A pharmacokinetic model for hyperpolarized 13C-pyruvate MRI when using metabolite-specific bSSFP sequences.

PURPOSE: Metabolite-specific balanced SSFP (MS-bSSFP) sequences are increasingly used in hyperpolarized [1-13C]Pyruvate (HP 13C) MRI studies as they improve SNR by refocusing the magnetization each TR. Currently, pharmacokinetic models used to fit conversion rate constants, kPL and kPB, and rate constant maps do not account for differences in the signal evolution of MS-bSSFP acquisitions. METHODS: In this work, a flexible MS-bSSFP model was built that can be used to fit conversion rate constants for these experiments. The model was validated in vivo using paired animal (healthy rat kidneys n = 8, transgenic adenocarcinoma of the mouse prostate n = 3) and human renal cell carcinoma (n = 3) datasets. Gradient echo (GRE) acquisitions were used with a previous GRE model to compare to the results of the proposed GRE-bSSFP model. RESULTS: Within simulations, the proposed GRE-bSSFP model fits the simulated data well, whereas a GRE model shows bias because of model mismatch. For the in vivo datasets, the estimated conversion rate constants using the proposed GRE-bSSFP model are consistent with a previous GRE model. Jointly fitting the lactate T2 with kPL resulted in less precise kPL estimates. CONCLUSION: The proposed GRE-bSSFP model provides a method to estimate conversion rate constants, kPL and kPB, for MS-bSSFP HP 13C experiments. This model may also be modified and used for other applications, for example, estimating rate constants with other hyperpolarized reagents or multi-echo bSSFP.

Mixed Supervision of Histopathology Improves Prostate Cancer Classification from MRI.

Non-invasive prostate cancer classification from MRI has the potential to revolutionize patient care by providing early detection of clinically significant disease, but has thus far shown limited positive predictive value. To address this, we present a image-based deep learning method to predict clinically significant prostate cancer from screening MRI in patients that subsequently underwent biopsy with results ranging from benign pathology to the highest grade tumors. Specifically, we demonstrate that mixed supervision via diverse histopathological ground truth improves classification performance despite the cost of reduced concordance with image-based segmentation. Where prior approaches have utilized pathology results as ground truth derived from targeted biopsies and whole-mount prostatectomy to strongly supervise the localization of clinically significant cancer, our approach also utilizes weak supervision signals extracted from nontargeted systematic biopsies with regional localization to improve overall performance. Our key innovation is performing regression by distribution rather than simply by value, enabling use of additional pathology findings traditionally ignored by deep learning strategies. We evaluated our model on a dataset of 973 (testing n = 198) multi-parametric prostate MRI exams collected at UCSF from 2016-2019 followed by MRI/ultrasound fusion (targeted) biopsy and systematic (nontargeted) biopsy of the prostate gland, demonstrating that deep networks trained with mixed supervision of histopathology can feasibly exceed the performance of the Prostate Imaging-Reporting and Data System (PI-RADS) clinical standard for prostate MRI interpretation (71.6% vs 66.7% balanced accuracy and 0.724 vs 0.716 AUC).

Current methods for hyperpolarized [1-13C]pyruvate MRI human studies.

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of HP agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate-by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation; (2) MRI system setup and calibrations; (3) data acquisition and image reconstruction; and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the "HP 13C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods and Equipment study groups. It further aims to provide a comprehensive reference for future consensus, building as the field continues to advance human studies with this metabolic imaging modality.

Hyperpolarized 13 C metabolic imaging of the human abdomen with spatiotemporal denoising.

PURPOSE: Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach. METHODS: Denoising performance was first evaluated using the simulated [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients). RESULTS: The parameterization of kglobal = 0.2 and klocal = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (conversion rate of pyruvate-to-metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground-truth metabolic conversion rates when there is adequate SNR (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5-fold increase in the number of voxels reliably fit across abdominal FOVs for kPL and kPA quantification maps. CONCLUSION: Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach.

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

Dynamic T 2 * relaxometry of hyperpolarized [1-13 C]pyruvate MRI in the human brain and kidneys.

PURPOSE: This study aimed to quantify T 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T. METHODS: Dynamic T 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamic T 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients. T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimated T 2 * $$ {T}_2^{\ast } $$ correction. RESULTS: The T 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas the T 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. The T 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and the T 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). The T 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys. CONCLUSION: Multi-echo dynamic imaging can quantify T 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in the T 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.

