Identification of a single-dose, low flip angle based CBV threshold for fractional tumor burden (FTB) mapping in recurrent glioblastoma.

BACKGROUND AND PURPOSE: DSC-MRI can be used to generate fractional tumor burden (FTB) maps, via application of relative CBV thresholds, to spatially differentiate glioblastoma recurrence from post treatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MRI protocol using preload, a moderate flip angle (MFA, 60°) and post-processing leakage correction. Recently, a DSC-MRI protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected RCBV equivalent to the reference protocol. This study aims to identify the RCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol. MATERIALS AND METHODS: Fifty-two patients with grade IV GBM who had prior surgical resection and received chemotherapy and radiotherapy were included in the study. Two sets of DSC-MRI data were collected sequentially first using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and co-registered with the anatomical post-contrast T1-weighted images. The reference MFA-based FTB maps were computed using previously published sRCBV thresholds (1.0 and 1.56). An ROC analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference. RESULTS: The mean sRCBV values of tumors across patients exhibited strong agreement (CCC = 0.99) between the two protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56. CONCLUSION: For LFA-based FTB maps, a sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumor. FTB maps aids in surgical planning, guiding pathological diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MRI. ABBREVIATIONS: LFA = low flip angle; MFA = moderate flip angle; sRCBV = standardized relative cerebral blood volume; FTB = fractional tumor burden; PTRE = post treatment radiation effects; ROC = receiver operating characteristics; CCC = concordance correlation coefficient.

A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection.

PURPOSE: Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. METHODS: A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. RESULTS: Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. CONCLUSION: A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength.

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.

MRI and amino acid PET detection of whole-brain tumor burden.

Background: [18F]fluciclovine amino acid PET has shown promise for detecting brain tumor regions undetected on conventional anatomic MRI scans. However, it remains unclear which of these modalities provides a better assessment of the whole brain tumor burden. This study quantifies the performance of [18F]fluciclovine PET and MRI for detecting the whole brain tumor burden. Methods: Thirteen rats were orthotopically implanted with fluorescently transduced human glioblastoma cells. Rats underwent MRI (T1- and T2-weighted) and [18F]fluciclovine PET. Next brains were excised, optically cleared, and scanned ex vivo with fluorescence imaging. All images were co-registered using a novel landmark-based registration to enable a spatial comparison. The tumor burden identified on the fluorescent images was considered the ground truth for comparison with the in vivo imaging. Results: Across all cases, the PET sensitivity for detecting tumor burden (median 0.67) was not significantly different than MRI (combined T1+T2-weighted) sensitivity (median 0.61; p=0.85). However, the combined PET+MRI sensitivity (median 0.86) was significantly higher than MRI alone (41% higher; p=0.004) or PET alone (28% higher; p=0.0002). The specificity of combined PET+MRI (median=0.91) was significantly lower compared with MRI alone (6% lower; p=0.004) or PET alone (2% lower; p=0.002). Conclusion: In these glioblastoma xenografts, [18F]fluciclovine PET did not provide a significant increase in tumor burden detection relative to conventional anatomic MRI. However, a combined PET and MRI assessment did significantly improve detection sensitivity relative to either modality alone, suggesting potential value in a combined assessment for some tumors.

Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma.

Background: Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol. Methods: The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold. Results: The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%). Conclusions: The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities.

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Tracking glioblastoma progression after initial resection with minimal reaction-diffusion models.

We describe a preliminary effort to model the growth and progression of glioblastoma multiforme, an aggressive form of primary brain cancer, in patients undergoing treatment for recurrence of tumor following initial surgery and chemoradiation. Two reaction-diffusion models are used: the Fisher-Kolmogorov equation and a 2-population model, developed by the authors, that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor, using both models, contains at least 40 percent of the volume of the observed tumor. We discuss some potential improvements that can be made to the parameterizations of the models and their initialization.

Chronic Cognitive and Cerebrovascular Function after Mild Traumatic Brain Injury in Rats.

