Myeloproliferative neoplasms (MPN's) including myelofibrosis (MF) are neoplastic diseases that initiate in the bone marrow from abnormal regulation of hematopoietic stem cells primarily harboring somatic mutation activating Janus Kinase 2 (JAK2). Central phenotypes resulting from uncontrolled JAK2 signaling in MF have been established, leading to pronounced extramedullary hematopoiesis, splenomegaly, and bone marrow fibrosis; however, therapeutic resistance, durability of remission, and assessment of treatment response remain significant limitations to inhibitor treatment in many MF patient populations. Mechanisms linked to compensatory phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways in MF highlight the frontier for combinatorial multi-kinase inhibition therapies. Striking a balance between positive clinical outcomes, dose-limiting toxicity, and monitoring of pharmacological efficacy represents an unmet need for evaluation strategies capable of effective translation from bench to bedside. Despite reliance of disease staging on the grade of fibrosis in bone marrow sampled from just a single biopsy site (iliac crest), oncologists have rarely utilized radiological imaging to analyze the global bone marrow architecture for monitoring disease progression and response to treatment. Uncontrolled hematopoiesis during MF progression results in displacement of normal marrow leading to fibrosis and alterations in the bone marrow microenvironment. Here, we evaluated multiparametric magnetic resonance imaging (MRI) for detection of bone marrow phenotypes and treatment normalization in the tibia of murine Jak2+/V617F transplant models of MF. Diffusion-weighted MRI (DWI) quantified changes in cellularity as the dynamics of water mobility through apparent diffusion coefficient (ADC) and was validated longitudinally by repeat test-retest measurements in Jak2+/V617F mice over a 10wk period post-bone marrow transplant (post-BMT), and used to generate spatially resolved repeatability coefficients of the murine tibia marrow space. Parametric response mapping (PRM) revealed an ~20% increase in ADC in the proximal tibia (2-9 mm region) between 5 and 10 w post-BMT, and detected advancement of a cellular/adipose interface towards the distal tibia indicative of increased proliferation and displacement of marrow adiposity, presenting the ability to non-invasively identify and monitor progression MF in the marrow space using PRM. Assessment of extramedullary hematopoiesis by abdominal MRI revealed that animals treated with an experimental orally bioavailable multi-kinase inhibitor LP-182 (MEKi/PI3Ki/mTORi) in combination with the JAK inhibitor Ruxolitinib displayed ~35% reduction in spleen volume as compared to either treatment alone, and ~60% reduction compared to vehicle, with concomitant on-target inhibition of downstream kinase signal transduction evidenced by immunochemistry. Combination treatment of LP-182 and Ruxolitinib between 5 and 10 w post-BMT prevented any significant increase in ADC in the tibia marrow space of Jak2+/V617F mice compared to wild-type untreated mice, whereas untreated Jak2+/V617F mice displayed ~30% increase in ADC over the same duration highlighting the ability to monitor both disease progression and response to treatment non-invasively using PRM. Furthermore, treatment of mice with LP-182 resulted in maintenance of hematologic markers, reduction in allele burden, and was well tolerated at the administered dosage (400 mg/kg; daily) for >2 months, with no observable pharmacotoxicity as evaluated in a blinded study by a board-certified veterinary pathologist.Taken together, MRI biomarker changes correlated with changes in the bone marrow space during disease progression and response treatment with novel agents designed to target key, co-activated oncogenic drivers of MF progression. Parametric response mapping revealed important discoveries: 1) imaging of bone marrow provides spatiotemporal monitoring of disease progression and heterogeneity; 2) temporal marrow changes in response to therapy intervention can be resolved; 3) LP-182 prevented changes in cellularity to normalize marrow and provide a translational opportunity for patient allele burden reduction. While our efforts center on MF, quantitative MRI of bone marrow will be applicable to other hematologic cancers providing broad oncological patient impact.

