Browsing by Author "Mowery, Yvonne M"
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Item Open Access Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials(Tomography) Peehl, Donna M; Badea, Cristian T; Chenevert, Thomas L; Daldrup-Link, Heike E; Ding, Li; Dobrolecki, Lacey E; Houghton, A McGarry; Kinahan, Paul E; Kurhanewicz, John; Lewis, Michael T; Li, Shunqiang; Luker, Gary D; Ma, Cynthia X; Manning, H Charles; Mowery, Yvonne M; O'Dwyer, Peter J; Pautler, Robia G; Rosen, Mark A; Roudi, Raheleh; Ross, Brian D; Shoghi, Kooresh I; Sriram, Renuka; Talpaz, Moshe; Wahl, Richard L; Zhou, RongThe availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients’ tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.Item Open Access Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.(Tomography (Ann Arbor, Mich.), 2020-09) Shoghi, Kooresh I; Badea, Cristian T; Blocker, Stephanie J; Chenevert, Thomas L; Laforest, Richard; Lewis, Michael T; Luker, Gary D; Manning, H Charles; Marcus, Daniel S; Mowery, Yvonne M; Pickup, Stephen; Richmond, Ann; Ross, Brian D; Vilgelm, Anna E; Yankeelov, Thomas E; Zhou, RongThe National Institutes of Health's (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.Item Open Access Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning(Tomography) Holbrook, Matthew D; Clark, Darin P; Patel, Rutulkumar; Qi, Yi; Bassil, Alex M; Mowery, Yvonne M; Badea, Cristian TWe are developing imaging methods for a co-clinical trial investigating synergy between immunotherapy and radiotherapy. We perform longitudinal micro-computed tomography (micro-CT) of mice to detect lung metastasis after treatment. This work explores deep learning (DL) as a fast approach for automated lung nodule detection. We used data from control mice both with and without primary lung tumors. To augment the number of training sets, we have simulated data using real augmented tumors inserted into micro-CT scans. We employed a convolutional neural network (CNN), trained with four competing types of training data: (1) simulated only, (2) real only, (3) simulated and real, and (4) pretraining on simulated followed with real data. We evaluated our model performance using precision and recall curves, as well as receiver operating curves (ROC) and their area under the curve (AUC). The AUC appears to be almost identical (0.76–0.77) for all four cases. However, the combination of real and synthetic data was shown to improve precision by 8%. Smaller tumors have lower rates of detection than larger ones, with networks trained on real data showing better performance. Our work suggests that DL is a promising approach for fast and relatively accurate detection of lung tumors in mice.Item Open Access Early 18F-FDG-PET Response During Radiation Therapy for HPV-Related Oropharyngeal Cancer May Predict Disease Recurrence.(International journal of radiation oncology, biology, physics, 2020-11) Mowery, Yvonne M; Vergalasova, Irina; Rushing, Christel N; Choudhury, Kingshuk Roy; Niedzwiecki, Donna; Wu, Qiuwen; Yoo, David S; Das, Shiva; Wong, Terence Z; Brizel, David MPurpose
Early indication of treatment outcome may guide therapeutic de-escalation strategies in patients with human papillomavirus (HPV)-related oropharyngeal cancer (OPC). This study investigated the relationships between tumor volume and 18F-fluorodeoxyglucose positron emission tomography (PET) parameters before and during definitive radiation therapy with treatment outcomes.Methods and materials
Patients undergoing definitive (chemo)radiation for HPV-related/p16-positive OPC were prospectively enrolled on an institutional review board-approved study. 18F-fluorodeoxyglucose PET/computed tomography scans were performed at simulation and after 2 weeks at a dose of ∼20 Gy. Tumor volume and standardized uptake value (SUV) characteristics were measured. SUV was normalized to blood pool uptake. Tumor volume and PET parameters associated with recurrence were identified through recursive partitioning (RPART). Recurrence-free survival (RFS) and overall survival (OS) curves between RPART-identified cohorts were estimated using the Kaplan-Meier method, and Cox models were used to estimate the hazard ratios (HRs).Results
From 2012 to 2016, 62 patients with HPV-related OPC were enrolled. Median follow-up was 4.4 years. RPART identified patients with intratreatment SUVmax (normalized to blood pool SUVmean) <6.7 or SUVmax (normalized to blood pool SUVmean) ≥6.7 with intratreatment SUV40% ≥2.75 as less likely to recur. For identified subgroups, results of Cox models showed unadjusted HRs for RFS and OS (more likely to recur vs less likely) of 7.33 (90% confidence interval [CI], 2.97-18.12) and 6.09 (90% CI, 2.22-16.71), respectively, and adjusted HRs of 6.57 (90% CI, 2.53-17.05) and 5.61 (90% CI, 1.90-16.54) for RFS and OS, respectively.Conclusions
