Quantitative MRI reveals heterogeneous impacts of treatment on diseased bone marrow in a mouse model of myelofibrosis.

PURPOSE: Analyzing bone marrow in the hematologic cancer myelofibrosis requires endpoint histology in mouse models and bone marrow biopsies in patients. These methods hinder the ability to monitor therapy over time. Preclinical studies typically begin treatment before mice develop myelofibrosis, unlike patients who begin therapy only after onset of disease. Using clinically relevant, quantitative MRI metrics allowed us to evaluate treatment in mice with established myelofibrosis. METHODS: We used chemical shift-encoded fat imaging, DWI, and magnetization transfer sequences to quantify bone marrow fat, cellularity, and macromolecular components in a mouse model of myelofibrosis. We monitored spleen volume, the established imaging marker for treatment, with anatomic MRI. After confirming bone marrow disease by MRI, we randomized mice to treatment with an approved drug (ruxolitinib or fedratinib) or an investigational agent, navitoclax, for 33 days. We measured the effects of therapy over time with bone marrow and spleen MRI. RESULTS: All treatments produced heterogeneous responses with improvements in bone marrow evident in subsets of individual mice in all treatment groups. Reductions in spleen volume commonly occurred without corresponding improvement in bone marrow. MRI revealed patterns associated with effective and ineffective responses to treatment in bone marrow and identified regional variations in efficacy within a bone. CONCLUSIONS: Quantitative MRI revealed modest, heterogeneous improvements in bone marrow disease when treating mice with established myelofibrosis. These results emphasize the value of bone marrow MRI to assess treatment in preclinical models and the potential to advance clinical trials for patients.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model.

Quantitative MRI biomarkers are sought to replace painful and invasive sequential bone-marrow biopsies routinely used for myelofibrosis (MF) cancer monitoring and treatment assessment. Repeatability of MRI-based quantitative imaging biomarker (QIB) measurements was investigated for apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), and magnetization transfer ratio (MTR) in a JAK2 V617F hematopoietic transplant model of MF. Repeatability coefficients (RCs) were determined for three defined tibia bone-marrow sections (2-9 mm; 10-12 mm; and 12.5-13.5 mm from the knee joint) across 15 diseased mice from 20-37 test-retest pairs. Scans were performed on consecutive days every two weeks for a period of 10 weeks starting 3-4 weeks after transplant. The mean RC with (95% confidence interval (CI)) for these sections, respectively, were for ADC: 0.037 (0.031, 0.050), 0.087 (0.069, 0.116), and 0.030 (0.022, 0.044) µm2/ms; for PDFF: 1.6 (1.3, 2.0), 15.5 (12.5, 20.2), and 25.5 (12.0, 33.0)%; and for MTR: 0.16 (0.14, 0.19), 0.11 (0.09, 0.15), and 0.09 (0.08, 0.15). Change-trend analysis of these QIBs identified a dynamic section within the mid-tibial bone marrow in which confident changes (exceeding RC) could be observed after a four-week interval between scans across all measured MRI-based QIBs. Our results demonstrate the capability to derive quantitative imaging metrics from mouse tibia bone marrow for monitoring significant longitudinal MF changes.

Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning.

A murine model of myelofibrosis in tibia was used in a co-clinical trial to evaluate segmentation methods for application of image-based biomarkers to assess disease status. The dataset (32 mice with 157 3D MRI scans including 49 test-retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets. Two expert annotators (EA1 and EA2) performed manual segmentations of the mouse tibia (EA1: all data; EA2: test and validation). Attention U-net (A-U-net) model performance was assessed for accuracy with respect to EA1 reference using the average Jaccard index (AJI), volume intersection ratio (AVI), volume error (AVE), and Hausdorff distance (AHD) for four training scenarios: full training, two half-splits, and a single-mouse subsets. The repeatability of computer versus expert segmentations for tibia volume of test-retest pairs was assessed by within-subject coefficient of variance (%wCV). A-U-net models trained on full and half-split training sets achieved similar average accuracy (with respect to EA1 annotations) for test set: AJI = 83-84%, AVI = 89-90%, AVE = 2-3%, and AHD = 0.5 mm-0.7 mm, exceeding EA2 accuracy: AJ = 81%, AVI = 83%, AVE = 14%, and AHD = 0.3 mm. The A-U-net model repeatability wCV [95% CI]: 3 [2, 5]% was notably better than that of expert annotators EA1: 5 [4, 9]% and EA2: 8 [6, 13]%. The developed deep learning model effectively automates murine bone marrow segmentation with accuracy comparable to human annotators and substantially improved repeatability.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The 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.