Background/Objectives: The recent development of four-dimensional X-ray velocimetry (4DXV) technology (three-dimensional space and time) provides a unique opportunity to obtain preclinical quantitative functional lung images. Only single-scan measurements in non-survival studies have been obtained to date; thus, methodologies enabling animal survival for repeated imaging to be accomplished over weeks or months from the same animal would establish new opportunities for the assessment of pathophysiology drivers and treatment response in advanced preclinical drug-screening efforts. Methods: An anesthesia protocol developed for animal recovery to allow for repetitive, longitudinal scanning of individual animals over time. Test–retest imaging scans from the lungs of healthy mice were performed over 8 weeks to assess the repeatability of scanner-derived quantitative imaging metrics and variability. Results: Using a murine model of fibroproliferative lung disease, this longitudinal scanning approach captured heterogeneous progressive changes in pulmonary function, enabling the visualization and quantitative measurement of averaged whole lung metrics and spatial/regional change. Radiation dosimetry studies evaluated the effects of imaging acquisition protocols on X-ray dosage to further adapt protocols for the minimization of radiation exposure during repeat imaging sessions using these newly developed image acquisition protocols. Conclusions: Overall, we have demonstrated that the 4DXV advanced imaging scanner allows for repeat measurements from the same animal over time to enable the high-resolution, noninvasive mapping of quantitative lung airflow dysfunction in mouse models with heterogeneous pulmonary disease. The animal anesthesia and image acquisition protocols described will serve as the foundation on which further applications of the 4DXV technology can be used to study a diverse array of murine pulmonary disease models. Together, 4DXV provides a novel and significant advancement for the longitudinal, noninvasive interrogation of pulmonary disease to assess spatial/regional disease initiation, progression, and response to therapeutic interventions.

PurposeTo automate bone marrow segmentation within pelvic bones in quantitative fat MRI of myelofibrosis (MF) patients using deep-learning (DL) U-Net models.MethodsAutomated segmentation of bone marrow (BM) was evaluated for four U-Net models: 2D U-Net, 2D attention U-Net (2D A-U-Net), 3D U-Net and 3D attention U-Net (3D A-U-Net). An experienced annotator performed the delineation on in-phase (IP) pelvic MRI slices to mark the boundaries of BM regions within two pelvic bones: proximal femur and posterior ilium. The dataset comprising volumetric images of 58 MF patients was split into 32 training, 6 validation and 20 test sub-sets. Model performance was assessed using conventional metrics: average Jaccard Index (AJI), average Volume Error (AVE), average Hausdorff Distance (AHD), and average Volume Intersection Ratio (VIR). Iterative model optimization was performed based on maximizing validation sub-set AJI. Wilcoxon’s rank sum test with Bonferroni corrected significance threshold of p<0.003 was used to compare DL segmentation models for test sub-set.Results2D segmentation models performed best for iliac BM with achieved scores of 95-96% for the VIR and 87-88% for AJI agreement with expert annotations on the test set. Similar performance was observed for femoral BM segmentation with slightly better VIR but worse AJI agreement for U-Net (94% and 86%) versus A-U-Net (92% and 87%). 2D models also exhibited lower AVE variability (8-9%) and ilium AHD (16 mm). The 3D segmentation models have shown marginally higher errors (AHD of 19-20 mm for ilium and 10-12% AVE-SD for both bones) and generally lower agreement scores (VIR of 91-93% for ilium and 89-91% for femur with 85-86% AJI).Pairwise comparison across four U-Nets for three metrics (AHD, AJI, AVE) showed that AJI and AHD performance was not significantly different for 3D U-Net versus 3D A-U-Net and for 2D U-Net versus 2D A-U-Net. Except for AVE, for majority of performance metric comparisons 2D versus 3D model differences were significant in both bones (p<0.001).ConclusionAll four tested U-Net models effectively automated BM segmentation in pelvic MRI of MF patients. The 2D A-U-Net was found best overall for BM segmentation in both femur and ilium.