Hyperpolarized 13 C Metabolic MRI of Patients with Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related death in the United States. However, early response assessment using the current approach of measuring changes in tumor size on computed tomography (CT) or MRI is challenging. PURPOSE: To investigate the feasibility of hyperpolarized (HP) [1-13 C]pyruvate MRI to quantify metabolism in the normal appearing pancreas and PDA, and to assess changes in PDA metabolism following systemic chemotherapy. STUDY TYPE: Prospective. SUBJECTS: Six patients (65.0 ± 7.6 years, 2 females) with locally advanced or metastatic PDA enrolled prior to starting a new line of systemic chemotherapy. FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted gradient echo, metabolite-selective 13 C echoplanar imaging. ASSESSMENT: Time-resolved HP [1-13 C]pyruvate data were acquired before (N = 6) and 4-weeks after (N = 3) treatment initiation. Pyruvate metabolism, as quantified by pharmacokinetic modeling and metabolite area-under-the-curve ratios, was assessed in manually segmented PDA and normal appearing pancreas ROIs (N = 5). The change in tumor metabolism before and 4-weeks after treatment initiation was assessed in primary PDA (N = 2) and liver metastases (N = 1), and was compared to objective tumor response defined by response evaluation criteria in solid tumors (RECIST) on subsequent CTs. STATISTICAL TESTS: Descriptive tests (mean ± standard deviation), model fit error for pharmacokinetic rate constants. RESULTS: Primary PDA showed reduced alanine-to-lactate ratios when compared to normal pancreas, due to increased lactate-to-pyruvate or reduced alanine-to-pyruvate ratios. Of the three patients who received HP [1-13 C]pyruvate MRI before and 4-weeks after treatment initiation, one patient had a primary tumor with early metabolic response (increase in alanine-to-lactate) and subsequent partial response according to RECIST, one patient had a primary tumor with relatively stable metabolism and subsequent stable disease by RECIST, and one patient had metastatic PDA with increase in lactate-to-pyruvate of the liver metastases and corresponding progressive disease according to RECIST. DATA CONCLUSION: Altered pyruvate metabolism with increased lactate or reduced alanine was observed in the primary tumor. Early metabolic response assessed at 4-weeks after treatment initiation correlated with subsequent objective tumor response assessed using RECIST. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Clinically Translatable Hyperpolarized 13C Bicarbonate pH Imaging Method for Use in Prostate Cancer.

Solid tumors such as prostate cancer (PCa) commonly develop an acidic microenvironment with pH 6.5-7.2, owing to heterogeneous perfusion, high metabolic activity, and rapid cell proliferation. In preclinical prostate cancer models, disease progression is associated with a decrease in tumor extracellular pH, suggesting that pH imaging may reflect an imaging biomarker to detect aggressive and high-risk disease. Therefore, we developed a hyperpolarized carbon-13 MRI method to image the tumor extracellular pH (pHe) and prepared it for clinical translation for detection and risk stratification of PCa. This method relies on the rapid breakdown of hyperpolarized (HP) 1,2-glycerol carbonate (carbonyl-13C) via base-catalyzed hydrolysis to produce HP 13CO32-, which is neutralized and converted to HP H13CO3-. After injection, HP H13CO3- equilibrates with HP 13CO2 in vivo and enables the imaging of pHe. Using insights gleaned from mechanistic studies performed in the hyperpolarized state, we solved issues of polarization loss during preparation in a clinical polarizer system. We successfully customized a reaction apparatus suitable for clinical application, developed clinical standard operating procedures, and validated the radiofrequency pulse sequence and imaging data acquisition with a wide range of animal models. The results demonstrated that we can routinely produce a highly polarized and safe HP H13CO3- contrast agent suitable for human injection. Preclinical imaging studies validated the reliability and accuracy of measuring acidification in healthy kidney and prostate tumor tissue. These methods were used to support an Investigational New Drug application to the U.S. Food and Drug Administration. This methodology is now ready to be implemented in human trials, with the ultimate goal of improving the management of PCa.

Multi-parametric hyperpolarized 13C/1H imaging reveals Warburg-related metabolic dysfunction and associated regional heterogeneity in high-grade human gliomas.

