Determining the aggressiveness of renal cell carcinoma (RCC) noninvasively is a critical part of the diagnostic workup for treating this disease that kills more than 15,000 people annually in the USA. Recently, we have shown that not only the amount of lactate produced, as a consequence of the Warburg effect, but also its efflux out of the cell, is a critical marker of RCC aggressiveness and differentiating RCCs from benign renal tumors. Enzymatic conversions can now be measured in situ with hyperpolarized (HP) ¹³ C magnetic resonance (MR) on a sub-minute time scale. Using RCC models, we have shown that this technology can interrogate in real time both lactate production and compartmentalization, which are associated with tumor aggressiveness. The dynamic HP MR data have enabled us to robustly characterize parameters that have been elusive to measure directly in intact living cells and murine tumors thus far. Specifically, we were able to measure the same intracellular lactate longitudinal relaxation time in three RCC cell lines of 16.42 s, and lactate efflux rate ranging from 0.14 to 0.8 s^-1 in the least to the most aggressive RCC cell lines and correlate it to monocarboxylate transporter isoform 4 expression. We also analyzed dynamic HP lactate and pyruvate data from orthotopic murine RCC tumors using a simplified one-compartment model, and showed comparable apparent pyruvate to lactate conversion rate (k_PL ) values with those measured in vitro. This kinetic modeling was then extended to characterize the lactate dynamics in patient-derived living RCC tissue slices; and even without direct measurement of the extracellular lactate signal the efflux parameter was still assessed and was distinct between the benign renal tumors and RCCs. Across all these preclinical models, the rate parameters of k_PL and lactate efflux correlated to cancer aggressiveness, demonstrating the validity of our modeling approach for noninvasive assessment of RCC aggressiveness.

Musculoskeletal conditions impede patient biomechanical function. However, clinicians rely on subjective functional assessments with poor test characteristics for biomechanical outcomes because more advanced assessments are impractical in the ambulatory care setting. Using markerless motion capture (MMC) in clinic to record time-series joint position data, we implemented a spatiotemporal assessment of patient kinematics during lower extremity functional testing to evaluate whether kinematic models could identify disease states beyond conventional clinical scoring. 213 trials of the star excursion balance test (SEBT) were recorded by 36 subjects during routine ambulatory clinic visits using both MMC technology and conventional clinician scoring. Conventional clinical scoring failed to distinguish patients with symptomatic lower extremity osteoarthritis (OA) from healthy controls in each component of the assessment. However, principal component analysis of shape models generated from MMC recordings revealed significant differences in subject posture between the OA and control cohorts for six of the eight components. Additionally, time-series models of subject posture change over time revealed distinct movement patterns and reduced overall postural change in the OA cohort compared to the controls. Finally, a novel metric quantifying postural control was derived from subject specific kinematic models and was shown to distinguish OA (1.69), asymptomatic postoperative (1.27), and control (1.23) cohorts (p = 0.0025) and to correlate with patient-reported OA symptom severity (R = -0.72, p = 0.018). Time series motion data have superior discriminative validity and clinical utility than conventional functional assessments in the case of the SEBT. Novel spatiotemporal assessment approaches can enable routine in-clinic collection of objective patient-specific biomechanical data for clinical decision-making and monitoring recovery.

Optimal treatment selection for localized renal tumors is challenging due to their variable biological behavior and limited ability to pre-operatively assess their aggressiveness. We investigated hyperpolarized (HP) ¹³C pyruvate MRI to noninvasively assess tumor lactate production and compartmentalization, which are strongly associated with renal tumor aggressiveness. Orthotopic tumors were created in mice using human renal cell carcinoma (RCC) lines (A498, 786-O, UOK262) with varying expression of lactate dehydrogenase A (LDHA) which catalyzes the pyruvate-to-lactate conversion, and varying expression of monocarboxylate transporter 4 (MCT4) which mediates lactate export out of the cells. Dynamic HP ¹³C pyruvate MRI showed that the A498 tumors had significantly higher ¹³C pyruvate-to-lactate conversion than the UOK262 and 786-O tumors, corresponding to higher A498 tumor LDHA expression. Additionally, diffusion-weighted HP ¹³C pyruvate MRI showed that the A498 tumors had significantly higher ¹³C lactate apparent diffusion coefficients compared to 786-O tumors, with corresponding higher MCT4 expression, which likely reflects more rapid lactate export in the A498 tumors. Our data demonstrate the feasibility of HP ¹³C pyruvate MRI to inform on tumor lactate production and compartmentalization, and provide the scientific premise for future clinical investigation into the utility of this technique to noninvasively interrogate renal tumor aggressiveness and to guide treatment selection.

Non-invasive assessment of the biological aggressiveness of prostate cancer (PCa) is needed for men with localized disease. Hyperpolarized (HP) ¹³C magnetic resonance (MR) spectroscopy is a powerful approach to image metabolism, specifically the conversion of HP [1-¹³C]pyruvate to [1-¹³C]lactate, catalyzed by lactate dehydrogenase (LDH). Significant increase in tumor lactate was measured in high-grade PCa relative to benign and low-grade cancer, suggesting that HP ¹³C MR could distinguish low-risk (Gleason score ≤3 + 4) from high-risk (Gleason score ≥4 + 3) PCa. To test this and the ability of HP ¹³C MR to detect these metabolic changes, we cultured prostate tissues in an MR-compatible bioreactor under continuous perfusion. ³¹P spectra demonstrated good viability and dynamic HP ¹³C-pyruvate MR demonstrated that high-grade PCa had significantly increased lactate efflux compared to low-grade PCa and benign prostate tissue. These metabolic differences are attributed to significantly increased LDHA expression and LDH activity, as well as significantly increased monocarboxylate transporter 4 (MCT4) expression in high- versus low- grade PCa. Moreover, lactate efflux, LDH activity, and MCT4 expression were not different between low-grade PCa and benign prostate tissues, indicating that these metabolic alterations are specific for high-grade disease. These distinctive metabolic alterations can be used to differentiate high-grade PCa from low-grade PCa and benign prostate tissues using clinically translatable HP [1-¹³C]pyruvate MR.