Whole-Slide Cytometric Feature Mapping for Distinguishing Tumor Genomic Subtypes in Head and Neck Squamous Cell Carcinoma Whole-Slide Images.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease where, in advanced stages, clinical and pathologic stages do not correlate with outcome. Molecular and genomic biomarkers for HNSCC classification have shown promise for prognostic and therapeutic applications. This study utilized 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, along with accompanying clinical, pathologic, 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. Thirty-two features demonstrated significant association with integrated genomic subtype 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.

Automated Nuclear Segmentation in Head and Neck Squamous Cell Carcinoma Pathology Reveals Relationships between Cytometric Features and ESTIMATE Stromal and Immune Scores.

The tumor microenvironment (TME) plays an important role in the progression of head and neck squamous cell carcinoma (HNSCC). Currently, pathologic assessment of TME is nonstandardized and subject to observer bias. Genome-wide transcriptomic approaches to understanding the TME, while less subject to bias, are expensive and not currently a part of the standard of care for HNSCC. To identify pathology-based biomarkers that correlate with genomic and transcriptomic signatures of TME in HNSCC, cytometric feature maps were generated in a publicly available data set from a cohort of patients with HNSCC, including whole-slide tissue images and genomic and transcriptomic phenotyping (N = 49). Cytometric feature maps were generated based on whole-slide nuclear detection, using a deep-learning algorithm trained for StarDist nuclear segmentation. Cytometric features in each patient were compared to transcriptomic measurements, including Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) scores and stemness scores. With correction for multiple comparisons, one feature (nuclear circularity) demonstrated a significant linear correlation with ESTIMATE stromal score. Two features (nuclear maximum and minimum diameter) correlated significantly with ESTIMATE immune score. Three features (nuclear solidity, nuclear minimum diameter, and nuclear circularity) correlated significantly with transcriptomic stemness score. This study provides preliminary evidence that observer-independent, automated tissue-slide analysis can provide insights into the HNSCC TME which correlate with genomic and transcriptomic assessments.

MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma.

Purpose: To identify significant relationships between quantitative cytometric tissue features and quantitative MR (qMRI) intratumorally in preclinical undifferentiated pleomorphic sarcomas (UPS). Materials and methods: In a prospective study of genetically engineered mouse models of UPS, we registered imaging libraries consisting of matched multi-contrast in vivo MRI, three-dimensional (3D) multi-contrast high-resolution ex vivo MR histology (MRH), and two-dimensional (2D) tissue slides. From digitized histology we generated quantitative cytometric feature maps from whole-slide automated nuclear segmentation. We automatically segmented intratumoral regions of distinct qMRI values and measured corresponding cytometric features. Linear regression analysis was performed to compare intratumoral qMRI and tissue cytometric features, and results were corrected for multiple comparisons. Linear correlations between qMRI and cytometric features with p values of <0.05 after correction for multiple comparisons were considered significant. Results: Three features correlated with ex vivo apparent diffusion coefficient (ADC), and no features correlated with in vivo ADC. Six features demonstrated significant linear relationships with ex vivo T2*, and fifteen features correlated significantly with in vivo T2*. In both cases, nuclear Haralick texture features were the most prevalent type of feature correlated with T2*. A small group of nuclear topology features also correlated with one or both T2* contrasts, and positive trends were seen between T2* and nuclear size metrics. Conclusion: Registered multi-parametric imaging datasets can identify quantitative tissue features which contribute to UPS MR signal. T2* may provide quantitative information about nuclear morphology and pleomorphism, adding histological insights to radiological interpretation of UPS.

An Online Repository for Pre-Clinical Imaging Protocols (PIPs).

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.

Cytostatic hypothermia and its impact on glioblastoma and survival.

Patients with glioblastoma (GBM) have limited options and require novel approaches to treatment. Here, we studied and deployed nonfreezing "cytostatic" hypothermia to stunt GBM growth. This growth-halting method contrasts with ablative, cryogenic hypothermia that kills both neoplastic and infiltrated healthy tissue. We investigated degrees of hypothermia in vitro and identified a cytostatic window of 20° to 25°C. For some lines, 18 hours/day of cytostatic hypothermia was sufficient to halt division in vitro. Next, we fabricated an experimental tool to test local cytostatic hypothermia in two rodent GBM models. Hypothermia more than doubled median survival, and all rats that successfully received cytostatic hypothermia survived their study period. Unlike targeted therapeutics that are successful in preclinical models but fail in clinical trials, cytostatic hypothermia leverages fundamental physics that influences biology broadly. It is a previously unexplored approach that could provide an additional option to patients with GBM by halting tumor growth.

Late onset cardiovascular dysfunction in adult mice resulting from galactic cosmic ray exposure.

The complex and inaccessible space radiation environment poses an unresolved risk to astronaut cardiovascular health during long-term space exploration missions. To model this risk, healthy male c57BL/6 mice aged six months (corresponding to an astronaut of 34 years) were exposed to simplified galactic cosmic ray (GCR5-ion; 5-ion sim) irradiation at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratories (BNL). Multi-modal cardiovascular functional assessments performed longitudinally and terminally revealed significant impairment in cardiac function in mice exposed to GCR5-ion compared to unirradiated controls, gamma irradiation, or single mono-energetic ions (56Fe or 16O). GCR5-ion-treated mice exhibited increased arterial elastance likely mediated by disruption of elastin fibers. This study suggests that a single exposure to GCR5-ion is associated with deterioration in cardiac structure and function that becomes apparent long after exposure, likely associated with increased morbidity and mortality. These findings represent important health considerations when preparing for successful space exploration.

Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas.

Purpose 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.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.

The 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.

Imaging of Nanoparticle Distribution to Assess Treatments That Alter Delivery.

Molecular imaging is a vital tool to non-invasively measure nanoparticle delivery to solid tumors. Despite the myriad of nanoparticles studied for cancer, successful applications of nanoparticles in humans is limited by inconsistent and ineffective delivery. Successful nanoparticle delivery in preclinical models is often attributed to enhanced permeability and retention (EPR)-a set of conditions that is heterogeneous and transient in patients. Thus, researchers are evaluating therapeutic strategies to modify nanoparticle delivery, particularly treatments which have demonstrated effects on EPR conditions. Imaging nanoparticle distribution provides a means to measure the effects of therapeutic intervention on nanoparticle delivery to solid tumors. This review focuses on the utility of imaging to measure treatment-induced changes in nanoparticle delivery to tumors and provides preclinical examples studying a broad range of therapeutic interventions.

Liposomal 64Cu-PET Imaging of Anti-VEGF Drug Effects on Liposomal Delivery to Colon Cancer Xenografts.

Liposomes (LP) deliver drug to tumors due to enhanced permeability and retention (EPR). LP were labeled with 64Cu for positron emission tomography (PET) to image tumor localization. Bevacizumab (bev), a VEGF targeted antibody, may modify LP delivery by altering tumor EPR and this change can also be imaged. Objective: Assess the utility of 64Cu-labeled LP for PET in measuring altered LP delivery early after treatment with bev. Methods: HT-29 human colorectal adenocarcinoma tumors were grown subcutaneously in SCID mice. Empty LP MM-DX-929 (Merrimack Pharmaceuticals, Inc. Cambridge, MA) were labeled with 64CuCl2 chelated with 4-DEAP-ATSC. Tumor-bearing mice received ~200-300 µCi of 64Cu-MM-DX-929 and imaged with microPET. All mice were scanned before and after the treatment period, in which half of the mice received bev for one week. Scans were compared for changes in LP accumulation during this time. Initially, tissues were collected after the second PET for biodistribution measurements and histological analysis. Subsequent groups were divided for further treatment. Tumor growth following bev treatment, with or without LP-I, was assessed compared to untreated controls. Results: PET scans of untreated mice showed increased uptake of 64Cu-MM-DX-929, with a mean change in tumor SUVmax of 43.9%±6.6% (n=10) after 7 days. Conversely, images of treated mice showed that liposome delivery did not increase, with changes in SUVmax of 7.6%±4.8% (n=12). Changes in tumor SUVmax were significantly different between both groups (p=0.0003). Histology of tumor tissues indicated that short-term bev was able to alter vessel size. Therapeutically, while bev monotherapy, LP-I monotherapy, and treatment with bev followed by LP-I all slowed HT-29 tumor growth compared to controls, combination provided no therapeutic benefit. Conclusions: PET with tracer LP 64Cu-MM-DX-929 can detect significant differences in LP delivery to colon tumors treated with bev when compared to untreated controls. Imaging with 64Cu-MM-DX-929 is sensitive enough to measure drug-induced changes in LP localization which can have an effect on outcomes of treatment with LP.

64Cu-MM-302 Positron Emission Tomography Quantifies Variability of Enhanced Permeability and Retention of Nanoparticles in Relation to Treatment Response in Patients with Metastatic Breast Cancer.

Purpose: Therapeutic nanoparticles are designed to deliver their drug payloads through enhanced permeability and retention (EPR) in solid tumors. The extent of EPR and its variability in human tumors is highly debated and has been proposed as an explanation for variable responses to therapeutic nanoparticles in clinical studies.Experimental Design: We assessed the EPR effect in patients using a 64Cu-labeled nanoparticle, 64Cu-MM-302 (64Cu-labeled HER2-targeted PEGylated liposomal doxorubicin), and imaging by PET/CT. Nineteen patients with HER2-positive metastatic breast cancer underwent 2 to 3 PET/CT scans postadministration of 64Cu-MM-302 as part of a clinical trial of MM-302 plus trastuzumab with and without cyclophosphamide (NCT01304797).Results: Significant background uptake of 64Cu-MM-302 was observed in liver and spleen. Tumor accumulation of 64Cu-MM-302 at 24 to 48 hours varied 35-fold (0.52-18.5 %ID/kg), including deposition in bone and brain lesions, and was independent of systemic plasma exposure. Computational analysis quantified rates of deposition and washout, indicating peak liposome deposition at 24 to 48 hours. Patients were classified on the basis of 64Cu-MM-302 lesion deposition using a cut-off point that is comparable with a response threshold in preclinical studies. In a retrospective exploratory analysis of patient outcomes relating to drug levels in tumor lesions, high 64Cu-MM-302 deposition was associated with more favorable treatment outcomes (HR = 0.42).Conclusions: These findings provide important evidence and quantification of the EPR effect in human metastatic tumors and support imaging nanoparticle deposition in tumors as a potential means to identify patients well suited for treatment with therapeutic nanoparticles. Clin Cancer Res; 23(15); 4190-202. ©2017 AACR.