PET parameters after 2 weeks of definitive radiation therapy for HPV-related OPC are associated with RFS and OS, thus potentially informing an adaptive treatment approach.Item Open Access Enhancing in vivo preclinical studies with VivoVist™ and photon-counting micro-CT imaging(Medical Imaging 2024: Clinical and Biomedical Imaging, 2024-04-02) Badea, Cristian T; Rickard, Ashlyn; Allphin, Alex; Clark, Darin P; Ghaghada, Ketan B; Ridwan, S; Smilowitz, Henry M; Hainfeld, James; Mowery, Yvonne MItem Open Access Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas.(Radiology. Imaging cancer, 2021-05) Blocker, Stephanie J; Cook, James; Mowery, Yvonne M; Everitt, Jeffrey I; Qi, Yi; Hornburg, Kathryn J; Cofer, Gary P; Zapata, Fernando; Bassil, Alex M; Badea, Cristian T; Kirsch, David G; Johnson, G AllanPurpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R2 values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R2 = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R2 = 0.99, P < .001) and variance in nuclear circularity (best line fit: R2 = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.Item Open Access Neoadjuvant Radiation Therapy and Surgery Improves Metastasis-Free Survival over Surgery Alone in a Primary Mouse Model of Soft Tissue Sarcoma.(Molecular cancer therapeutics, 2023-01) Patel, Rutulkumar; Mowery, Yvonne M; Qi, Yi; Bassil, Alex M; Holbrook, Matt; Xu, Eric S; Hong, Cierra S; Himes, Jonathon E; Williams, Nerissa T; Everitt, Jeffrey; Ma, Yan; Luo, Lixia; Selitsky, Sara R; Modliszewski, Jennifer L; Gao, Junheng; Jung, Sin-Ho; Kirsch, David G; Badea, Cristian TThis study aims to investigate whether adding neoadjuvant radiotherapy (RT), anti-programmed cell death protein-1 (PD-1) antibody (anti-PD-1), or RT + anti-PD-1 to surgical resection improves disease-free survival for mice with soft tissue sarcomas (STS). We generated a high mutational load primary mouse model of STS by intramuscular injection of adenovirus expressing Cas9 and guide RNA targeting Trp53 and intramuscular injection of 3-methylcholanthrene (MCA) into the gastrocnemius muscle of wild-type mice (p53/MCA model). We randomized tumor-bearing mice to receive isotype control or anti-PD-1 antibody with or without radiotherapy (20 Gy), followed by hind limb amputation. We used micro-CT to detect lung metastases with high spatial resolution, which was confirmed by histology. We investigated whether sarcoma metastasis was regulated by immunosurveillance by lymphocytes or tumor cell-intrinsic mechanisms. Compared with surgery with isotype control antibody, the combination of anti-PD-1, radiotherapy, and surgery improved local recurrence-free survival (P = 0.035) and disease-free survival (P = 0.005), but not metastasis-free survival. Mice treated with radiotherapy, but not anti-PD-1, showed significantly improved local recurrence-free survival and metastasis-free survival over surgery alone (P = 0.043 and P = 0.007, respectively). The overall metastasis rate was low (∼12%) in the p53/MCA sarcoma model, which limited the power to detect further improvement in metastasis-free survival with addition of anti-PD-1 therapy. Tail vein injections of sarcoma cells into immunocompetent mice suggested that impaired metastasis was due to inability of sarcoma cells to grow in the lungs rather than a consequence of immunosurveillance. In conclusion, neoadjuvant radiotherapy improves metastasis-free survival after surgery in a primary model of STS.Item Open Access Neoadjuvant Radiation Therapy and Surgery Improves Metastasis-Free Survival over Surgery Alone in a Primary Mouse Model of Soft Tissue Sarcoma.(Molecular cancer therapeutics, 2023-01) Patel, Rutulkumar; Mowery, Yvonne M; Qi, Yi; Bassil, Alex M; Holbrook, Matt; Xu, Eric S; Hong, Cierra S; Himes, Jonathon E; Williams, Nerissa T; Everitt, Jeffrey; Ma, Yan; Luo, Lixia; Selitsky, Sara R; Modliszewski, Jennifer L; Gao, Junheng; Jung, Sin-Ho; Kirsch, David G; Badea, Cristian TThis study aims to investigate whether adding neoadjuvant radiotherapy (RT), anti-programmed cell death protein-1 (PD-1) antibody (anti-PD-1), or RT + anti-PD-1 to surgical resection improves disease-free survival for mice with soft tissue sarcomas (STS). We generated a high mutational load primary mouse model of STS by intramuscular injection of adenovirus expressing Cas9 and guide RNA targeting Trp53 and intramuscular injection of 3-methylcholanthrene (MCA) into the gastrocnemius muscle of wild-type mice (p53/MCA model). We randomized tumor-bearing mice to receive isotype control