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.

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.

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 assessment of a biophysical model for distinguishing tumor progression from radiation necrosis.

PURPOSE: The efficacy of an imaging-driven mechanistic biophysical model of tumor growth for distinguishing radiation necrosis from tumor progression in patients with enhancing lesions following stereotactic radiosurgery (SRS) for brain metastasis is validated. METHODS: We retrospectively assessed the model using 73 patients with 78 lesions and histologically confirmed radiation necrosis or tumor progression. Postcontrast T1-weighted MRI images were used to extract parameters for a mechanistic reaction-diffusion logistic growth model mechanically coupled to the surrounding tissue. The resulting model was then used to estimate mechanical stress fields, which were then compared with edema visualized on FLAIR imaging using DICE similarity coefficients. DICE, model, and standard radiographic morphometric analysis parameters were evaluated using a receiver operating characteristic (ROC) curve for prediction of radiation necrosis or tumor progression. Multivariate logistic regression models were then constructed using mechanistic model parameters or advanced radiomic features. An independent validation was performed to evaluate predictive performance. RESULTS: Tumor cell proliferation rate resulted in ROC AUC = 0.86, 95% CI: 0.76-0.95, P < 0.0001, 74% sensitivity and 95% specificity) and DICE similarity coefficient associated with high stresses demonstrated an ROC AUC = 0.93, 95% CI: 0.86-0.99, P < 0.0001, 81% sensitivity and 95% specificity. In a multivariate logistic regression model using an independent validation dataset, mechanistic modeling parameters had an ROC AUC of 0.95, with 94% sensitivity and 96% specificity. CONCLUSIONS: Imaging-driven biophysical modeling of tumor growth represents a novel method for accurately predicting clinically significant tumor behavior.

Lactate Dehydrogenase A Depletion Alters MyC-CaP Tumor Metabolism, Microenvironment, and CAR T Cell Therapy.

To enhance human prostate-specific membrane antigen (hPSMA)-specific chimeric antigen receptor (CAR) T cell therapy in a hPSMA+ MyC-CaP tumor model, we studied and imaged the effect of lactate dehydrogenase A (LDH-A) depletion on the tumor microenvironment (TME) and tumor progression. Effective LDH-A short hairpin RNA (shRNA) knockdown (KD) was achieved in MyC-CaP:hPSMA+ Renilla luciferase (RLuc)-internal ribosome entry site (IRES)-GFP tumor cells, and changes in tumor cell metabolism and in the TME were monitored. LDH-A downregulation significantly inhibited cell proliferation and subcutaneous tumor growth compared to control cells and tumors. However, total tumor lactate concentration did not differ significantly between LDH-A knockdown and control tumors, reflecting the lower vascularity, blood flow, and clearance of lactate from LDH-A knockdown tumors. Comparing treatment responses of MyC-CaP tumors with LDH-A depletion and/or anti-hPSMA CAR T cells showed that the dominant effect on tumor growth was LDH-A depletion. With anti-hPSMA CAR T cell treatment, tumor growth was significantly slower when combined with tumor LDH-A depletion and compared to control tumor growth (p < 0.0001). The lack of a complete tumor response in our animal model can be explained in part by (1) the lower activity of human CAR T cells against hPSMA-expressing murine tumors in a murine host, and (2) a loss of hPSMA antigen from the tumor cell surface in progressive generations of tumor cells.

Biophysical model-based parameters to classify tumor recurrence from radiation-induced necrosis for brain metastases.

PURPOSE: Stereotactic radiosurgery (SRS) is used for local control treatment of patients with intracranial metastases. As a result of SRS, some patients develop radiation-induced necrosis. Radiographically, radiation-induced necrosis can appear similar to tumor recurrence in magnetic resonance (MR) T1 -weighted contrast-enhanced imaging, T2 -weighted MR imaging, and Fluid-Attenuated Inversion Recovery (FLAIR) MR imaging. Radiographic ambiguities often necessitate invasive brain biopsies to determine lesion etiology or cause delayed subsequent therapy initiation. We use a biomechanically coupled tumor growth model to estimate patient-specific model parameters and model-derived measures to noninvasively classify etiology of enhancing lesions in this patient population. METHODS: In this initial, preliminary retrospective study, we evaluated five patients with tumor recurrence and five with radiation-induced necrosis. Longitudinal patient-specific MR imaging data were used in conjunction with the model to parameterize tumor cell proliferation rate and tumor cell diffusion coefficient, and Dice correlation coefficients were used to quantify degree of correlation between model-estimated mechanical stress fields and edema visualized from MR imaging. RESULTS: Results found four statistically relevant parameters which can differentiate tumor recurrence and radiation-induced necrosis. CONCLUSIONS: This preliminary investigation suggests potential of this framework to noninvasively determine the etiology of enhancing lesions in patients who previously underwent SRS for intracranial metastases.