Plasencia, Jonathan D.

Abstract Background Listed pediatric heart transplant patients have the highest solid‐organ waitlist mortality rate. The donor‐recipient body weight ( DRBW ) ratio is the clinical standard for allograft size matching but may unnecessarily limit a patient's donor pool. To overcome DRBW ratio limitations, two methods of performing virtual heart transplant fit assessments were developed that account for patient‐specific nuances. Method 1 uses an allograft total cardiac volume ( TCV ) prediction model informed by patient data wherein a matched allograft 3‐D reconstruction is selected from a virtual library for assessment. Method 2 uses donor images for a direct virtual transplant assessment. Methods Assessments were performed in medical image reconstruction software. The allograft model was developed using allometric/isometric scaling assumptions and cross‐validation. Results The final predictive model included gender, height, and weight. The 25th‐, 50th‐, and 75th‐percentiles for TCV percentage errors were −13% (over‐prediction), −1%, and 8% (under‐prediction), respectively. Two examples illustrating the potential of virtual assessments are presented. Conclusion Transplant centers can apply these methods to perform their virtual assessments using existing technology. These techniques have potential to improve organ allocation. With additional experience and refinement, virtual transplants may become standard of care for determining suitability of donor organ size for an identified recipient.

AbstractBackgroundGlioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments.MethodsWe collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV).ResultsWe collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32).ConclusionMRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.

Mechanical circulatory support emerged for the pediatric population in the late 1980s as a bridge to cardiac transplantation. The Total Artificial Heart (TAH-t) (SynCardia Systems Inc., Tuscon, AZ) has been approved for compassionate use by the Food and Drug Administration for patients with end-stage biventricular heart failure as a bridge to heart transplantation since 1985 and has had FDA approval since 2004. However, of the 1,061 patients placed on the TAH-t, only 21 (2%) were under the age 18. SynCardia Systems, Inc. recommends a minimum patient body surface area (BSA) of 1.7 m 2 , thus, limiting pediatric application of this device. This unique case report shares this pediatric institution’s first experience with the TAH-t. A 14-year-old male was admitted with dilated cardiomyopathy and severe biventricular heart failure. The patient rapidly decompensated, requiring extracorporeal life support. An echocardiogram revealed severe biventricular dysfunction and diffuse clot formation in the left ventricle and outflow tract. The decision was made to transition to biventricular assist device. The biventricular failure and clot formation helped guide the team to the TAH-t, in spite of a BSA (1.5 m 2 ) below the recommendation of 1.7m 2 . A computed tomography (CT) scan of the thorax, in conjunction with a novel three-dimensional (3D) modeling system and team, assisted in determining appropriate fit. Chest CT and 3D modeling following implantation were utilized to determine all major vascular structures were unobstructed and the bronchi were open. The virtual 3D model confirmed appropriate device fit with no evidence of compression to the left pulmonary veins. The postoperative course was complicated by a left lung opacification. The left lung anomalies proved to be atelectasis and improved with aggressive recruitment maneuvers. The patient was supported for 11 days prior to transplantation. Chest CT and 3D modeling were crucial in assessing whether the device would fit, as well as postoperative complications in this smaller pediatric patient.