Severe traumatic brain injury (TBI) results in cognitive dysfunction in part due to vascular perturbations. In contrast, the long-term vasculo-cognitive pathophysiology of mild TBI (mTBI) remains unknown. We evaluated mTBI effects on chronic cognitive and cerebrovascular function and assessed their interrelationships. Sprague-Dawley rats received midline fluid percussion injury (n = 20) or sham (n = 21). Cognitive function was assessed (3- and 6-month novel object recognition [NOR], novel object location [NOL], and temporal order object recognition [TOR]). Six-month cerebral blood flow (CBF) and cerebral blood volume (CBV) using contrast magnetic resonance imaging (MRI) and ex vivo circle of Willis artery endothelial and smooth muscle-dependent function were measured. mTBI rats showed significantly impaired NOR, with similar trends (non-significant) in NOL/TOR. Regional CBF and CBV were similar in sham and mTBI. NOR correlated with CBF in lateral hippocampus, medial hippocampus, and primary somatosensory barrel cortex, whereas it inversely correlated with arterial smooth muscle-dependent dilation. Six-month baseline endothelial and smooth muscle-dependent arterial function were similar among mTBI and sham, but post-angiotensin 2 stimulation, mTBI showed no change in smooth muscle-dependent dilation from baseline response, unlike the reduction in sham. mTBI led to chronic cognitive dysfunction and altered angiotensin 2-stimulated smooth muscle-dependent vasoreactivity. The findings of persistent pathophysiological consequences of mTBI in this animal model add to the broader understanding of chronic pathophysiological sequelae in human mild TBI.

Imaging Glioblastoma With 18F-Fluciclovine Amino Acid Positron Emission Tomography.

INTRODUCTION: Conventional methods of imaging brain tumors fail to assess metabolically active tumor regions, which limits their capabilities for tumor detection, localization, and response assessment. Positron emission tomography (PET) with 18F-fluciclovine (fluciclovine) provides regional assessment of amino acid uptake in tumors that could overcome some of the limitations of conventional imaging. However, the biological basis of enhanced fluciclovine uptake is insufficiently characterized in brain tumors, which confounds clinical interpretation and application. This study sought to address this gap by correlating multiple biologic quantities with fluciclovine PET uptake across a range of human glioblastoma xenograft models. METHODS: Thirty-one rats underwent orthotopic implantations with one of five different human glioblastoma cell lines. After tumors were established, fluciclovine PET and magnetic resonance imaging (MRI) scans were performed. The fluciclovine tumor-to-normal-brain (TN) uptake ratio was used to quantify fluciclovine uptake. MRI scans were used to assess tumor volume and gadolinium enhancement status. Histologic assessments quantified tumor cell proliferation, tumor cell density, and tumor cell amino acid transporters (LAT1 and ASCT2). Multivariate linear regression models related fluciclovine uptake with the other measured quantities. RESULTS: Within the multivariate regression, the fluciclovine TN uptake ratio (measured 15 to 35 minutes after fluciclovine injection) was most strongly associated with tumor ASCT2 levels (ß=0.64; P=0.001). The fluciclovine TN uptake ratio was also significantly associated with tumor volume (ß=0.45; P=0.001) and tumor enhancement status (ß=0.40; P=0.01). Tumor cell proliferation, tumor cell density, and LAT1 levels were not significantly associated with fluciclovine uptake in any of the multivariate models. In general, both enhancing and non-enhancing tumors could be visualized on fluciclovine PET images, with the median TN uptake ratio across the five tumor lines being 2.4 (range 1.1 to 8.9). CONCLUSIONS: Increased fluciclovine PET uptake was associated with increased levels of the amino acid transporter ASCT2, suggesting fluciclovine PET may be useful for assessing brain tumor amino acid metabolism. Fluciclovine PET uptake was elevated in both enhancing and non-enhancing tumors but the degree of uptake was greater in larger tumors and tumors with enhancement, indicating these variables could confound fluciclovine metabolic measurements if not accounted for.

Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions.

In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.

Longitudinal evaluation of myofiber microstructural changes in a preclinical ALS model using the transverse relaxivity at tracer equilibrium (TRATE): A preliminary study.