Introduction: Most cases of myelofibrosis (MF) arise from constitutive activation of the JAK/STAT signaling pathway in hematopoietic stem cells (HSCs) with resultant activation of bone marrow stromal cells driving fibrosis. Treatment options are limited to approved Janus kinase (JAK) inhibitors that produce minimal reductions in fibrosis or malignant HSCs, the primary drivers of disease. Overall five-year survival remains ~40%, underscoring the dismal plight of patients with MF. Aberrant JAK/STAT signaling activates downstream PI3K/AKT/mTOR pathway and MAPK/ERK pathways with interconnections between these pathways regulating outputs such as gene expression, proliferation, and survival. Due to considerable signaling crosstalk, we posited that combined targeting of both upstream (JAK/STAT) along with downstream (MEK and PI3K/mTOR) signaling effectors would increase treatment efficiency compared to current, single agent JAKi's. Methods & Results: Treatment of in vitro SET-2 cells revealed IC50 for proliferation of LP-182, MMB and LP-182+MMB was 14.4, 0.13 and 0.07mm, respectively. MRI was used to quantify changes in spleen volumes over time in a mouse JAK2-mutant MF mouse model. Treatment cohorts consisted of vehicle (n=11), LP-182 (400 mg/kg, PO, n=5), momelotinib (MMB, 50 mg/kg, PO, n=7) and combination (LP-182+MMB, n=4) OD for 28 days. Mean spleen volume/body weight (mm3/BW) were assessed over time at T0/T28 (mean(+/-sem)) days for vehicle (23.5(2.1)/25.8(2.1)), MMB (24.0(3.0)/19.8(2.5)), LP-182 (26.5(2.73)/22.6(3.2)) and combination group (22.0(1.9)/16.1(2.8). Measurements of spleen volumes in LP-182 and MMB treatment groups generally declined over the treatment period but to a lesser extent than the combination treatment group. Harvested spleens at the end of study were evaluated for signaling modulation which revealed for the MMB treated cohort, no significant reduction of pATK or pERK1/2 levels, however, MMB treatment resulted in significantly reduced pSTAT5 levels (p<0.001) compared to vehicles. LP-182 treatment alone or in combination with MMB revealed normalization of pAKT and pERK was achieved. Clinical Implications: Jaki's such as MMB and ruxolitinib are unable to down modulate oncogenic driver signals such as PI3K/mTOR and MAPK necessitating development of an improved therapeutic strategy. LP-182 was demonstrated to have potency as single agent and in combination with MMB for down-modulating proliferative and survival signals. As LP-182 was demonstrated to provide therapeutic potency in combination with MMB, clinical evaluation of this combination strategy appears warranted. LP-182 has been demonstrated to be absorbed through the lymphatic system which provides a unique opportunity to establish an efficacious, less toxic combination approach towards development of an efficacious MF treatment strategy for ultimately improving patient outcomes.

The mitogen-activated protein kinase (MAPK) and mechanistic target of rapamycin (mTOR) signaling nodes play a crucial role in many human cancers. Due to the molecular reciprocity between MAPK and mTOR signaling nodes, development of compounds with multikinase targeting was explored. A series of mTOR inhibitor analogs of AZD8055 and AZD2014 were designed to allow for covalent linking to a potent MAPK kinase (MEK) inhibitor to produce a single, bivalent chemical entity. Dual-acting agents (i.e., compound LP-65) were synthesized displaying high in vitro inhibition of both MEK (IC50 = 83.2 nM) and mTOR (IC50 = 40.5 nM). Additionally, compound LP-65 demonstrated significant modulation of MEK and mTOR signaling activity in human glioma cells (D54) and human melanoma cells (A375), with a corresponding decrease in cellular proliferation and migration. Treatment of mice with LP-65 (40 mg/kg) having a myeloproliferative neoplasm, myelofibrosis, revealed down modulation of in vivo signaling pathways and therapeutic efficacy.

Clinical application of AI/DL-aided acquisitions for quantitative bi-parametric (q-bp)MRI requires validation and harmonization across vendor platforms. An AI/DL-accelerated q-bpMRI, including 5-echo T2 and 4-b-value apparent diffusion coefficient (ADC) mapping, was implemented on two 3T clinical scanners by two vendors alongside the qualitative standard-of-care (SOC) MRI protocols for six patients with biopsy-confirmed prostate cancer (PCa). AI/DL versus SOC bpMRI image quality was compared for MR-visible PCa lesions on a 4-point Likert-like scale. Quantitative validation and protocol bias assessment were performed using a multiparametric phantom with reference T2 and diffusion kurtosis values mimicking prostate tissue ranges. Six-minute q-bpMRI achieved acceptable diagnostic quality comparable to the SOC. Better SNR was observed for DL/AI versus SOC ADC with method-dependent distortion susceptibility and resolution enhancement. The measured biases were unaffected by AI/DL reconstruction and related to acquisition protocol parameters: constant for spin-echo T2 (−7 ms to +5 ms) and ADC (4b-fit: −0.37 µm2/ms and 2b-fit: −0.19 µm2/ms), while nonlinear for echo-planar T2 (−37 ms to +14 ms). Measured phantom ADC bias dependence on b-value range was consistent with that observed for PCa lesions. Bias correction harmonized lesion T2 and ADC values across different AI/DL-aided q-bpMRI acquisitions. The developed workflow enables harmonization of AI/DL-accelerated quantitative T2 and ADC mapping in multi-vendor clinical settings.