BACKGROUND: Dynamic hyperpolarized (HP)-13C MRI has enabled real-time, non-invasive assessment of Warburg-related metabolic dysregulation in glioma using a [1-13C]pyruvate tracer that undergoes conversion to [1-13C]lactate and [13C]bicarbonate. Using a multi-parametric 1H/HP-13C imaging approach, we investigated dynamic and steady-state metabolism, together with physiological parameters, in high-grade gliomas to characterize active tumor. METHODS: Multi-parametric 1H/HP-13C MRI data were acquired from fifteen patients with progressive/treatment-naïve glioblastoma [prog/TN GBM, IDH-wildtype (n = 11)], progressive astrocytoma, IDH-mutant, grade 4 (G4AIDH+, n = 2) and GBM manifesting treatment effects (n = 2). Voxel-wise regional analysis of the cohort with prog/TN GBM assessed imaging heterogeneity across contrast-enhancing/non-enhancing lesions (CEL/NEL) and normal-appearing white matter (NAWM) using a mixed effects model. To enable cross-nucleus parameter association, normalized perfusion, diffusion, and dynamic/steady-state (HP-13C/spectroscopic) metabolic data were collectively examined at the 13C resolution. Prog/TN GBM were similarly compared against progressive G4AIDH+ and treatment effects. RESULTS: Regional analysis of Prog/TN GBM metabolism revealed statistically significant heterogeneity in 1H choline-to-N-acetylaspartate index (CNI)max, [1-13C]lactate, modified [1-13C]lactate-to-[1-13C]pyruvate ratio (CELval > NELval > NAWMval); [1-13C]lactate-to-[13C]bicarbonate ratio (CELval > NELval/NAWMval); and 1H-lactate (CELval/NELval > NAWMundetected). Significant associations were found between normalized perfusion (cerebral blood volume, nCBV; peak height, nPH) and levels of [1-13C]pyruvate and [1-13C]lactate, as well as between CNImax and levels of [1-13C]pyruvate, [1-13C]lactate and modified ratio. GBM, by comparison to G4AIDH+, displayed lower perfusion %-recovery and modeled rate constants for [1-13C]pyruvate-to-[1-13C]lactate conversion (kPL), and higher 1H-lactate and [1-13C]pyruvate levels, while having higher nCBV, %-recovery, kPL, [1-13C]pyruvate-to-[1-13C]lactate and modified ratios relative to treatment effects. CONCLUSIONS: GBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.

A metabolite specific 3D stack-of-spirals bSSFP sequence for improved bicarbonate imaging in hyperpolarized [1-13C]Pyruvate MRI.

13C-bicarbonate is a crucial measure of pyruvate oxidation and TCA cycle flux, but is challenging to measure due to its relatively low concentration and thus will greatly benefit from improved signal-to-noise ratio (SNR). To address this, we developed and investigated the feasibility of a 3D stack-of-spirals metabolite-specific balanced steady-state free precession (MS-bSSFP) sequence for improving the SNR and spatial resolution of dynamic 13C-bicarbonate imaging in hyperpolarized [1-13C]pyruvate studies. The bicarbonate MS-bSSFP sequence was evaluated by simulations, phantoms studies, preclinical studies on five rats, brain studies on two healthy volunteers and renal study on one renal cell carcinoma patient. The simulations and phantom results showed that the bicarbonate-specific pulse had minimal perturbation of other metabolites (<1%). In the animal studies, the MS-bSSFP sequence provided an approximately 2.6-3 × improvement in 13C-bicarbonate SNR compared to a metabolite-specific gradient echo (MS-GRE) sequence without altering the bicarbonate or pyruvate kinetics, and the shorter spiral readout in the MS-bSSFP approach reduced blurring. Using the SNR ratio between MS-bSSFP and MS-GRE, the T2 values of bicarbonate and lactate in the rat kidneys were estimated as 0.5 s and 1.1 s, respectively. The in-vivo feasibility of bicarbonate MS-bSSFP sequence was demonstrated in two human brain studies and one renal study. These studies demonstrate the potential of the sequence for in-vivo applications, laying the foundation for future studies to observe this relatively low concentration metabolite with high-quality images and improve measurements of pyruvate oxidation.

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.

Metabolite-Specific Echo Planar Imaging for Preclinical Studies with Hyperpolarized 13C-Pyruvate MRI.