T2⁎ relaxivity contrast imaging may serve as a potential imaging biomarker for amyotrophic lateral sclerosis (ALS) by noninvasively quantifying the tissue microstructure. In this preliminary longitudinal study, we investigated the Transverse Relaxivity at Tracer Equilibrium (TRATE) in three muscle groups between SOD1-G93A (ALS model) rat and a control population at two different timepoints. The control group was time matched to the ALS group such that the second timepoint was the onset of disease. We observed a statistically significant decrease in TRATE over time in the gastrocnemius, tibialis, and digital flexor muscles in the SOD1-G93A model (p-value = 0.003, 0.008, 0.005; respectively), whereas TRATE did not change over time in the control group (p-value = 0.4777, 0.6837, 0.9682; respectively). Immunofluorescent staining revealed a decrease in minimum fiber area and cell density in the SOD1-G93A model when compared to the control group (p-value = 6.043E-10 and 2.265E-10, respectively). These microstructural changes observed from histology align with the theorized biophysical properties of TRATE. We demonstrate that TRATE can longitudinally differentiate disease associated atrophy from healthy muscle and has potential to serve as a biomarker for disease progression and ultimately therapy response in patients with ALS.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients.

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.

Development of a spiral spin- and gradient-echo (spiral-SAGE) approach for improved multi-parametric dynamic contrast neuroimaging.

PURPOSE: The purpose of this study was to develop a spiral-based combined spin- and gradient-echo (spiral-SAGE) method for simultaneous dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI). METHODS: Using this sequence, we obtained gradient-echo TEs of 1.69 and 26 ms, a SE TE of 87.72 ms, with a TR of 1663 ms. Using an iterative SENSE reconstruction followed by deblurring, spiral-induced image artifacts were minimized. Healthy volunteer images are shown to demonstrate image quality using the optimized reconstruction, as well as for comparison with EPI-based SAGE. A bioreactor phantom was used to compare dynamic-contrast time courses with both spiral-SAGE and EPI-SAGE. A proof-of-concept cohort of patients with brain tumors shows the range of hemodynamic maps available using spiral-SAGE. RESULTS: Comparison of spiral-SAGE images with conventional EPI-SAGE images illustrates substantial reductions of image distortion and artifactual image intensity variations. Bioreactor phantom data show similar dynamic contrast time courses between standard EPI-SAGE and spiral-SAGE for the second and third echoes, whereas first-echo data show improvements in quantifying T1 changes with shorter echo times. In a cohort of patients with brain tumors, spiral-SAGE-based perfusion and permeability maps are shown with comparison with the standard single-echo EPI perfusion map. CONCLUSION: Spiral-SAGE provides a substantial improvement for the assessment of perfusion and permeability by mitigating artifacts typically encountered with EPI and by providing a shorter echo time for improved characterization of permeability. Spiral-SAGE enables quantification of perfusion, permeability, and vessel architectural parameters, as demonstrated in brain tumors.

Evaluation of Amyotrophic Lateral Sclerosis-Induced Muscle Degeneration Using Magnetic Resonance-Based Relaxivity Contrast Imaging (RCI).

(1) Background: This work characterizes the sensitivity of magnetic resonance-based Relaxivity Contrast Imaging (RCI) to Amyotrophic Lateral Sclerosis (ALS)-induced changes in myofiber microstructure. Transverse Relaxivity at Tracer Equilibrium (TRATE), an RCI-based parameter, was evaluated in the lower extremities of ALS patients and healthy subjects. (2) Methods: In this IRB-approved study, 23 subjects (12 ALS patients and 11 healthy controls) were scanned at 3T (Philips, The Netherlands). RCI data were obtained during injection of a gadolinium-based contrast agent. TRATE, fat fraction and T2 measures, were compared in five muscle groups of the calf muscle, between ALS and control populations. TRATE was also evaluated longitudinally (baseline and 6 months) and was compared to clinical measures, namely ALS Functional Rating Scale (ALSFRS-R) and Hand-Held Dynamometry (HHD), in a subset of the ALS population. (3) Results: TRATE was significantly lower (p < 0.001) in ALS-affected muscle than in healthy muscle in all muscle groups. Fat fraction differences between ALS and healthy muscle were statistically significant for the tibialis anterior (p = 0.01), tibialis posterior (p = 0.004), and peroneus longus (p = 0.02) muscle groups but were not statistically significant for the medial (p = 0.07) and lateral gastrocnemius (p = 0.06) muscles. T2 differences between ALS and healthy muscle were statistically significant for the tibialis anterior (p = 0.004), peroneus longus (p = 0.004) and lateral gastrocnemius (p = 0.03) muscle groups but were not statistically significant for the tibialis posterior (p = 0.06) and medial gastrocnemius (p = 0.07) muscles. Longitudinally, TRATE, averaged over all patients, decreased by 28 ± 16% in the tibialis anterior, 47 ± 18% in the peroneus longus, 25 ± 19% in the tibialis posterior, 29 ± 14% in the medial gastrocnemius and 35 ± 18% in the lateral gastrocnemius muscles between two timepoints. ALSFRS-R scores were stable in two of four ALS patients. HHD scores decreased in three of four ALS patients. (4) Conclusion: RCI-based TRATE was shown to consistently differentiate ALS-affected muscle from healthy muscle and also provide a quantitative measure of longitudinal muscle degeneration.