Background/Objectives: This work prospectively evaluates the vendor-provided Low Variance (LOVA) apparent diffusion coefficient (ADC) gradient nonlinearity correction (GNC) technique for primary tumors, neck nodal metastases, and normal masseter muscles in patients with head and neck cancers (HNCs). Methods: Multiple b-value diffusion-weighted (DW)-MR images were acquired on a 3.0 T scanner using a single-shot echo planar imaging (SS-EPI) and multi-shot (MS)-EPI for diffusion phantom materials (20% and 40% polyvinylpyrrolidone (PVP) in water). Pretreatment DW-MRI acquisitions were performed for sixty HNC patients (n = 60) who underwent chemoradiation therapy. ADC values with and without GNC were calculated offline using a monoexponential diffusion model over all b-values, relative percentage (r%) changes (Δ) in ADC values with and without GNC were calculated, and the ADC histograms were analyzed. Results: Mean ADC values calculated using SS-EPI DW data with and without GNC differed by ≤1% for both PVP20% and PVP40% at the isocenter, whereas off-center differences were ≤19.6% for both concentrations. A similar trend was observed for these materials with MS-EPI. In patients, the mean rΔADC (%) values measured with SS-EPI differed by 4.77%, 3.98%, and 5.68% for primary tumors, metastatic nodes, and masseter muscle. MS-EPI exhibited a similar result with 5.56%, 3.95%, and 4.85%, respectively. Conclusions: This study showed that the GNC method improves the robustness of the ADC measurement, enhancing its value as a quantitative imaging biomarker used in HNC clinical trials.

Background/Objectives: Myelofibrosis (MF) is a myeloproliferative neoplasm characterized by the replacement of healthy bone marrow (BM) with malignant and fibrotic tissue. In a healthy state, bone marrow is composed of approximately 60–70% fat cells, which are replaced as disease progresses. Proton density fat fraction (PDFF), a non-invasive and quantitative MRI metric, enables analysis of BM architecture by measuring the percentage of fat versus cells in the environment. Our objective is to investigate variance in quantitative PDFF-MRI values over time as a marker of disease progression and response to treatment. Methods: We analyzed existing data from three cohorts of mice: two groups with MF that failed to respond to therapy with approved drugs for MF (ruxolitinib, fedratinib), investigational compounds (navitoclax, balixafortide), or vehicle and monitored over time by MRI; the third group consisted of healthy controls imaged at a single time point. Using in-house MATLAB programs, we performed a voxel-wise analysis of PDFF values in lower extremity bone marrow, specifically comparing the variance of each voxel within and among mice. Results: Our findings revealed a significant difference in PDFF values between healthy and diseased BM. With progressive disease non-responsive to therapy, the expansion of hematopoietic cells in BM nearly completely replaced normal fat, as determined by a markedly reduced PDFF and notable reduction in the variance in PDFF values in bone marrow over time. Conclusions: This study validated our hypothesis that the variance in PDFF in BM decreases with disease progression, indicating pathologic expansion of hematopoietic cells. We can conclude that disease progression can be tracked by a decrease in PDFF values. Analyzing variance in PDFF may improve the assessment of disease progression in pre-clinical models and ultimately patients with MF.

