Despite excellent 1-year survival, morbidity in benchmark cases remains high with half of patients developing severe complications during 1-year follow-up. Benchmark cutoffs targeting morbidity parameters offer a valid tool to assess higher risk groups.

ObjectiveTo provide a multi-atlas framework for automated hippocampus segmentation in temporal lobe epilepsy (TLE) and clinically validate the results with respect to surgical lateralization and post-surgical outcome.MethodsWe retrospectively identified 47 TLE patients who underwent surgical resection and 12 healthy controls. T1-weighted 3 T MRI scans were acquired for all subjects, and patients were identified by a neuroradiologist with regards to lateralization and degree of hippocampal sclerosis (HS). Automated segmentation was implemented through the Joint Label Fusion/Corrective Learning (JLF/CL) method. Gold standard lateralization was determined from the surgically resected side in Engel I (seizure-free) patients at the two-year timepoint. ROC curves were used to identify appropriate thresholds for hippocampal asymmetry ratios, which were then used to analyze JLF/CL lateralization.ResultsThe optimal template atlas based on subject images with varying appearances, from normal-appearing to severe HS, was demonstrated to be composed entirely of normal-appearing subjects, with good agreement between automated and manual segmentations. In applying this atlas to 26 surgically resected seizure-free patients at a two-year timepoint, JLF/CL lateralized seizure onset 92% of the time. In comparison, neuroradiology reads lateralized 65% of patients, but correctly lateralized seizure onset in these patients 100% of the time. When compared to lateralized neuroradiology reads, JLF/CL was in agreement and correctly lateralized all 17 patients. When compared to nonlateralized radiology reads, JLF/CL correctly lateralized 78% of the nine patients.SignificanceWhile a neuroradiologist's interpretation of MR imaging is a key, albeit imperfect, diagnostic tool for seizure localization in medically-refractory TLE patients, automated hippocampal segmentation may provide more efficient and accurate epileptic foci localization. These promising findings demonstrate the clinical utility of automated segmentation in the TLE MR imaging pipeline prior to surgical resection, and suggest that further investigation into JLF/CL-assisted MRI reading could improve clinical outcomes. Our JLF/CL software is publicly available at https://www.nitrc.org/projects/ashs/.

The prevalence of end-stage renal disease (ESRD) and the number of kidney transplants performed continues to rise every year, straining the procurement of deceased and living kidney allografts and health systems. Genome-wide genotyping and sequencing of diseased populations have uncovered genetic contributors in substantial proportions of ESRD patients. A number of these discoveries are beginning to be utilized in risk stratification and clinical management of patients. Specifically, genetics can provide insight into the primary cause of chronic kidney disease (CKD), the risk of progression to ESRD, and post-transplant outcomes, including various forms of allograft rejection. The International Genetics & Translational Research in Transplantation Network (iGeneTRAiN), is a multi-site consortium that encompasses >45 genetic studies with genome-wide genotyping from over 51,000 transplant samples, including genome-wide data from >30 kidney transplant cohorts (n = 28,015). iGeneTRAiN is statistically powered to capture both rare and common genetic contributions to ESRD and post-transplant outcomes. The primary cause of ESRD is often difficult to ascertain, especially where formal biopsy diagnosis is not performed, and is unavailable in ∼2% to >20% of kidney transplant recipients in iGeneTRAiN studies. We overview our current copy number variant (CNV) screening approaches from genome-wide genotyping datasets in iGeneTRAiN, in attempts to discover and validate genetic contributors to CKD and ESRD. Greater aggregation and analyses of well phenotyped patients with genome-wide datasets will undoubtedly yield insights into the underlying pathophysiological mechanisms of CKD, leading the way to improved diagnostic precision in nephrology.

Combined heart–liver transplantation (CHLT) is indicated for patients with concomitant end‐stage heart and liver disease or patients with amyloid heart disease where liver transplantation mitigates progression. Limited data suggest that the liver allograft provides immunoprotection for heart and kidney allografts in combined transplantation from the same donor. We hypothesized that CHLT reduces the incidence of acute cellular rejection (ACR) and the development of de novo donor‐specific antibodies (DSAs) compared with heart‐alone transplantation (HA). We conducted a retrospective analysis of 32 CHLT and 280 HA recipients in a single‐center experience. The primary outcome was incidence of ACR based on protocol and for‐cause myocardial biopsy. Rejection was graded by the International Society of Heart and Lung Transplantation guidelines with Grade 2R and higher considered significant. Secondary outcomes included the development of new DSAs, cardiac function, and patient and cardiac graft survival rates. Of CHLT patients, 9.7% had ACR compared with 45.3% of HA patients (p < 0.01). Mean pretransplant calculated panel reactive antibody (cPRA) levels were similar between groups (CHLT 9.4% vs. HA 9.5%; p = 0.97). Among patients who underwent testing, 26.9% of the CHLT and 16.7% of HA developed DSA (p = 0.19). Despite the difference in ACR, patient and cardiac graft survival rates were similar at 5 years (CHLT 82.1% vs. HA 80.9% [p = 0.73]; CHLT 82.1% vs. HA 80.9% [p = 0.73]). CHLT reduced the incidence of ACR in the cardiac allograft, suggesting that the liver offers immunoprotection against cellular mechanisms of rejection without significant impacts on patient and cardiac graft survival rates. CHLT did not reduce the incidence of de novo DSA, possibly portending similar long‐term survival among cardiac allografts in CHLT and HA.

Background. Pharmacogenetic profiling of transplant recipients demonstrates that the marked variation in the metabolism of immunosuppressive medications, particularly tacrolimus, is related to genetic variants. Patients of African ancestry are less likely to carry loss-of-function (LoF) variants in the CYP3A5 gene and therefore retain a rapid metabolism phenotype and higher clearance of tacrolimus. Patients with this rapid metabolism typically require higher dosing to achieve therapeutic trough concentrations. This study aims to further characterize the impact of CYP3A5 genotype on clinical outcomes and financial expenditure. Methods. The CYP3A5 phenotype status was identified in 438 adult kidney transplant (KTx) recipients (96% were African American) using 3 LoF alleles ( CYP3A5*3 , *6 or *7 ). Individuals were categorized as rapid metabolism phenotype without LoF alleles‚ intermediate phenotype for 1 LoF allele‚ and slow phenotype for 2 LoF alleles. KTx outcomes (patient/kidney survival and Medicare spending) were determined using linked transplant registry and claims data. Results. Among the cohort, 23% had a rapid, 47% intermediate, and 30% a slow metabolism phenotype based on genotype. At 3 y, the rate of death censored graft failure and all cause graft failure was highest in the rapid metabolism phenotype and lowest in the intermediate metabolism phenotype group. First-year Medicare reimbursement differed significantly by genotype (rapid: $79 535, intermediate: $72 796, slow: $79 346, P = 0.03). After adjustment for donor and recipient characteristics, care for patients with intermediate metabolism was $4790 less expensive ( P = 0.003). Conclusions. Pharmacogenomic assessment of African American KTx recipients may be useful to guide therapy when as CYP3A5 functional variants appear to be associated with differential outcome and spending after transplant.