A lymphatic-absorbed multi-targeted kinase inhibitor for myelofibrosis therapy.

Activation of compensatory signaling nodes in cancer often requires combination therapies that are frequently plagued by dose-limiting toxicities. Intestinal lymphatic drug absorption is seldom explored, although reduced toxicity and sustained drug levels would be anticipated to improve systemic bioavailability. A potent orally bioavailable multi-functional kinase inhibitor (LP-182) is described with intrinsic lymphatic partitioning for the combined targeting of phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways without observable toxicity. We demonstrate selectivity and therapeutic efficacy through reduction of downstream kinase activation, amelioration of disease phenotypes, and improved survival in animal models of myelofibrosis. Our further characterization of synthetic and physiochemical properties for small molecule lymphatic uptake will support continued advancements in lymphatropic therapy for altering disease trajectories of a myriad of human disease indications.

Multiparametric MRI to quantify disease and treatment response in mice with myeloproliferative neoplasms.

Histopathology, the standard method to assess BM in hematologic malignancies such as myeloproliferative neoplasms (MPNs), suffers from notable limitations in both research and clinical settings. BM biopsies in patients fail to detect disease heterogeneity, may yield a nondiagnostic sample, and cannot be repeated frequently in clinical oncology. Endpoint histopathology precludes monitoring disease progression and response to therapy in the same mouse over time, missing likely variations among mice. To overcome these shortcomings, we used MRI to measure changes in cellularity, macromolecular constituents, and fat versus hematopoietic cells in BM using diffusion-weighted imaging (DWI), magnetization transfer, and chemical shift-encoded fat imaging. Combining metrics from these imaging parameters revealed dynamic alterations in BM following myeloablative radiation and transplantation. In a mouse MPLW515L BM transplant model of MPN, MRI detected effects of a JAK2 inhibitor, ruxolitinib, within 5 days of initiating treatment and identified differing kinetics of treatment responses in subregions of the tibia. Histopathology validated the MRI results for BM composition and heterogeneity. Anatomic MRI scans also showed reductions in spleen volume during treatment. These findings establish an innovative, clinically translatable MRI approach to quantify spatial and temporal changes in BM in MPN.

Technical note: Temperature and concentration dependence of water diffusion in polyvinylpyrrolidone solutions.

