BACKGROUND: MRI-based modeling of tumor cell density (TCD) can significantly improve targeted treatment of Glioblastoma (GBM). Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a Transfer Learning (TL) method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient’s own histologic data. METHODS: We recruited primary GBM patients undergoing image-guided biopsies and preoperative imaging including contrast-enhanced MRI (CE-MRI), Dynamic-Susceptibility-Contrast (DSC)-MRI, and Diffusion Tensor Imaging (DTI). We calculated relative cerebral blood volume (rCBV) from DSC-MRI and mean diffusivity (MD) and fractional anisotropy (FA) from DTI. Following image coregistration, we assessed TCD for each biopsy and identified corresponding localized MRI measurements. We then explored a range of univariate and multivariate predictive models of TCD based on MRI measurements in a generalized one-model-fits-all (OMFA) approach. We then implemented both univariate and multivariate individualized TL predictive models, which harness the available population level data but allow for individual variability in their predictions. Finally, we compared Pearson correlation coefficients and mean absolute error between the individualized TL versus generalized OMFA models. RESULTS: TCD significantly correlated with rCBV (r=0.33,p<0.0001) and T1+C (r=0.36,p<0.0001) on univariate analysis after correcting for multiple comparisons. With single variable modeling (using rCBV), TL increased predictive performance (r=0.53, MAE=15.19%) compared to OMFA (r=0.27, MAE=17.79%). With multivariate modeling, TL further improved performance (r=0.88, MAE 5.66%) compared to OMFA (r=0.39, MAE=16.55%). CONCLUSION: TL significantly improves predictive modeling performance for quantifying tumor cell density in GBM.

Background and Purpose: DSC-MRI using preload, intermediate (60°) flip-angle (α), and post-processing leakage correction (PPLC) has gained traction as standard methodology. Simulations suggest that DSC-MRI with α=30° and no preload yields rCBV practically equivalent to the reference standard. This study tests this hypothesis in vivo. Methods: 84 patients with brain lesions were enrolled in this IRB-approved three-institution study. 43 patients satisfied inclusion criteria. DSC-MRI (3T, single-dose gadobutrol, GRE-EPI, TE=20-35ms, TR=1.2-1.63s) was performed twice for each patient: with α=30-35°, and no preload (P−) provided preload (P+) for intermediate α=60°. Normalized (nRCBV) and standardized (sRCBV) rCBV maps were generated, with (C+) and without (C−) PPLC. Contrast-enhancing lesion volume (CELV), mean rCBV and CNR obtained with 30°/P−/C−, 30°/P−/C+ and 60°/P+/C− were compared to 60°/P+/C+ using Lin’s Concordance Correlation Coefficient (LCCC) and Bland Altman analysis. Equivalence between the 30°/P−/C+ and 60°/P+/C− protocols and the temporal SNR (tSNR) for the 30°/P− and 60°/P+ DSC-MRI data were also determined. Results: Compared to 60°/P+/C+, 30°/P−/C+ had closest mean sRCBV (p=0.6054), highest LCCC (0.96) and lowest Bland-Altman bias (μ=1.89), as compared to 30°/P−/C− (p=0.018, LCCC=0.59, μ=14.6) and 60°/P+/C− (p=0.030, LCCC=0.88, μ=−10.1) with no statistical difference in CNR across protocols. The nRCBV and sRCBV were statistically equivalent at the 10% level using either the 30°/P−/C+ or 60°/P+/C+ protocols. tSNR was not significantly different for 30°/P− and 60°/P+ (p=0.06). Conclusion: Tumor rCBV derived from low-α, no-preload DSC-MRI, with leakage-correction, is an attractive single-dose alternative to the higher-dose reference standard.

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm3 to 62 mm3, even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.

ObjectivesTo assess the outcomes of abdominal dermal‐fat grafting following superficial and total parotidectomy.MethodsA retrospective chart review of parotidectomy patients was performed. Patients were divided into four groups based on surgical extent and grafting status: superficial parotidectomy (SP), superficial parotidectomy with grafting (SPg), total parotidectomy (TP), and total parotidectomy with grafting (TPg). Complication rates and operative times were then compared between surgically matched groups (SP vs. SPg, TP vs. TPg). Complications included graft necrosis, gustatory sweating, first‐bite syndrome, infection, hematoma, sialocele, and seroma. Data was analyzed via chi‐square and two‐sample t testing, logistic regression, and one‐way analysis of variance.ResultsThe cohort consisted of 330 patients: 106 SP (32.12%), 61 SPg (18.48%), 82 TP (24.85%), and 81 TPg (24.55%). No donor site complications occurred. TPg resulted in seven graft necroses (8.64%), and 22 reported gustatory sweating (27.20% vs. 10 TP patients (12.2%), P = 0.016); SPg resulted in two necroses (3.28%). There were no other statistically significant differences in complication rates. Graft recipients receiving adjuvant radiation were more likely to develop necrosis (odds ratio [OR] 4.60, 95% confidence interval [CI], 1.16–18.27, P = .0194). Patients who developed gustatory sweating were 8.38 years younger (95% CI 2.66–14.10, P = 0.002, follow‐up time > 48 days). Grafting did not increase operative times (TP/TPg: mean = 275.91/263.65 minutes, standard error of the mean = 41.96/33.75, P = 0.822).ConclusionAn abdominal dermal‐fat graft is an excellent reconstructive choice for a parotidectomy defect and is not associated with increased complication rates or prolonged operative time.Level of Evidence4 Laryngoscope, 130:2144–2147, 2020

Objectives/Hypothesis Use validated eye‐tracking technology to objectively measure 1) the attentional distraction of facial contour defects after superficial and total parotidectomy and 2) changes in attentional distraction with abdominal dermal fat graft reconstruction. Methods Standardized frontal and oblique facial images of 16 patients who had undergone superficial or total parotidectomy with or without fat graft reconstruction; four normal controls were obtained. One hundred casual observers were recruited to view these images, and gaze data were collected using a Tobii Pro eye‐tracking system. Gaze durations for predefined facial areas of interest were analyzed using mixed‐effects linear regression to test study hypotheses. Results For frontal images, total parotidectomy increased gaze to the operated parotid area compared to the contralateral nonoperated parotid area (92 milliseconds, 95% confidence interval [CI]: 48‐138 milliseconds, P < .001). Fat grafting normalized the attentional distraction, with no difference in gaze time on the operated parotid region compared to normal control faces (P = .414). For oblique images, total parotidectomy increased gaze to the operated parotid area compared to the contralateral nonoperated parotid area (658 milliseconds, 95% CI: 463‐854 milliseconds, P < .001). Fat grafting normalized this attentional distraction, with no difference in gaze time on the operated parotid region compared to normal control faces (P = .504). In both views, superficial parotidectomy demonstrated no significant attentional distractions, with or without fat grafting. Conclusions This eye‐tracking study objectively demonstrates that total parotidectomy results in a facial contour deformity that is distracting to observers, whereas superficial parotidectomy does not. For total parotidectomy, this attentional distraction can be normalized with dermal fat graft reconstruction. Level of Evidence 3b Laryngoscope, 131:E124–E131, 2021