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In Eurotransplant kidney allocation system (ETKAS), candidates can be considered unlimitedly for repeated re‐transplantation. Data on outcome and benefit are indeterminate. We performed a retrospective 15‐year patient and graft outcome data analysis from 1464 recipients of a third or fourth or higher sequential deceased donor renal transplantation (DDRT) from 42 transplant centers. Repeated re‐DDRT recipients were younger (mean 43.0 vs. 50.2 years) compared to first DDRT recipients. They received grafts with more favorable HLA matches (89.0% vs. 84.5%) but thereby no statistically significant improvement of patient and graft outcome was found as comparatively demonstrated in 1st DDRT. In the multivariate modeling accounting for confounding factors, mortality and graft loss after 3rd and ≥4th DDRT (P < 0.001 each) and death with functioning graft (DwFG) after 3rd DDRT (P = 0.001) were higher as compared to 1st DDRT. The incidence of primary nonfunction (PNF) was also significantly higher in re‐DDRT (12.7%) than in 1st DDRT (7.1%; P < 0.001). Facing organ shortage, increasing waiting time, and considerable mortality on dialysis, we question the current policy of repeated re‐DDRT. The data from this survey propose better HLA matching in first DDRT and second DDRT and careful selection of candidates, especially for ≥4th DDRT.
Background:
Oncolytic viral therapy represents an alternative therapeutic strategy for the treatment of cancer. We previously described GLV-1h68, a modified Vaccinia Virus with exclusive tropism for tumor cells, and we observed a cell line-specific relationship between the ability of GLV-1h68 to replicate in vitro and its ability to colonize and eliminate tumor in vivo.
Methods:
In the current study we surveyed the in vitro permissivity to GLV-1h68 replication of the NCI-60 panel of cell lines. Selected cell lines were also tested for permissivity to another Vaccinia Virus and a vesicular stomatitis virus (VSV) strain. In order to identify correlates of permissity to viral infection, we measured transcriptional profiles of the cell lines prior infection.
Results:
We observed highly heterogeneous permissivity to VACV infection amongst the cell lines. The heterogeneity of permissivity was independent of tissue with the exception of B cell derivation. Cell lines were also tested for permissivity to another Vaccinia Virus and a vesicular stomatitis virus (VSV) strain and a significant correlation was found suggesting a common permissive phenotype. While no clear transcriptional pattern could be identified as predictor of permissivity to infection, some associations were observed suggesting multifactorial basis permissivity to viral infection.
Conclusions:
Our findings have implications for the design of oncolytic therapies for cancer and offer insights into the nature of permissivity of tumor cells to viral infection.
Context:
Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.
Objective:
Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.
Design:
Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.
Results:
Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.
Conclusions:
Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.
Purpose
Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians.
Methods
A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning.
Results
Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805).
Conclusions
This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available.
Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe\(^{−/−}\), n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe\(^{−/−}\) mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.
Atherosclerosis is an inflammatory disease of large and medium-sized arteries, characterized by the growth of atherosclerotic lesions (plaques). These plaques often develop at inner curvatures of arteries, branchpoints, and bifurcations, where the endothelial wall shear stress is low and oscillatory. In conjunction with other processes such as lipid deposition, biomechanical factors lead to local vascular inflammation and plaque growth. There is also evidence that low and oscillatory shear stress contribute to arterial remodeling, entailing a loss in arterial elasticity and, therefore, an increased pulse-wave velocity. Although altered shear stress profiles, elasticity and inflammation are closely intertwined and critical for plaque growth, preclinical and clinical investigations for atherosclerosis mostly focus on the investigation of one of these parameters only due to the experimental limitations. However, cardiovascular magnetic resonance imaging (MRI) has been demonstrated to be a potent tool which can be used to provide insights into a large range of biological parameters in one experimental session. It enables the evaluation of the dynamic process of atherosclerotic lesion formation without the need for harmful radiation. Flow-sensitive MRI provides the assessment of hemodynamic parameters such as wall shear stress and pulse wave velocity which may replace invasive and radiation-based techniques for imaging of the vascular
function and the characterization of early plaque development. In combination with inflammation imaging, the analyses and correlations of these parameters could not only significantly advance basic preclinical investigations of atherosclerotic lesion formation and progression, but also the diagnostic clinical evaluation for early identification of high-risk plaques, which are prone to rupture. In this review, we summarize the key applications of magnetic resonance imaging for the evaluation of plaque characteristics through flow sensitive and morphological measurements. The simultaneous measurements of functional and structural parameters will further preclinical research on atherosclerosis and has the potential to fundamentally improve the detection of inflammation and vulnerable plaques in patients.