Consensus recommendations for MRI and PET imaging of primary central nervous system lymphoma: guideline statement from the International Primary CNS Lymphoma Collaborative Group (IPCG).

Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both "ideal" and "minimum standard" protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.

Correlation of Tumor Hypoxia Metrics Derived from 18F-Fluoromisonidazole Positron Emission Tomography and Pimonidazole Fluorescence Images of Optically Cleared Brain Tissue.

18F-fluoromisonidazole (FMISO) positron emission tomography (PET) is a widely used noninvasive imaging modality for assessing hypoxia. We describe the first spatial comparison of FMISO PET with an ex vivo reference standard for hypoxia across whole tumor volumes. Eighteen rats were orthotopically implanted with C6 or 9L brain tumors and made to undergo FMISO PET scanning. Whole brains were excised, sliced into 1-mm-thick sections, optically cleared, and fluorescently imaged for pimonidazole using an in vivo imaging system. FMISO maximum tumor uptake, maximum tumor-to-cerebellar uptake (TCmax), and hypoxic fraction (extracted 110 minutes after FMISO injection) were correlated with analogous metrics derived from pimonidazole fluorescence images. FMISO SUVmax was not significantly different between C6 and 9L brain tumors (P = .70), whereas FMISO TCmax and hypoxic fraction were significantly greater for C6 tumors (P < .01). FMISO TCmax was significantly correlated with the maximum tumor pimonidazole intensity (ρ = 0.76, P < .01), whereas FMISO SUVmax was not. FMISO tumor hypoxic fraction was significantly correlated with the pimonidazole-derived hypoxic fraction (ρ = 0.78, P < .01). Given that FMISO TCmax and tumor hypoxic fraction had strong correlations with the pimonidazole reference standard, these metrics may offer more reliable measures of tumor hypoxia than conventional PET uptake metrics (SUVmax). The voxel-wise correlation between FMISO uptake and pimonidazole intensity for a given tumor was strongly dependent on the tumor's TCmax (ρ = 0.81, P < .01) and hypoxic fraction (ρ = 0.85, P < .01), indicating PET measurements within individual voxels showed greater correlation with pimonidazole reference standard in tumors with greater hypoxia.

Imaging for Response Assessment in Cancer Clinical Trials.