OBJECTIVE: The goal of this work is to provide temperature and concentration calibration of water diffusivity in polyvinylpyrrolidone (PVP) solutions used in phantoms to assess system bias and linearity in apparent diffusion coefficient (ADC) measurements. METHOD: ADC measurements were performed for 40 kDa (K40) PVP of six concentrations (0%, 10%, 20%, 30%, 40%, and 50% by weight) at three temperatures (19.5°C, 22.5°C, and 26.4°C), with internal phantom temperature monitored by optical thermometer (±0.2°C). To achieve ADC measurement and fit accuracy of better than 0.5%, three orthogonal diffusion gradients were calibrated using known water diffusivity at 0°C and system gradient nonlinearity maps. Noise-floor fit bias was also controlled by limiting the maximum b-value used for ADC calculation of each sample. The ADC temperature dependence was modeled by Arrhenius functions of each PVP concentration. The concentration dependence was modeled by quadratic function for ADC normalized by the theoretical water diffusion values. Calibration coefficients were obtained from linear regression model fits. RESULTS: Measured phantom ADC values increased with temperature and decreasing PVP concentration, [PVP]. The derived Arrhenius model parameters for [PVP] between 0% and 50%, are reported and can be used for K40 ADC temperature calibration with absolute ADC error within ±0.016 µm2 /ms. Arrhenius model fit parameters normalized to water value scaled with [PVP] between 10% and 40%, and proportional change in activation energy increased faster than collision frequency. ADC normalization by water diffusivity, DW , from the Speedy-Angell relation accounted for the bulk of temperature dependence (±0.035 µm2 /ms) and yielded quadratic calibration for ADCPVP /DW  = (12.5 ± 0.7) ·10-5 ·[PVP]2 - (23.2 ± 0.3)·10-3 ·[PVP]+1, nearly independent of PVP molecular weight and temperature. CONCLUSION: The study provides ground-truth ADC values for K40 PVP solutions commonly used in diffusion phantoms for scanning at ambient room temperature. The described procedures and the reported calibration can be used for quality control and standardization of measured ADC values of PVP at different concentrations and temperatures.

Vascular Deformation Mapping for CT Surveillance of Thoracic Aortic Aneurysm Growth.

Background Aortic diameter measurements in patients with a thoracic aortic aneurysm (TAA) show wide variation. There is no technique to quantify aortic growth in a three-dimensional (3D) manner. Purpose To validate a CT-based technique for quantification of 3D growth based on deformable registration in patients with TAA. Materials and Methods Patients with ascending and descending TAA with two or more CT angiography studies between 2006 and 2020 were retrospectively identified. The 3D aortic growth was quantified using vascular deformation mapping (VDM), a technique that uses deformable registration to warp a mesh constructed from baseline aortic anatomy. Growth assessments between VDM and clinical CT diameter measurements were compared. Aortic growth was quantified as the ratio of change in surface area at each mesh element (area ratio). Manual segmentations were performed by independent raters to assess interrater reproducibility. Registration error was assessed using manually placed landmarks. Agreement between VDM and clinical diameter measurements was assessed using Pearson correlation and Cohen κ coefficients. Results A total of 38 patients (68 surveillance intervals) were evaluated (mean age, 69 years ± 9 [standard deviation]; 21 women), with TAA involving the ascending aorta (n = 26), descending aorta (n = 10), or both (n = 2). VDM was technically successful in 35 of 38 (92%) patients and 58 of 68 intervals (85%). Median registration error was 0.77 mm (interquartile range, 0.54-1.10 mm). Interrater agreement was high for aortic segmentation (Dice similarity coefficient = 0.97 ± 0.02) and VDM-derived area ratio (bias = 0.0, limits of agreement: -0.03 to 0.03). There was strong agreement (r = 0.85, P < .001) between peak area ratio values and diameter change. VDM detected growth in 14 of 58 (24%) intervals. VDM revealed growth outside the maximally dilated segment in six of 14 (36%) growth intervals, none of which were detected with diameter measurements. Conclusion Vascular deformation mapping provided reliable and comprehensive quantitative assessment of three-dimensional aortic growth and growth patterns in patients with thoracic aortic aneurysms undergoing CT surveillance. Published under a CC BY 4.0 license Online supplemental material is available for this article. See also the editorial by Wieben in this issue.

Structural effects of morpholine replacement in ZSTK474 on Class I PI3K isoform inhibition: Development of novel MEK/PI3K bifunctional inhibitors.