Differences between immunotherapy-induced and primary hypophysitis—a multicenter retrospective study
(2022)
Objective
Immune checkpoint inhibitors can cause various immune-related adverse events including secondary hypophysitis. We compared clinical characteristics of immunotherapy-induced hypophysitis (IIH) and primary hypophysitis (PH)
Design
Retrospective multicenter cohort study including 56 patients with IIH and 60 patients with PH.
Methods
All patients underwent extensive endocrine testing. Data on age, gender, symptoms, endocrine dysfunction, MRI, immunotherapeutic agents and autoimmune diseases were collected.
Results
Median time of follow-up was 18 months in IIH and 69 months in PH. The median time from initiation of immunotherapy to IIH diagnosis was 3 months. IIH affected males more frequently than PH (p < 0.001) and led to more impaired pituitary axes in males (p < 0.001). The distribution of deficient adenohypophysial axes was comparable between both entities, however, central hypocortisolism was more frequent (p < 0.001) and diabetes insipidus considerably less frequent in IIH (p < 0.001). Symptoms were similar except that visual impairment occurred more rarely in IIH (p < 0.001). 20 % of IIH patients reported no symptoms at all. Regarding MRI, pituitary stalk thickening was less frequent in IIH (p = 0.009). Concomitant autoimmune diseases were more prevalent in PH patients before the diagnosis of hypophysitis (p = 0.003) and more frequent in IIH during follow-up (p = 0.002).
Conclusions
Clinically, IIH and PH present with similar symptoms. Diabetes insipidus very rarely occurs in IIH. Central hypocortisolism, in contrast, is a typical feature of IIH. Preexisting autoimmunity seems not to be indicative of developing IIH.
Mitotane is the only approved drug for advanced adrenocortical carcinoma (ACC) and no biomarkers are available to predict attainment of therapeutic plasma concentrations and clinical response. Aim of the study was to evaluate the suitability of cytochrome P450(CYP)2W1 and CYP2B6 single nucleotide polymorphisms (SNPs) as biomarkers. A multicenter cohort study including 182 ACC patients (F/M = 121/61) treated with mitotane monotherapy after radical resection (group A, n = 103) or in not completely resectable, recurrent or advanced disease (group B, n = 79) was performed. CYP2W1*2, CYP2W1*6, CYP2B6*6 and CYP2B6 rs4803419 were genotyped in germline DNA. Mitotane blood levels were measured regularly. Response to therapy was evaluated as time to progression (TTP) and disease control rate (DCR). Among investigated SNPs, CYP2W1*6 and CYP2B6*6 correlated with mitotane treatment only in group B. Patients with CYP2W1*6 (n = 21) achieved less frequently therapeutic mitotane levels (>14 mg/L) than those with wild type (WT) allele (76.2% vs 51.7%, p = 0.051) and experienced shorter TTP (HR = 2.10, p = 0.019) and lower DCR (chi-square = 6.948, p = 0.008). By contrast, 55% of patients with CYP2B6*6 vs. 28.2% WT (p = 0.016) achieved therapeutic range. Combined, a higher rate of patients with CYP2W1*6WT+CYP2B6*6 (60.6%) achieved mitotane therapeutic range (p = 0.034). In not completely resectable, recurrent or advanced ACC, CYP2W1*6 SNP was associated with a reduced probability to reach mitotane therapeutic range and lower response rates, whereas CYP2B6*6 correlated with higher mitotane levels. The association of these SNPs may predict individual response to mitotane.
