main complications in the immediate postoperative period are dysfunction and rejection of the graft, infections, bile duct complications and pulmonary or neurological problems. Long-term complications after LTx are typically a consequence of the prolonged immunosuppressive therapy, and include diabetes mellitus, infections, renal dysfunction, hypertension, osteoporosis, and de novo neoplasia.[3] Currently, three University Medical Centers are performing LTx’s in the Netherlands: Groningen, Leiden and Rotterdam

A Deep Learning Model for Segmentation of Geographic Atrophy to Study Its Long-Term Natural History

__Purpose:__ To develop and validate a deep learning model for the automatic segmentation of geographic atrophy (GA) using color fundus images (CFIs) and its application to study the growth rate of GA. __Design:__ Prospective, multicenter, natural history study with up to 15 years of follow-up. __Participants:__ Four hundred nine CFIs of 238 eyes with GA from the Rotterdam Study (RS) and Blue Mountain Eye Study (BMES) for model development, and 3589 CFIs of 376 eyes from the Age-Related Eye Disease Study (AREDS) for analysis of GA growth rate. __Methods:__ A deep learning model based on an ensemble of encoder–decoder architectures was implemented and optimized for the segmentation of GA in CFIs. Four experienced graders delineated, in consensus, GA in CFIs from the RS and BMES. These manual delineations were used to evaluate the segmentation model using 5-fold cross-validation. The model was applied further to CFIs from the AREDS to study the growth rate of GA. Linear regression analysis was used to study associations between structural biomarkers at baseline and the GA growth rate. A general estimate of the progression of GA area over time was made by combining growth rates of all eyes with GA from the AREDS set. __Main Outcome Measures:__ Automatically segmented GA and GA growth rate. __Results:__ The model obtained an average Dice coefficient of 0.72±0.26 on the BMES and RS set while comparing the automatically segmented GA area with the graders’ manual delineations. An intraclass correlation coefficient of 0.83 was reached between the automatically estimated GA area and the graders’ consensus measures. Nine automatically calculated structural biomarkers (area, filled area, convex area, convex solidity, eccentricity, roundness, foveal involvement, perimeter, and circularity) were significantly associated with growth rate. Combining all growth rates indicated that GA area grows quadratically up to an area of approximately 12 mm2, after which growth rate stabilizes or decreases. __Conclusions:__ The deep learning model allowed for fully automatic and robust segmentation of GA on CFIs. These segmentations can be used to extract structural characteristics of GA that predict its growth rate

Bone suppression increases the visibility of invasive pulmonary aspergillosis in chest radiographs

Objective: Chest radiographs (CXR) are an important diagnostic tool for the detection of invasive pulmonary aspergillosis (IPA) in critically ill patients, but their diagnostic value is limited by a poor sensitivity. By using advanced image processing, the aim of this study was to increase the value of chest radiographs in the diagnostic work up of neutropenic patients who are suspected of IPA. Methods: The frontal CXRs of 105 suspected cases of IPA were collected from four institutions. Radiographs could contain single or multiple sites of infection. CT was used as reference standard. Five radiologists and two residents participated in an observer study for the detection of IPA on CXRs with and without bone suppressed images (ClearRead BSI 3.2; Riverain Technologies). The evaluation was performed separately for the right and left lung, resulting in 78 diseased cases (or lungs) and 132 normal cases (or lungs). For each image, observers scored the likelihood of focal infectious lesions being present on a continuous scale (0-100). The area under the receiver operating characteristics curve (AUC) served as the performance measure. Sensitivity and specificity were calculated by considering only the lungs with a suspiciousness score of greater than 50 to be positive. Results: The average AUC for only CXRs was 0.815. Performance significantly increased, to 0.853, when evaluation was aided with BSI (p = 0.01). Sensitivity increased from 49% to 66% with BSI, while specificity decreased from 95% to 90%. Conclusion: The detection of IPA in CXRs can be improved when their evaluation is aided by bone suppressed images. BSI improved the sensitivity of the CXR examination, outweighing a small loss in specificity

Physical fitness, fatigue, and quality of life after liver transplantation

Fatigue is often experienced after liver transplantation. The aims of this cross-sectional study were to assess physical fitness (cardiorespiratory fitness, neuromuscular fitness, body composition) in liver transplant recipients and to explore whether physical fitness is related to severity of fatigue. In addition, we explored the relationship between physical fitness and health-related quality of life. Included were 18 patients 1–5 years after transplantation (aged 48.0 ± 11.8 years) with varying severity of fatigue. Peak oxygen uptake during cycle ergometry, 6-min walk distance, isokinetic muscle strength of the knee extensors, body mass index, waist circumference, skinfold thickness, severity of fatigue, and health-related quality of life were measured. Cardiorespiratory fitness in the liver transplant recipients was on average 16–34% lower than normative values (P ≤ 0.05). Furthermore, the prevalence of obesity seemed to be higher than in the general population (17 vs. 10%). We found no deficit in neuromuscular fitness. Cardiorespiratory fitness was the only fitness component that was related with severity of fatigue (rs = −0.61 to rs = -0.50, P ≤ 0.05). Particularly cardiorespiratory fitness was related with several aspects of health-related quality of life (rs = 0.48 to rs = 0.70, P ≤ 0.05). Results of our study imply that cardiorespiratory fitness and body composition are impaired in liver transplant recipients and that fitness is related with severity of fatigue (only cardiorespiratory fitness) and quality of life (particularly cardiorespiratory fitness) in this group. These findings have implications for the development of rehabilitation programs for liver transplant recipients

Why rankings of biomedical image analysis competitions should be interpreted with care

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future

Sensory evaluation of the hands in patients with Charcot-Marie-Tooth disease using Semmes-Weinstein monofilaments

In this study, the intra- and interobserver reliability of the Semmes-Weinstein monofilaments (SWMFs) was determined in the hands of 15 patients with Charcot-Marie-Tooth disease. In addition, the amount and distribution of sensory loss in the hand, and the relation between sensory loss, intrinsic muscle strength, and hand dexterity was explored in 45 patients. SWMF testing had good intra- and interobserver reliability with intraclass correlation coefficients of 0.91 and 0.86, respectively. The SWMF testing revealed normal sensory function in 43% of all six locations. The average loss of the intrinsic hand muscle strength was 57%. Poor strength was found in patients with both poor and with good sensory function. The correlation between the measurements of intrinsic muscle strength and the Sollerman test for dexterity was 0.70