The use of biomarkers is integral to the routine management of cancer patients, including diagnosis of disease, clinical staging and response to therapeutic intervention. Advanced imaging metrics with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are used to assess response during new drug development and in cancer research for predictive metrics of response. Key components and challenges to identifying an appropriate imaging biomarker are selection of integral vs integrated biomarkers, choosing an appropriate endpoint and modality, and standardization of the imaging biomarkers for cooperative and multicenter trials. Imaging biomarkers lean on the original proposed quantified metrics derived from imaging such as tumor size or longest dimension, with the most commonly implemented metrics in clinical trials coming from the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and then adapted versions such as immune-RECIST (iRECIST) and Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) for immunotherapy response and PET imaging, respectively. There have been many widely adopted biomarkers in clinical trials derived from MRI including metrics that describe cellularity and vascularity from diffusion-weighted (DW)-MRI apparent diffusion coefficient (ADC) and Dynamic Susceptibility Contrast (DSC) or dynamic contrast enhanced (DCE)-MRI (Ktrans, relative cerebral blood volume (rCBV)), respectively. Furthermore, Fluorodexoyglucose (FDG), fluorothymidine (FLT), and fluoromisonidazole (FMISO)-PET imaging, which describe molecular markers of glucose metabolism, proliferation and hypoxia have been implemented into various cancer types to assess therapeutic response to a wide variety of targeted- and chemotherapies. Recently, there have been many functional and molecular novel imaging biomarkers that are being developed that are rapidly being integrated into clinical trials (with anticipation of being implemented into clinical workflow in the future), such as artificial intelligence (AI) and machine learning computational strategies, antibody and peptide specific molecular imaging, and advanced diffusion MRI. These include prostate-specific membrane antigen (PSMA) and trastuzumab-PET, vascular tumor burden extracted from contrast-enhanced CT, diffusion kurtosis imaging, and CD8 or Granzyme B PET imaging. Further excitement surrounds theranostic procedures such as the combination of 68Ga/111In- and 177Lu-DOTATATE to use integral biomarkers to direct care and personalize therapy. However, there are many challenges in the implementation of imaging biomarkers that remains, including understand the accuracy, repeatability and reproducibility of both acquisition and analysis of these imaging biomarkers. Despite the challenges associated with the biological and technical validation of novel imaging biomarkers, a distinct roadmap has been created that is being implemented into many clinical trials to advance the development and implementation to create specific and sensitive novel imaging biomarkers of therapeutic response to continue to transform medical oncology.

Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge.

We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking.

Analysis of postprocessing steps for residue function dependent dynamic susceptibility contrast (DSC)-MRI biomarkers and their clinical impact on glioma grading for both 1.5 and 3T.

BACKGROUND: Dynamic susceptibility contrast (DSC)-MRI analysis pipelines differ across studies and sites, potentially confounding the clinical value and use of the derived biomarkers. PURPOSE/HYPOTHESIS: To investigate how postprocessing steps for computation of cerebral blood volume (CBV) and residue function dependent parameters (cerebral blood flow [CBF], mean transit time [MTT], capillary transit heterogeneity [CTH]) impact glioma grading. STUDY TYPE: Retrospective study from The Cancer Imaging Archive (TCIA). POPULATION: Forty-nine subjects with low- and high-grade gliomas. FIELD STRENGTH/SEQUENCE: 1.5 and 3.0T clinical systems using a single-echo echo planar imaging (EPI) acquisition. ASSESSMENT: Manual regions of interest (ROIs) were provided by TCIA and automatically segmented ROIs were generated by k-means clustering. CBV was calculated based on conventional equations. Residue function dependent biomarkers (CBF, MTT, CTH) were found by two deconvolution methods: circular discretization followed by a signal-to-noise ratio (SNR)-adapted eigenvalue thresholding (Method 1) and Volterra discretization with L-curve-based Tikhonov regularization (Method 2). STATISTICAL TESTS: Analysis of variance, receiver operating characteristics (ROC), and logistic regression tests. RESULTS: MTT alone was unable to statistically differentiate glioma grade (P > 0.139). When normalized, tumor CBF, CTH, and CBV did not differ across field strengths (P > 0.141). Biomarkers normalized to automatically segmented regions performed equally (rCTH AUROC is 0.73 compared with 0.74) or better (rCBF AUROC increases from 0.74-0.84; rCBV AUROC increases 0.78-0.86) than manually drawn ROIs. By updating the current deconvolution steps (Method 2), rCTH can act as a classifier for glioma grade (P < 0.007), but not if processed by current conventional DSC methods (Method 1) (P > 0.577). Lastly, higher-order biomarkers (eg, rCBF and rCTH) along with rCBV increases AUROC to 0.92 for differentiating tumor grade as compared with 0.78 and 0.86 (manual and automatic reference regions, respectively) for rCBV alone. DATA CONCLUSION: With optimized analysis pipelines, higher-order perfusion biomarkers (rCBF and rCTH) improve glioma grading as compared with CBV alone. Additionally, postprocessing steps impact thresholds needed for glioma grading. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:547-553.