Established roles for PI3K and MAPK signaling pathways in tumorigenesis has prompted extensive research towards the discovery of small-molecule inhibitors as cancer therapeutics. However, significant compensatory regulation exists between these two signaling cascades, leading to redundancy among survival pathways. Consequently, initial clinical trials aimed at either PI3K or MEK inhibition alone have proven ineffective and highlight the need for development of targeted and innovative therapeutic combination strategies. We designed a series of PI3K inhibitor derivatives wherein a single morpholine group of the PI3K inhibitor ZSTK474 was substituted with a variety of 2-aminoethyl functional groups. Analogs with pendant hydroxyl or methoxy groups maintained low nanomolar inhibition towards PI3Kα, PI3Kγ, and PI3Kδ isoforms in contrast to those with pendant amino groups which were significantly less inhibitory. Synthesis of prototype PI3K/MEK bifunctional inhibitors (6r, 6s) was guided by the structure-activity data, where a MEK-targeting inhibitor was tethered directly via a short PEG linker to the triazine core of the PI3K inhibitor analogs. These compounds (6r, 6s) displayed nanomolar inhibition towards PI3Kα, δ, and MEK (IC50 ∼105-350 nM), and low micromolar inhibition for PI3Kß and PI3Kγ (IC50 ∼1.5-3.9 µM) in enzymatic inhibition assays. Cell viability assays demonstrated superior anti-proliferative activity for 6s over 6r in three tumor-derived cell lines (A375, D54, SET-2), which correlated with inhibition of downstream AKT and ERK1/2 phosphorylation. Compounds 6r and 6s also demonstrated in vivo tolerability with therapeutic efficacy through reduction of kinase activation and amelioration of disease phenotypes in the JAK2V617F mutant myelofibrosis mouse cancer model. Taken together, these results support further structure optimization of 6r and 6s as promising leads for combination therapy in human cancer as a new class of PI3K/MEK bifunctional inhibitors.

PEGylated Nanoscale Metal-Organic Frameworks for Targeted Cancer Imaging and Drug Delivery.

Nanoscale metal-organic frameworks (nMOFs) are a unique type of hybrid materials, which are broadly applicable as cargo delivery systems. However, the relatively low material stability and insufficient cancer cell interacting capacity have limited nMOFs' applications in cancer theranostics. Herein, a zirconium-based nMOF UiO-66-N3 was synthesized, and its surface was covalently functionalized with alkyne-containing polyethylene glycol (PEG) via the azide-alkyne click chemistry. After that, F3 peptide was attached for targeting of cancer cells (the material was denoted as UiO-66-PEG-F3). Doxorubicin (DOX) served as a therapeutic drug and a fluorescent label in this study, and it was transported into UiO-66-PEG conjugates with sufficient drug loading efficiency. pH-responsive release of DOX from UiO-66 conjugates was witnessed. The structural integrity of UiO-66-N3 was maintained post the surface modification process. Flow cytometry and confocal fluorescence microscopy revealed that DOX/UiO-66-PEG-F3 had stronger accumulation in MDA-MB-231 cells (nucleolin+) compared with DOX/UiO-66-PEG. In order to track the pharmacokinetic behavior (organ distribution profile) in vivo, the positron-emitting zirconium-89 (89Zr) was incorporated into UiO-66-N3. Similar PEGylation and F3 peptide conjugation resulted in the formation of 89Zr-UiO-66-PEG-F3. Serial positron emission tomography (PET) imaging demonstrated that the preferential accumulation of 89Zr-UiO-66-PEG-F3 in MDA-MB-231 tumors, and their liver clearance was faster than PEGylated UiO-66 using noncovalent methods. Thus, the PEGylated nMOFs using covalent strategies may find broad application in future cancer theranostics.

Engineered Antibody Fragment against the Urokinase Plasminogen Activator for Fast Delineation of Triple-Negative Breast Cancer by Positron Emission Tomography.