Metabolite-specific echo-planar imaging (EPI) sequences with spectral-spatial (spsp) excitation are commonly used in clinical hyperpolarized [1-13C]pyruvate studies because of their speed, efficiency, and flexibility. In contrast, preclinical systems typically rely on slower spectroscopic methods, such as chemical shift imaging (CSI). In this study, a 2D spspEPI sequence was developed for use on a preclinical 3T Bruker system and tested on in vivo mice experiments with patient-derived xenograft renal cell carcinoma (RCC) or prostate cancer tissues implanted in the kidney or liver. Compared to spspEPI sequences, CSI were found to have a broader point spread function via simulations and exhibited signal bleeding between vasculature and tumors in vivo. Parameters for the spspEPI sequence were optimized using simulations and verified with in vivo data. The expected lactate SNR and pharmacokinetic modeling accuracy increased with lower pyruvate flip angles (less than 15°), intermediate lactate flip angles (25° to 40°), and temporal resolution of 3 s. Overall SNR was also higher with coarser spatial resolution (4 mm isotropic vs. 2 mm isotropic). Pharmacokinetic modelling used to fit kPL maps showed results consistent with the previous literature and across different sequences and tumor xenografts. This work describes and justifies the pulse design and parameter choices for preclinical spspEPI hyperpolarized 13C-pyruvate studies and shows superior image quality to CSI.

Federated Learning with Research Prototypes: Application to Multi-Center MRI-based Detection of Prostate Cancer with Diverse Histopathology.

RATIONALE AND OBJECTIVES: Early prostate cancer detection and staging from MRI is extremely challenging for both radiologists and deep learning algorithms, but the potential to learn from large and diverse datasets remains a promising avenue to increase their performance within and across institutions. To enable this for prototype-stage algorithms, where the majority of existing research remains, we introduce a flexible federated learning framework for cross-site training, validation, and evaluation of custom deep learning prostate cancer detection algorithms. MATERIALS AND METHODS: We introduce an abstraction of prostate cancer groundtruth that represents diverse annotation and histopathology data. We maximize use of this groundtruth if and when they are available using UCNet, a custom 3D UNet that enables simultaneous supervision of pixel-wise, region-wise, and gland-wise classification. We leverage these modules to perform cross-site federated training using 1400+ heterogeneous multi-parameteric prostate MRI exams from two University hospitals. RESULTS: We observe a positive result, with significant improvements in cross-site generalization performance with negligible intra-site performance degradation for both lesion segmentation and per-lesion binary classification of clinically-significant prostate cancer. Cross-site lesion segmentation performance intersection-over-union (IoU) improved by 100%, while cross-site lesion classification performance overall accuracy improved by 9.5-14.8%, depending on the optimal checkpoint selected by each site. CONCLUSION: Federated learning can improve the generalization performance of prostate cancer detection models across institutions while protecting patient health information and institution-specific code and data. However, even more data and participating institutions are likely required to improve the absolute performance of prostate cancer classification models. To enable adoption of federated learning with limited re-engineering of federated components, we open-source our FLtools system at https://federated.ucsf.edu, including examples that can be easily adapted to other medical imaging deep learning projects.

A 13C/31P surface coil to visualize metabolism and energetics in the rodent brain at 3 Tesla.

PURPOSE: We constructed a 13C/31P surface coil at 3 T for studying cancer metabolism and bioenergetics. In a single scan session, hyperpolarized 13C-pyruvate MRS and 31P MRS was carried out for a healthy rat brain. METHODS: All experiments were carried out at 3 Tesla. The multinuclear surface coil was designed as two coplanar loops each tuned to either the 13C or 31P operating frequency with an LCC trap on the 13C loop. A commercial volume proton coil was used for anatomical localization and B0 shimming. Single tuned coils operating at either the 13C or 31P frequency were built to evaluate the relative performance of the multinuclear coil. Coil performance metrics consisted of measuring Q factor ratio, calculating system input power using a single-pulse acquisition, and acquiring SNR and flip angle maps using 2D CSI sequences. To observe in vivo spectra, a bolus of hyperpolarized [1-13C] pyruvate was administered via tail vein. In vivo13C and endogenous 31P spectra were obtained in a single scan session using 1D slice selective acquisitions. RESULTS: When compared with single tuned surface coils, the multinuclear coil performance showed a decrease in Q factor ratio, SNR, and transmit efficiency. Flip angle maps showed adequate flip angles within the phantom when the transmit voltage was set using an external phantom. Results show good detection of 13C labeled lactate, alanine, and bicarbonate in addition to ATP from 31P MRS. CONCLUSIONS: The coil enables obtaining complementary information within a scan session, thus reducing the number of trials and minimizing biological variability for studies of metabolism and bioenergetics.