Disclosure: A. Dill Gomes: None. M.C. Foss de Freitas: None. N. Shah: None. R. Meral: None. T. Chenevert: None. E.A. Oral: Regeneron Pharmaceuticals, Amryt Pharmaceuticals, Chiesi Rare Disease Group, Marea Therapeutics, Rejuvenate Bio, Fractyl Laboratories, Novo Nordisk, Morphic Medical. Background: Precise body fat measurements are essential for assessment of novel phenotypes and follow-up in lipodystrophy syndromes. However, there is a lack of adequate tools for evaluating regional fat distribution in the body. Our radiology team developed software in-house to quantify subcutaneous and visceral compartments in the abdomen. Here, we adapt this method to quantify adipose tissue in the neck and thighs to better assist in diagnosis of abnormal fat distribution disorders. Methods: In a previously reported clinical trial, data from 4 subjects diagnosed with Madelung’s symmetric lipomatosis (a severe phenotype of abnormal fat distribution) were collected before and after leptin replacement therapy. We took MRI image scans from baseline and week 24 of therapy and applied region of interest (ROI) masks over three slices in the neck and mid-thigh regions. We quantified the percentage of fat in these areas and compared them to the same regions in DEXA scans taken at the same timepoints. To analyze the measurement differences between the MRI and DEXA ROI’s, we performed t-tests and Pearson correlation. To determine the agreement of the two methods, we evaluated Bland-Altman Plots. Results: All subjects displayed altered percentages of regional fat between baseline and week 24. MRI showed an average reduction of 17% fat in the neck (baseline = 45%±0.1, week 24 = 37%±0.2) and 36% in the thigh (baseline = 26%±0.2, week 24 = 16.6%±0.2). Meanwhile, DEXA showed a 23% reduction in the neck (baseline = 37.8%±0.05, week 24 = 29%±0.1), and a 26.5% reduction in the thigh (baseline = 11.2%±0.06, week 24 =8.3%±0.03). The change in fat percentages detected by MRI was similar compared to changes detected by DEXA in neck and thigh. Both methods showed good correlation in neck (r = 0.79, 95% CI = 0.18, 0.95, p=0.02) and thigh (r = 0.92, 95% CI = 0.60, 0.98, p=0.001). However, a high correlation does not imply agreement between the methods, therefore we performed Bland-Altman analyses to assess the agreement between the two methods. We found that the two methods were similar for the neck quantification (bias = 1.25, 95% CI = 0.81, 1.69), but not for the thigh quantification (bias = 1.85) with a wide limit of agreement (95% CI = -0.41, 4.11). Conclusions: Despite a difference between the average fat quantification from neck and thigh using MRI and DEXA, both methods show a strong correlation. Our data show a strong agreement between MRI and DEXA for neck fat quantification, but the same agreement was not seen in the thigh. Though preliminary, whole body MRI scans combined with ROI mapping can be utilized to determine precise fat quantification regionally and these methods can be useful during clinical trials testing impact of therapeutic agents on fat distribution. Further work is needed to provide more robust validation in a larger number of patients and across different trials. Presentation: Monday, July 14, 2025

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

Purpose To describe the design, conduct, and results of the Breast Multiparametric MRI for prediction of neoadjuvant chemotherapy Response (BMMR2) challenge. Materials and Methods The BMMR2 computational challenge opened on May 28, 2021, and closed on December 21, 2021. The goal of the challenge was to identify image-based markers derived from multiparametric breast MRI, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI, along with clinical data for predicting pathologic complete response (pCR) following neoadjuvant treatment. Data included 573 breast MRI studies from 191 women (mean age [±SD], 48.9 years ± 10.56) in the I-SPY 2/American College of Radiology Imaging Network (ACRIN) 6698 trial (ClinicalTrials.gov: NCT01042379). The challenge cohort was split into training (60%) and test (40%) sets, with teams blinded to test set pCR outcomes. Prediction performance was evaluated by area under the receiver operating characteristic curve (AUC) and compared with the benchmark established from the ACRIN 6698 primary analysis. Results Eight teams submitted final predictions. Entries from three teams had point estimators of AUC that were higher than the benchmark performance (AUC, 0.782 [95% CI: 0.670, 0.893], with AUCs of 0.803 [95% CI: 0.702, 0.904], 0.838 [95% CI: 0.748, 0.928], and 0.840 [95% CI: 0.748, 0.932]). A variety of approaches were used, ranging from extraction of individual features to deep learning and artificial intelligence methods, incorporating DCE and DWI alone or in combination. Conclusion The BMMR2 challenge identified several models with high predictive performance, which may further expand the value of multiparametric breast MRI as an early marker of treatment response. Clinical trial registration no. NCT01042379 Keywords: MRI, Breast, Tumor Response Supplemental material is available for this article. © RSNA, 2024.

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.