The urokinase plasminogen activator (uPA) and its cofactors are important regulators of tumor initiation and progression (including metastasis), and its overexpression is associated with unfavorable situations in cancer patients. We have previously used positron emission tomography (PET) imaging with a radiolabeled monoclonal antibody against the uPA (named ATN-291) to detect the uPA signaling activity in various cancer types; however, good tumor contrast can only be observed 24 h postinjection. To shorten the antibody circulation time and decrease interactions of ATN-291 with the mononuclear phagocyte system (MPS), our goal in this study is to develop an engineered antibody fragment (F(ab')2) from the parent antibody. By pepsin digestion and chromatography purification, ATN-291 F(ab')2 was obtained and characterized. Subsequently, it was conjugated with NOTA-Bn-NCS or fluorescein isothiocyanate (FITC) for PET imaging and fluorescence-mediated cellular analysis (i.e., flow cytometry or fluorescence microscopy). We confirmed that ATN-291 F(ab')2 still maintained a good targeting efficacy for the uPA in MDA-MB-231 cells (uPA+) and it had a faster blood clearance speed compared with ATN-291, while its interaction with MPS has been significantly decreased. In rodent tumor xenografts, radiolabeled ATN-291 F(ab')2 had a selective and persistent uptake in MDA-MB-231 tumors, with an early tumor-to-blood ratio of 1.3 ± 0.8 (n = 4) at 2 h postinjection from PET imaging. During our observation, radiolabeled ATN-291 F(ab')2 was excreted from both renal and hepatobiliary pathways. Radiolabeled ATN-291 F(ab')2 was also used for detecting uPA fluctuation during the tumor treatment in test animals. We concluded that radiolabeled ATN-291 F(ab')2 could be used as fast as PET cancer diagnostics with versatile applicability.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma.

RATIONALE AND OBJECTIVES: Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression. MATERIALS AND METHODS: We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRMrFLAIR+), decreased (PRMrFLAIR-), or unchanged (PRMrFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRMrFLAIR between weeks 10 and 20 and continuously until the PRMrFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection. RESULTS: Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRMrFLAIR+ (PFS: p <0.01; OS: p <0.001). PRMrFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRMrFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001). CONCLUSION: PRMrFLAIR may provide an early biomarker of disease progression in glioblastoma.

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.

Murine models of IDH-wild-type glioblastoma exhibit spatial segregation of tumor initiation and manifestation during evolution.

Recent characterization of spatiotemporal genomic architecture of IDH-wild-type multifocal glioblastomas (M-GBMs) suggests a clinically unobserved common-ancestor (CA) with a less aggressive phenotype, generating highly genetically divergent malignant gliomas/GBMs in distant brain regions. Using serial MRI/3D-reconstruction, whole-genome sequencing and spectral karyotyping-based single-cell phylogenetic tree building, we show two distinct types of tumor evolution in p53-mutant driven mouse models. Malignant gliomas/GBMs grow as a single mass (Type 1) and multifocal masses (Type 2), respectively, despite both exhibiting loss of Pten/chromosome 19 (chr19) and PI3K/Akt activation with sub-tetraploid/4N genomes. Analysis of early biopsied and multi-segment tumor tissues reveals no evidence of less proliferative diploid/2N lesions in Type 1 tumors. Strikingly, CA-derived relatively quiescent tumor precursors with ancestral diploid/2N genomes and normal Pten/chr19 are observed in the subventricular zone (SVZ), but are distantly segregated from multi focal Type 2 tumors. Importantly, PI3K/Akt inhibition by Rictor/mTORC2 deletion blocks distant dispersal, restricting glioma growth in the SVZ.

Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial.

Mean tumor apparent diffusion coefficient (ADC) of breast cancer showed excellent repeatability but only moderate predictive power for breast cancer therapy response in the ACRIN 6698 multicenter imaging trial. Previous single-center studies have shown improved predictive performance for alternative ADC histogram metrics related to low ADC dense tumor volume. Using test/retest (TT/RT) 4 b-value diffusion-weighted imaging acquisitions from pretreatment or early-treatment time-points on 71 ACRIN 6698 patients, we evaluated repeatability for ADC histogram metrics to establish confidence intervals and inform predictive models for future therapy response analysis. Histograms were generated using regions of interest (ROIs) defined separately for TT and RT diffusion-weighted imaging. TT/RT repeatability and intra- and inter-reader reproducibility (on a 20-patient subset) were evaluated using wCV and Bland-Altman limits of agreement for histogram percentiles, low-ADC dense tumor volumes, and fractional volumes (normalized to total histogram volume). Pearson correlation was used to reveal connections between metrics and ROI variability across the sample cohort. Low percentiles (15th and 25th) were highly repeatable and reproducible, wCV < 8.1%, comparable to mean ADC values previously reported. Volumetric metrics had higher wCV values in all cases, with fractional volumes somewhat better but at least 3 times higher than percentile wCVs. These metrics appear most sensitive to ADC changes around a threshold of 1.2 µm2/ms. Volumetric results were moderately to strongly correlated with ROI size. In conclusion, Lower histogram percentiles have comparable repeatability to mean ADC, while ADC-thresholded volumetric measures currently have poor repeatability but may benefit from improvements in ROI techniques.