Improving multiparametric MR-transrectal ultrasound guided fusion prostate biopsies with hyperpolarized 13 C pyruvate metabolic imaging: A technical development study.

PURPOSE: To develop techniques and establish a workflow using hyperpolarized carbon-13 (13 C) MRI and the pyruvate-to-lactate conversion rate (kPL ) biomarker to guide MR-transrectal ultrasound fusion prostate biopsies. METHODS: The integrated multiparametric MRI (mpMRI) exam consisted of a 1-min hyperpolarized 13 C-pyruvate EPI acquisition added to a conventional prostate mpMRI exam. Maps of kPL values were calculated, uploaded to a picture archiving and communication system and targeting platform, and displayed as color overlays on T2 -weighted anatomic images. Abdominal radiologists identified 13 C research biopsy targets based on the general recommendation of focal lesions with kPL >0.02(s-1 ), and created a targeting report for each study. Urologists conducted transrectal ultrasound-guided MR fusion biopsies, including the standard 1 H-mpMRI targets as well as 12-14 core systematic biopsies informed by the research 13 C-kPL targets. All biopsy results were included in the final pathology report and calculated toward clinical risk. RESULTS: This study demonstrated the safety and technical feasibility of integrating hyperpolarized 13 C metabolic targeting into routine 1 H-mpMRI and transrectal ultrasound fusion biopsy workflows, evaluated via 5 men (median age 71 years, prostate-specific antigen 8.4 ng/mL, Cancer of the Prostate Risk Assessment score 2) on active surveillance undergoing integrated scan and subsequent biopsies. No adverse event was reported. Median turnaround time was less than 3 days from scan to 13 C-kPL targeting, and scan-to-biopsy time was 2 weeks. Median number of 13 C targets was 1 (range: 1-2) per patient, measuring 1.0 cm (range: 0.6-1.9) in diameter, with a median kPL of 0.0319 s-1 (range: 0.0198-0.0410). CONCLUSIONS: This proof-of-concept work demonstrated the safety and feasibility of integrating hyperpolarized 13 C MR biomarkers to the standard mpMRI workflow to guide MR-transrectal ultrasound fusion biopsies.

Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1-13C]pyruvate MRI data from patients with glioma.

BACKGROUND: Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma. METHODS: Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared. RESULTS: Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD). CONCLUSION: Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.

Development of specialized magnetic resonance acquisition techniques for human hyperpolarized [13 C,15 N2 ]urea + [1-13 C]pyruvate simultaneous perfusion and metabolic imaging.

PURPOSE: This study aimed to develop and demonstrate the in vivo feasibility of a 3D stack-of-spiral balanced steady-state free precession(3D-bSSFP) urea sequence, interleaved with a metabolite-specific gradient echo (GRE) sequence for pyruvate and metabolic products, for improving the SNR and spatial resolution of the first hyperpolarized 13 C-MRI human study with injection of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea. METHODS: A metabolite-specific bSSFP urea imaging sequence was designed using a urea-specific excitation pulse, optimized TR, and 3D stack-of-spiral readouts. Simulations and phantom studies were performed to validate the spectral response of the sequence. The image quality of urea data acquired by the 3D-bSSFP sequence and the 2D-GRE sequence was evaluated with 2 identical injections of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea formula in a rat. Subsequently, the feasibility of the acquisition strategy was validated in a prostate cancer patient. RESULTS: Simulations and phantom studies demonstrated that 3D-bSSFP sequence achieved urea-only excitation, while minimally perturbing other metabolites (<1%). An animal study demonstrated that compared to GRE, bSSFP sequence provided an ∼2.5-fold improvement in SNR without perturbing urea or pyruvate kinetics, and bSSFP approach with a shorter spiral readout reduced blurring artifacts caused by J-coupling of [13 C,15 N2 ]urea. The human study demonstrated the in vivo feasibility and data quality of the acquisition strategy. CONCLUSION: The 3D-bSSFP urea sequence with a stack-of-spiral acquisition demonstrated significantly increased SNR and image quality for [13 C,15 N2 ]urea in co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea imaging studies. This work lays the foundation for future human studies to achieve high-quality and high-SNR metabolism and perfusion images.

Whole-Abdomen Metabolic Imaging of Healthy Volunteers Using Hyperpolarized [1-13 C]pyruvate MRI.