or anti-PD-1 antibody with or without radiotherapy (20 Gy), followed by hind limb amputation. We used micro-CT to detect lung metastases with high spatial resolution, which was confirmed by histology. We investigated whether sarcoma metastasis was regulated by immunosurveillance by lymphocytes or tumor cell-intrinsic mechanisms. Compared with surgery with isotype control antibody, the combination of anti-PD-1, radiotherapy, and surgery improved local recurrence-free survival (P = 0.035) and disease-free survival (P = 0.005), but not metastasis-free survival. Mice treated with radiotherapy, but not anti-PD-1, showed significantly improved local recurrence-free survival and metastasis-free survival over surgery alone (P = 0.043 and P = 0.007, respectively). The overall metastasis rate was low (∼12%) in the p53/MCA sarcoma model, which limited the power to detect further improvement in metastasis-free survival with addition of anti-PD-1 therapy. Tail vein injections of sarcoma cells into immunocompetent mice suggested that impaired metastasis was due to inability of sarcoma cells to grow in the lungs rather than a consequence of immunosurveillance. In conclusion, neoadjuvant radiotherapy improves metastasis-free survival after surgery in a primary model of STS.Item Open Access Photon Counting CT and Radiomic Analysis Enables Differentiation of Tumors Based on Lymphocyte Burden(Tomography) Allphin, Alex J; Mowery, Yvonne M; Lafata, Kyle J; Clark, Darin P; Bassil, Alex M; Castillo, Rico; Odhiambo, Diana; Holbrook, Matthew D; Ghaghada, Ketan B; Badea, Cristian TThe purpose of this study was to investigate if radiomic analysis based on spectral micro-CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden. High mutational load transplant soft tissue sarcomas were initiated in Rag2+/− and Rag2−/− mice to model varying lymphocyte burden. Mice received radiation therapy (20 Gy) to the tumor-bearing hind limb and were injected with a liposomal iodinated contrast agent. Five days later, animals underwent conventional micro-CT imaging using an energy integrating detector (EID) and spectral micro-CT imaging using a photon-counting detector (PCD). Tumor volumes and iodine uptakes were measured. The radiomic features (RF) were grouped into feature-spaces corresponding to EID, PCD, and spectral decomposition images. The RFs were ranked to reduce redundancy and increase relevance based on TL burden. A stratified repeated cross validation strategy was used to assess separation using a logistic regression classifier. Tumor iodine concentration was the only significantly different conventional tumor metric between Rag2+/− (TLs present) and Rag2−/− (TL-deficient) tumors. The RFs further enabled differentiation between Rag2+/− and Rag2−/− tumors. The PCD-derived RFs provided the highest accuracy (0.68) followed by decomposition-derived RFs (0.60) and the EID-derived RFs (0.58). Such non-invasive approaches could aid in tumor stratification for cancer therapy studies.Item Open Access Whole-slide cytometric feature mapping for distinguishing tumor genomic subtypes in HNSCC whole slide images.(The American journal of pathology, 2022-11) Blocker, Stephanie J; Morrison, Samantha; Everitt, Jeffrey I; Cook, James; Luo, Sheng; Watts, Tammara L; Mowery, Yvonne MHead and neck squamous cell carcinoma (HNSCC) is a heterogenous disease where, in advanced stages, clinical and pathological stages do not correlate with outcome. Molecular and genomic biomarkers for HNSCC classification have shown promise for prognostic and therapeutic applications. In this study, we utilize automated image analysis techniques in whole slide images of HNSCC tumors to identify relationships between cytometric features and genomic phenotypes. Hematoxylin and eosin-stained slides of HNSCC tumors (N=49) were obtained from the Cancer Imaging Archive (TCIA), along with accompanying clinical, pathological, genomic, and proteomic reports. Automated nuclear detection was performed across the entirety of slides, and cytometric feature maps were generated. Forty-one cytometric features were evaluated for associations with tumor grade, tumor stage, tumor subsite, and integrated genomic subtype (IGS). Thirty-two features demonstrated significant association with IGS when corrected for multiple comparisons. In particular, the basal subtype was visually distinguishable from the chromosomal instability and immune subtypes based on cytometric feature measurements. No features were significantly associated with tumor grade, stage, or subsite. This study provides preliminary evidence that features derived from tissue pathology slides could provide insights into genomic phenotypes of HNSCC.