Enhanced mitochondrial fission suppresses signaling and metastasis in triple-negative breast cancer.

BACKGROUND: Mitochondrial dynamics underlies malignant transformation, cancer progression, and response to treatment. Current research presents conflicting evidence for functions of mitochondrial fission and fusion in tumor progression. Here, we investigated how mitochondrial fission and fusion states regulate underlying processes of cancer progression and metastasis in triple-negative breast cancer (TNBC). METHODS: We enforced mitochondrial fission and fusion states through chemical or genetic approaches and measured migration and invasion of TNBC cells in 2D and 3D in vitro models. We also utilized kinase translocation reporters (KTRs) to identify single cell effects of mitochondrial state on signaling cascades, PI3K/Akt/mTOR and Ras/Raf/MEK/ERK, commonly activated in TNBC. Furthermore, we determined effects of fission and fusion states on metastasis, bone destruction, and signaling in mouse models of breast cancer. RESULTS: Enforcing mitochondrial fission through chemical or genetic approaches inhibited migration, invasion, and metastasis in TNBC. Breast cancer cells with predominantly fissioned mitochondria exhibited reduced activation of Akt and ERK both in vitro and in mouse models of breast cancer. Treatment with leflunomide, a potent activator of mitochondrial fusion proteins, overcame inhibitory effects of fission on migration, signaling, and metastasis. Mining existing datasets for breast cancer revealed that increased expression of genes associated with mitochondrial fission correlated with improved survival in human breast cancer. CONCLUSIONS: In TNBC, mitochondrial fission inhibits cellular processes and signaling pathways associated with cancer progression and metastasis. These data suggest that therapies driving mitochondrial fission may benefit patients with breast cancer.

Positron Emission Tomography/Magnetic Resonance Imaging of Glioblastoma Using a Functionalized Gadofullerene Nanoparticle.

Water-soluble gadofullerene nanomaterials have been extensively investigated as magnetic resonance imaging (MRI) contrast agents, radical scavengers, sensitizers for photodynamic therapy, and inherent antineoplastic agents. Most recently, an alanine-modified gadofullerene nanoparticle (Gd@C82-Ala) with excellent anticancer activity has been reported; however, the absolute tumor uptake of Gd@C82-Ala is still far from being satisfactory, and its dynamic pharmacokinetics and long-term metabolic behaviors remain to be elucidated. Herein, Gd@C82-Ala was chemically modified with eight-arm polyethylene glycol amine to improve its biocompatibility and provide the active sites for the attachment of a tumor-homing ligand (cRGD) and positron emission tomography (PET) isotopes (i.e., 64Cu or 89Zr). The physical and chemical properties (e.g., size, surface functionalization condition, radiochemical stability, etc.) of functionalized Gd@C82-Ala were properly characterized. Also, its glioblastoma cell targeting capacity was evaluated in vitro by flow cytometry, confocal fluorescence microscopy, and dynamic cellular interaction assays. Because of the presence of gadolinium ions, the gadofullerene conjugates can act simultaneously as T1* MRI contrast agents and PET probes. Thus, the pharmacokinetic behavior of functionalized Gd@C82-Ala was investigated by PET/MRI, which combines the merits of high resolution and excellent sensitivity. The functionalized Gd@C82-Ala-PEG-cRGD-NOTA-64Cu (NOTA stands for 1,4,7-triazacyclononane-triacetic acid) demonstrated much higher accumulation in U87-MG tumor than its counterpart without cRGD attachment from in vivo PET observation, consistent with observation at the cellular level. In addition, Gd@C82-Ala-PEG-Df-89Zr (Df stands for desferrioxamine) was employed to investigate the metabolic behavior of gadofullerene conjugates in vivo for up to 30 days. It was estimated that nearly 70% of Gd@C82-Ala-PEG-Df-89Zr was excreted from the test subjects primarily through renal pathways within 24 h. With proper surface engineering, functionalized Gd@C82-Ala nanoparticles can show an improved accumulation in glioblastoma. Pharmacokinetic studies also confirmed the safety of this nanoplatform, which can be used as an image-guidable therapeutic agent for glioblastoma.