Muscle weakness following anterior cruciate ligament reconstruction (ACLR) increases the risk of posttraumatic osteoarthritis (OA). However, focusing solely on muscle weakness overlooks other aspects like muscle composition, which could hinder strength recovery. Intramuscular fat is a non-contractile element linked to joint degeneration in idiopathic OA, but its role post-ACLR has not been thoroughly investigated. To bridge this gap, we aimed to characterize quadriceps volume and intramuscular fat in participants with ACLR (male/female = 15/9, age = 22.8 ± 3.6 years, body mass index [BMI] = 23.2 ± 1.9, time since surgery = 3.3 ± 0.9 years) and in controls (male/female = 14/10, age = 22.0 ± 3.1 years, BMI = 23.3 ± 2.6) while also exploring the associations between intramuscular fat and muscle volume with isometric strength. Linear mixed effects models assessed (I) muscle volume, (II) intramuscular fat, and (III) strength between limbs (ACLR vs. contralateral vs. control). Regression analyses were run to determine if intramuscular fat or volume were associated with quadriceps strength. The ACLR limb was 8%-11% smaller than the contralateral limb (p < 0.05). No between-limb differences in intramuscular fat were observed (p = 0.091-0.997). Muscle volume but not intramuscular fat was associated with strength in the ACLR and control limbs (p < 0.001-0.002). We demonstrate that intramuscular fat does not appear to be an additional source of quadriceps dysfunction following ACLR and that muscle size only explains some of the variance in muscle strength.

The apparent diffusion coefficient (ADC) provides a quantitative measure of water mobility that can be used to probe alterations in tissue microstructure due to disease or treatment. Establishment of the accepted level of variance in ADC measurements for each clinical application is critical for its successful implementation. The Diffusion-Weighted Imaging Biomarker Committee of the Quantitative Imaging Biomarkers Alliance (QIBA) has recently advanced the ADC Profile from the consensus to clinically feasible stage for the brain, liver, prostate, and breast. This profile distills multiple studies on ADC repeatability and describes detailed procedures to achieve stated performance claims on an observed ADC change within acceptable confidence limits. In addition to reviewing the current ADC Profile claims, this report has used recent literature to develop proposed updates for establishing metrology benchmarks for mean lesion ADC change that account for measurement variance. Specifically, changes in mean ADC exceeding 8% for brain lesions, 27% for liver lesions, 27% for prostate lesions, and 15% for breast lesions are claimed to represent true changes with 95% confidence. This report also discusses the development of the ADC Profile, highlighting its various stages, and describes the workflow essential to achieving a standardized implementation of advanced quantitative diffusion-weighted MRI in the clinic. The presented QIBA ADC Profile guidelines should enable successful clinical application of ADC as a quantitative imaging biomarker and ensure reproducible ADC measurements that can be used to confidently evaluate longitudinal changes and treatment response for individual patients.

This review article discusses the role of MR imaging-based biomarkers in understanding and managing hemorrhagic strokes, focusing on intracerebral hemorrhage (ICH) and aneurysmal subarachnoid hemorrhage. ICH is a severe type of stroke with high mortality and morbidity rates, primarily caused by the rupture of small blood vessels in the brain, resulting in hematoma formation. MR imaging-based biomarkers, including brain iron quantification, ultra-early erythrolysis detection, and diffusion tensor imaging, offer valuable insights for hemorrhagic stroke management. These biomarkers could improve early diagnosis, risk stratification, treatment monitoring, and patient outcomes in the future, revolutionizing our approach to hemorrhagic strokes.

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.

To more fully realize the promise of advanced breast diffusion-weighted imaging (DWI) methods in the clinical environment, repeatability and reproducibility of quantitative diffusion-based imaging results need to be assessed and maximized across vendor platforms and clinical sites. Identification of sources of variability and their possible remediation should precede initiation of costly multicenter trials. In particular, gains in consistency are realized by standardization of DWI scan sequences performed across diverse hardware platforms. Standardization in image acquisition protocol includes not only specification of obvious top-level parameters such as b value set, gradient timing, and scan geometry but also secondary-level settings that impact image quality, such as those related to fat suppression, readout bandwidth, phase-encode echo-spacing, and acceleration options. In practice, vendor-specific terminology and default DWI sequence design vary with platform and present a significant challenge to standardization. Reasonably “harmonized” DWI acquisition protocols should be defined in parallel for each clinical scanner platform. Consideration for standardized image processing pipeline and analysis methods are also important. Use of a “central core lab” for image collection, potential vendor-specific DWI sorting and quantitative diffusion metric map generation, and consistency in downstream analysis support overall standardization. This chapter will address breast DWI performance evaluation for clinical applications, overview test objects for quality control, provide guidance on how to standardize DWI protocols, and control conditions toward accurate and reproducible results.