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Background: Treatment of nasal tumors in dogs is associated with high morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion., Objectives: To assess perfusion parameters of nasal tumors (correlating with tumor type) before and during radiotherapy (RT) and find potential correlation with survival., Animals: Twenty-four client-owned dogs with nasal tumors, including 16 epithelial tumors and 8 sarcomas., Methods: Prospective cross-sectional study. All dogs had baseline DCECT to assess fractional vascular volume (BV), blood flow (BF), and transit time (TT). Thirteen dogs had repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated., Results: Median BV was 17.83 mL/100 g (range, 3.63-66.02), median BF was 122.63 mL/100 g/minute (range, 23.65-279.99), and median TT was 8.91 seconds (range, 4.57-14.23). Sarcomas had a significantly lower BF than adenocarcinomas (P = .002), carcinomas (P = .01), and other carcinomas (P = .001), and significantly lower BV than adenocarcinomas (P = .03) and other carcinomas (P = .004). Significant associations were found between epithelial tumors and sarcoma for change in tumor volume (P = .01), width (P = .004), and length (P = .02) in that epithelial tumors decreased in volume whereas sarcomas increased in volume. Perfusion parameters were not correlated with survival., Conclusions and Clinical Importance: Nasal sarcomas have lower BV and BF than nasal carcinomas, and sarcomas have a lower size reduction than carcinomas early on during RT. Baseline results and changes in perfusion parameters may not be correlated with survival., (© 2023 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.) more...

Introduction: Treatment of brain tumors in dogs can be associated with significant morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to assess perfusion parameters and change in size of suspected brain tumors before and during radiotherapy (RT) depending on their location and find a potential correlation with survival., Methods: Seventeen client-owned dogs with suspected brain tumors were prospectively recruited. All dogs had a baseline DCECT to assess mass size, blood volume (BV), blood flow (BF), and transit time (TT). Twelve dogs had a repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated., Results: Intra-axial masses had lower BF ( p  = 0.005) and BV ( p  < 0.001) than extra-axial masses but not than pituitary masses. Pituitary masses had lower BF ( p  = 0.001) and BV ( p  = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT ( p  = 0.001) but not with BF and BV. Intra-axial masses showed a more marked decrease in size than extra-axial and pituitary masses during RT ( p  = 0.022 for length, p  = 0.05 for height). Extra-axial masses showed a greater decrease in BF ( p  = 0.011) and BV ( p  = 0.012) during RT than pituitary masses and intra-axial masses. Heavier dogs had a shorter survival time ( p  = 0.011). Perfusion parameters were not correlated with survival., Conclusion: DCECT perfusion parameters and change in size of brain masses during RT might be different based on the location of the mass., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Mortier, Maddox, Blackwood, La Fontaine and Busoni.) more...

Objective: Treatment of orofacial tumors in dogs is associated with high morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to describe the perfusion parameters of different types of orofacial tumors and to describe the changes in perfusion parameters during radiotherapy (RT) in a subset of them., Animals: 11 dogs with orofacial tumors prospectively recruited., Clinical Presentation and Procedures: All dogs had baseline DCECT to assess blood volume (BV), blood flow (BF), and transit time (TT). Five dogs had repeat DCECT during megavoltage RT., Results: 5 squamous cell carcinomas, 3 sarcomas, 1 melanoma, 1 histiocytic sarcoma, and 1 acanthomatous ameloblastoma were included. Blood volume and BF were higher in squamous cell carcinomas than in sarcomas, although no statistical analysis was performed. At repeat DCECT, 4 dogs showed a reduction in the size of their tumor during RT. Among these dogs, 3 showed an increase in BV and BF and 1 a decrease in these parameters between the baseline and the follow-up DCECT. The only dog whose tumor increased in size between the first and the second DCECT showed a decrease in BV and BF., Clinical Relevance: Perfusion parameters derived from DCECT were described in a series of dogs with various types of orofacial tumors. The results suggest that epithelial tumors could have higher BV and BF than mesenchymal tumors, although larger sample sizes are needed to support these preliminary findings. more...

In locally advanced lung cancer, established baseline clinical variables show limited prognostic accuracy and 18F-fluorodeoxyglucose positron emission tomography (FDG PET) radiomics features may increase accuracy for optimal treatment selection. Their robustness and added value relative to current clinical factors are unknown. Hence, we identify robust and independent PET radiomics features that may have complementary value in predicting survival endpoints. A 4D PET dataset (n = 70) was used for assessing the repeatability (Bland-Altman analysis) and independence of PET radiomics features (Spearman rank: |ρ|<0.5). Two 3D PET datasets combined (n = 252) were used for training and validation of an elastic net regularized generalized logistic regression model (GLM) based on a selection of clinical and robust independent PET radiomics features (GLMall). The fitted model performance was externally validated (n = 40). The performance of GLMall (measured with area under the receiver operating characteristic curve, AUC) was highest in predicting 2-year overall survival (0.66±0.07). No significant improvement was observed for GLMall compared to a model containing only PET radiomics features or only clinical variables for any clinical endpoint. External validation of GLMall led to AUC values no higher than 0.55 for any clinical endpoint. In this study, robust independent FDG PET radiomics features did not have complementary value in predicting survival endpoints in lung cancer patients. Improving risk stratification and clinical decision making based on clinical variables and PET radiomics features has still been proven difficult in locally advanced lung cancer patients., Competing Interests: The authors have declared that no competing interests exist. more...

Background and Purpose: We aimed to identify tumour subregions with characteristic phenotypes based on pre-treatment multi-parametric functional imaging and correlate these subregions to treatment outcome. The subregions were created using imaging of metabolic activity (FDG-PET/CT), hypoxia (HX4-PET/CT) and tumour vasculature (DCE-CT)., Materials and Methods: 36 non-small cell lung cancer (NSCLC) patients underwent functional imaging prior to radical radiotherapy. Kinetic analysis was performed on DCE-CT scans to acquire blood flow (BF) and volume (BV) maps. HX4-PET/CT and DCE-CT scans were non-rigidly co-registered to the planning FDG-PET/CT. Two clustering steps were performed on multi-parametric images: first to segment each tumour into homogeneous subregions (i.e. supervoxels) and second to group the supervoxels of all tumours into phenotypic clusters. Patients were split based on the absolute or relative volume of supervoxels in each cluster; overall survival was compared using a log-rank test., Results: Unsupervised clustering of supervoxels yielded four independent clusters. One cluster (high hypoxia, high FDG, intermediate BF/BV) related to a high-risk tumour type: patients assigned to this cluster had significantly worse survival compared to patients not in this cluster (p = 0.035)., Conclusions: We designed a subregional analysis for multi-parametric imaging in NSCLC, and showed the potential of subregion classification as a biomarker for prognosis. This methodology allows for a comprehensive data-driven analysis of multi-parametric functional images., (Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.) more...