Comparison of Voxel-Wise and Histogram Analyses of Glioma ADC Maps for Prediction of Early Therapeutic Change.

Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent diffusion coefficient (ADC), have previously shown promise when used in combination with voxel-based analysis reflecting regional changes. The functional diffusion mapping (fDM) metric is hypothesized to be associated with volume of tumor exhibiting an increasing ADC owing to effective therapeutic action. In this work, the reference fDM-predicted survival (from previous study) for 3 weeks from treatment initiation (midtreatment) is compared to multiple histogram-based metrics using Kaplan-Meier estimator for 80 glioma patients stratified to responders and nonresponders based on the population median value for the given metric. The ADC histogram metric reflecting reduction in midtreatment volume of solid tumor (ADC < 1.25 × 10-3 mm2/s) by >8% population-median with respect to pretreatment is found to have the same predictive power as the reference fDM of increasing midtreatment ADC volume above 4%. This study establishes the level of correlation between fDM increase and low-ADC tumor volume shrinkage for prediction of early response to radiation therapy in patients with glioma malignancies.

Reprint of: Voxel-Wise Longitudinal Parametric Response Mapping Analysis of Chest Computed Tomography in Smokers.

RATIONALE AND OBJECTIVES: Chronic obstructive pulmonary disease is a heterogeneous disease characterized by small airway abnormality and emphysema. We hypothesized that a voxel-wise computed tomography analytic approach would identify patterns of disease progression in smokers. MATERIALS AND METHODS: We analyzed 725 smokers in spirometric GOLD stages 0-4 with two chest CTs 5 years apart. Baseline inspiration, follow-up inspiration and follow-up expiration images were spatially registered to baseline expiration so that each voxel had correspondences across all time points and respiratory phases. Voxel-wise Parametric Response Mapping (PRM) was then generated for the baseline and follow-up scans. PRM classifies lung as normal, functional small airway disease (PRMfSAD), and emphysema (PRMEMPH). RESULTS: Subjects with low baseline PRMfSAD and PRMEMPH predominantly had an increase in PRMfSAD on follow-up; those with higher baseline PRMfSAD and PRMEMPH mostly had increases in PRMEMPH. For GOLD 0 participants (n = 419), mean 5-year increases in PRMfSAD and PRMEMPH were 0.3% for both; for GOLD 1-4 participants (n = 306), they were 0.6% and 1.6%, respectively. Eighty GOLD 0 subjects (19.1%) had overall radiologic progression (30.0% to PRMfSAD, 52.5% to PRMEMPH, and 17.5% to both); 153 GOLD 1-4 subjects (50.0%) experienced progression (17.6% to PRMfSAD, 48.4% to PRMEMPH, and 34.0% to both). In a multivariable model, both baseline PRMfSAD and PRMEMPH were associated with development of PRMEMPH on follow-up, although this relationship was diminished at higher levels of baseline PRMEMPH. CONCLUSION: A voxel-wise longitudinal PRM analytic approach can identify patterns of disease progression in smokers with and without chronic obstructive pulmonary disease.