Livin/BIRC7 is a member of the inhibitors of apoptosis proteins family, which are involved in tumor development through the inhibition of caspases. Aim was to investigate the expression of livin and other members of its pathway in adrenocortical tumors and in the adrenocortical carcinoma (ACC) cell line NCI-H295R.
The mRNA expression of livin, its isoforms α and β, XIAP, CASP3 and DIABLO was evaluated by qRT-PCR in 82 fresh-frozen adrenal tissues (34 ACC, 25 adenomas = ACA, 23 normal adrenal glands = NAG). Livin protein expression was assessed by immunohistochemistry in 270 paraffin-embedded tissues (192 ACC, 58 ACA, 20 NAG). Livin, CASP3 and cleaved caspase-3 were evaluated in NCI-H295R after induction of livin overexpression.
Relative livin mRNA expression was significantly higher in ACC than in ACA and NAG (0.060 ± 0.116 vs 0.004 ± 0.014 and 0.002 ± 0.009, respectively, p < 0.01), being consistently higher in tumors than in adjacent NAG and isoform β more expressed than α. No significant differences in CASP3, XIAP and DIABLO levels were found among these groups. In immunohistochemistry, livin was localized in both cytoplasm and nuclei. The ratio between cytoplasmic and nuclear staining was significantly higher in ACC (1.51 ± 0.66) than in ACA (0.80 ± 0.35) and NAG (0.88 ± 0.27; p < 0.0001). No significant correlations were observed between livin expression and histopathological parameters or clinical outcome. In NCI-H295R cells, the livin overexpression slightly reduced the activation of CASP3, but did not correlate with cell viability.
In conclusion, livin is specifically over-expressed in ACC, suggesting that it might be involved in adrenocortical tumorigenesis and represent a new molecular marker of malignancy.
Background: Large Cell Neuroendocrine Carcinoma (LCNEC) is a rare subtype of lung cancer with poor clinical outcomes. Data on recurrence-free survival (RFS) in early and locally advanced pure LCNEC after complete resection (R0) are lacking. This study aims to evaluate clinical outcomes in this subgroup of patients and to identify potential prognostic markers. Methods: Retrospective multicenter study including patients with pure LCNEC stage I-III and R0 resection. Clinicopathological characteristics, RFS, and disease-specific survival (DSS) were evaluated. Univariate and multivariate analyses were performed. Results: 39 patients (M:F = 26:13), with a median age of 64 years (44–83), were included. Lobectomy (69.2%), bilobectomy (5.1%), pneumonectomy (18%), and wedge resection (7.7%) were performed mostly associated with lymphadenectomy. Adjuvant therapy included platinum-based chemotherapy and/or radiotherapy in 58.9% of cases. After a median follow-up of 44 (4–169) months, the median RFS was 39 months with 1-, 2- and 5-year RFS rates of 60.0%, 54.6%, and 44.9%, respectively. Median DSS was 72 months with a 1-, 2- and 5-year rate of 86.8, 75.9, and 57.4%, respectively. At multivariate analysis, age (cut-off 65 years old) and pN status were independent prognostic factors for both RFS (HR = 4.19, 95%CI = 1.46–12.07, p = 0.008 and HR = 13.56, 95%CI 2.45–74.89, p = 0.003, respectively) and DSS (HR = 9.30, 95%CI 2.23–38.83, p = 0.002 and HR = 11.88, 95%CI 2.28–61.84, p = 0.003, respectively). Conclusion: After R0 resection of LCNEC, half of the patients recurred mostly within the first two years of follow-up. Age and lymph node metastasis could help to stratify patients for adjuvant therapy.