BACKGROUND: Hyperpolarized 13 C MRI quantitatively measures enzyme-catalyzed metabolism in cancer and metabolic diseases. Whole-abdomen imaging will permit dynamic metabolic imaging of several abdominal organs simultaneously in healthy and diseased subjects. PURPOSE: Image hyperpolarized [1-13 C]pyruvate and products in the abdomens of healthy volunteers, overcoming challenges of motion, magnetic field variations, and spatial coverage. Compare hyperpolarized [1-13 C]pyruvate metabolism across abdominal organs of healthy volunteers. STUDY TYPE: Prospective technical development. SUBJECTS: A total of 13 healthy volunteers (8 male), 21-64 years (median 36). FIELD STRENGTH/SEQUENCE: A 3 T. Proton: T1 -weighted spoiled gradient echo, T2 -weighted single-shot fast spin echo, multiecho fat/water imaging. Carbon-13: echo-planar spectroscopic imaging, metabolite-specific echo-planar imaging. ASSESSMENT: Transmit magnetic field was measured. Variations in main magnetic field (ΔB0 ) determined using multiecho proton acquisitions were compared to carbon-13 acquisitions. Changes in ΔB0 were measured after localized shimming. Improvements in metabolite signal-to-noise ratio were calculated. Whole-organ regions of interests were drawn over the liver, spleen, pancreas, and kidneys by a single investigator. Metabolite signals, time-to-peak, decay times, and mean first-order rate constants for pyruvate-to-lactate (kPL ) and alanine (kPA ) conversion were measured in each organ. STATISTICAL TESTS: Linear regression, one-sample Kolmogorov-Smirnov tests, paired t-tests, one-way ANOVA, Tukey's multiple comparisons tests. P ≤ 0.05 considered statistically significant. RESULTS: Proton ΔB0 maps correlated with carbon-13 ΔB0 maps (slope = 0.93, y-intercept = -2.88, R2  = 0.73). Localized shimming resulted in mean frequency offset within ±25 Hz for all organs. Metabolite SNR significantly increased after denoising. Mean kPL and kPA were highest in liver, followed by pancreas, spleen, and kidneys (all comparisons with liver were significant). DATA CONCLUSION: Whole-abdomen coverage with hyperpolarized carbon-13 MRI was feasible despite technical challenges. Multiecho gradient echo 1 H acquisitions accurately predicted chemical shifts observed using carbon-13 spectroscopy. Carbon-13 acquisitions benefited from local shimming. Metabolite energetics in the abdomen compiled for healthy volunteers can be used to design larger clinical trials in patients with metabolic diseases. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Clinical translation of hyperpolarized 13 C pyruvate and urea MRI for simultaneous metabolic and perfusion imaging.

PURPOSE: The combined hyperpolarized (HP) 13 C pyruvate and urea MRI has provided a simultaneous assessment of glycolytic metabolism and tissue perfusion for improved cancer diagnosis and therapeutic evaluation in preclinical studies. This work aims to translate this dual-probe HP imaging technique to clinical research. METHODS: A co-polarization system was developed where [1-13 C]pyruvic acid (PA) and [13 C, 15 N2 ]urea in water solution were homogeneously mixed and polarized on a 5T SPINlab system. Physical and chemical characterizations and toxicology studies of the combined probe were performed. Simultaneous metabolic and perfusion imaging was performed on a 3T clinical MR scanner by alternatively applying a multi-slice 2D spiral sequence for [1-13 C]pyruvate and its downstream metabolites and a 3D balanced steady-state free precession (bSSFP) sequence for [13 C, 15 N2 ]urea. RESULTS: The combined PA/urea probe has a glass-formation ability similar to neat PA and can generate nearly 40% liquid-state 13 C polarization for both pyruvate and urea in 3-4 h. A standard operating procedure for routine on-site production was developed and validated to produce 40 mL injection product of approximately 150 mM pyruvate and 35 mM urea. The toxicology study demonstrated the safety profile of the combined probe. Dynamic metabolite-specific imaging of [1-13 C]pyruvate, [1-13 C]lactate, [1-13 C]alanine, and [13 C, 15 N2 ]urea was achieved with adequate spatial (2.6 mm × 2.6 mm) and temporal resolution (4.2 s), and urea images showed reduced off-resonance artifacts due to the JCN coupling. CONCLUSION: The reported technical development and translational studies will lead to the first-in-human dual-agent HP MRI study and mark the clinical translation of the first HP 13 C MRI probe after pyruvate.