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Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique.

BackgroundEfficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. ObjectiveThe objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. MethodsWe created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). ResultsAlthough the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. ConclusionsOur pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.

BackgroundOptimal treatment selection for localized renal tumors is challenging because of their variable biologic behavior and limitations in the preoperative assessment of tumor aggressiveness. The authors investigated the emerging hyperpolarized (HP) 13 C magnetic resonance imaging (MRI) technique to noninvasively assess tumor lactate production, which is strongly associated with tumor aggressiveness.MethodsEleven patients with renal tumors underwent HP 13 C pyruvate MRI before surgical resection. Tumor 13 C pyruvate and 13 C lactate images were acquired dynamically. Five patients underwent 2 scans on the same day to assess the intrapatient reproducibility of HP 13 C pyruvate MRI. Tumor metabolic data were compared with histopathology findings.ResultsEight patients had tumors with a sufficient metabolite signal-to-noise ratio for analysis; an insufficient tumor signal-to-noise ratio was noted in 2 patients, likely caused by poor tumor perfusion and, in 1 patient, because of technical errors. Of the 8 patients, 3 had high-grade clear cell renal cell carcinoma (ccRCC), 3 had low-grade ccRCC, and 2 had chromophobe RCC. There was a trend toward a higher lactate-to-pyruvate ratio in high-grade ccRCCs compared with low-grade ccRCCs. Both chromophobe RCCs had relatively high lactate-to-pyruvate ratios. Good reproducibility was noted across the 5 patients who underwent 2 HP 13 C pyruvate MRI scans on the same day.ConclusionsThe current results demonstrate the feasibility of HP 13 C pyruvate MRI for investigating the metabolic phenotype of localized renal tumors. The initial data indicate good reproducibility of metabolite measurements. In addition, the metabolic data indicate a trend toward differentiating low-grade and high-grade ccRCCs, the most common subtype of renal cancer.Lay summaryRenal tumors are frequently discovered incidentally because of the increased use of medical imaging, but it is challenging to identify which aggressive tumors should be treated. A new metabolic imaging technique was applied to noninvasively predict renal tumor aggressiveness. The imaging results were compared with tumor samples taken during surgery and showed a trend toward differentiating between low-grade and high-grade clear cell renal cell carcinomas, which are the most common type of renal cancers.

PurposeThe balanced steady-state free precession sequence has been previously explored to improve the efficient use of nonrecoverable hyperpolarized 13C magnetization, but suffers from poor spectral selectivity and long acquisition time. The purpose of this study was to develop a novel metabolite-specific 3D bSSFP ("MS-3DSSFP") sequence with stack-of-spiral readouts for improved lactate imaging in hyperpolarized [1-13 C]pyruvate studies on a clinical 3T scanner.MethodsSimulations were performed to evaluate the spectral response of the MS-3DSSFP sequence. Thermal 13C phantom experiments were performed to validate the MS-3DSSFP sequence. In vivo hyperpolarized [1-13 C], pyruvate studies were performed to compare the MS-3DSSFP sequence with metabolite-specific gradient echo ("MS-GRE") sequences for lactate imaging.ResultsSimulations, phantom, and in vivo studies demonstrate that the MS-3DSSFP sequence achieved spectrally selective excitation on lactate while minimally perturbing other metabolites. Compared with MS-GRE sequences, the MS-3DSSFP sequence showed approximately a 2.5-fold SNR improvement for lactate imaging in rat kidneys, prostate tumors in a mouse model, and human kidneys.ConclusionsImproved lactate imaging using the MS-3DSSFP sequence in hyperpolarized [1-13 C]pyruvate studies was demonstrated in animals and humans. The MS-3DSSFP sequence could be applied for other clinical applications such as in the brain or adapted for imaging other metabolites such as pyruvate and bicarbonate.

PurposeThe balanced steady-state free precession sequence has been previously explored to improve the efficient use of nonrecoverable hyperpolarized 13C magnetization, but suffers from poor spectral selectivity and long acquisition time. The purpose of this study was to develop a novel metabolite-specific 3D bSSFP ("MS-3DSSFP") sequence with stack-of-spiral readouts for improved lactate imaging in hyperpolarized [1-13 C]pyruvate studies on a clinical 3T scanner.MethodsSimulations were performed to evaluate the spectral response of the MS-3DSSFP sequence. Thermal 13C phantom experiments were performed to validate the MS-3DSSFP sequence. In vivo hyperpolarized [1-13 C], pyruvate studies were performed to compare the MS-3DSSFP sequence with metabolite-specific gradient echo ("MS-GRE") sequences for lactate imaging.ResultsSimulations, phantom, and in vivo studies demonstrate that the MS-3DSSFP sequence achieved spectrally selective excitation on lactate while minimally perturbing other metabolites. Compared with MS-GRE sequences, the MS-3DSSFP sequence showed approximately a 2.5-fold SNR improvement for lactate imaging in rat kidneys, prostate tumors in a mouse model, and human kidneys.ConclusionsImproved lactate imaging using the MS-3DSSFP sequence in hyperpolarized [1-13 C]pyruvate studies was demonstrated in animals and humans. The MS-3DSSFP sequence could be applied for other clinical applications such as in the brain or adapted for imaging other metabolites such as pyruvate and bicarbonate.

ObjectivesStandardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization.Materials and methodsReported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement.ResultsCorrelations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65-74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided.DiscussionThe consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.

The article Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.

Kidney transplantation is the treatment of choice for patients with end-stage renal disease, as it extends survival and increases quality of life in these patients. However, chronic allograft injury continues to be a major problem, and leads to eventual graft loss. Early detection of allograft injury is essential for guiding appropriate intervention to delay or prevent irreversible damage. Several advanced MRI techniques can offer some important information regarding functional changes such as perfusion, diffusion, structural complexity, as well as oxygenation and fibrosis. This review highlights the potential of multiparametric MRI for noninvasive and comprehensive assessment of renal allograft injury.

Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Oxidative stress is a critical feature of several common neurologic disorders. The brain is well adapted to neutralize oxidative injury by maintaining a high steady-state concentration of small-molecule intracellular antioxidants including glutathione in astrocytes and ascorbic acid in neurons. Ascorbate-derived imaging probes for hyperpolarized 13C magnetic resonance spectroscopy and positron emission tomography have been used to study redox changes (antioxidant depletion and reactive oxygen species accumulation) in vivo. In this study, we applied these imaging probes to the normal rat brain and a rat model of glutathione depletion. We first studied hyperpolarized [1-13C]dehydroascorbate in the normal rat brain, demonstrating its robust conversion to [1-13C]vitamin C, consistent with rapid transport of the oxidized form across the blood-brain barrier. We next showed that the kinetic rate of this conversion decreased by nearly 50% after glutathione depletion by diethyl maleate treatment. Finally, we showed that dehydroascorbate labeled for positron emission tomography, namely [1-11C]dehydroascorbate, showed no change in brain signal accumulation after diethyl maleate treatment. These results suggest that hyperpolarized [1-13C]dehydroascorbate may be used to non-invasively detect oxidative stress in common disorders of the brain.

Acute kidney injury (AKI) is a major risk factor for the development of chronic kidney disease (CKD). Persistent oxidative stress and mitochondrial dysfunction are implicated across diverse forms of AKI and in the transition to CKD. In this study, we applied hyperpolarized (HP) 13 C dehydroascorbate (DHA) and 13 C pyruvate magnetic resonance spectroscopy (MRS) to investigate the renal redox capacity and mitochondrial pyruvate dehydrogenase (PDH) activity, respectively, in a murine model of AKI at baseline and 7 days after unilateral ischemia reperfusion injury (IRI). Compared with the contralateral sham-operated kidneys, the kidneys subjected to IRI showed a significant decrease in the HP 13 C vitamin C/(vitamin C + DHA) ratio, consistent with a decrease in redox capacity. The kidneys subjected to IRI also showed a significant decrease in the HP 13 C bicarbonate/pyruvate ratio, consistent with impaired PDH activity. The IRI kidneys showed a significantly higher HP 13 C lactate/pyruvate ratio at day 7 compared with baseline, although the 13 C lactate/pyruvate ratio was not significantly different between the IRI and contralateral sham-operated kidneys at day 7. Arterial spin labeling magnetic resonance imaging (MRI) demonstrated significantly reduced perfusion in the IRI kidneys. Renal tissue analysis showed corresponding increased reactive oxygen species (ROS) and reduced PDH activity in the IRI kidneys. Our results show the feasibility of HP 13 C MRS for the non-invasive assessment of oxidative stress and mitochondrial PDH activity following renal IRI.

ObjectiveThe purpose of the study was to assess the ability of rapid-kV switching (rs) dual-energy computed tomography (DECT) to reduce peristalsis-related streak artifact.MethodsrsDECT images of 100 consecutive patients (48 male, 52 female, mean age 57 years) were retrospectively evaluated in this institutional review board-approved study. Image reconstructions included virtual monochromatic 70 and 120 keV images, as well as iodine(-water) and water(-iodine) material decomposition images. We recorded the presence and severity of artifacts qualitatively (4-point scale) and quantitatively [iodine/water concentrations, Hounsfield units, gray scale values (GY)] and compared to corresponding unaffected reference tissue. Similar measures were obtained in DECT images of a peristalsis phantom. Wilcoxon signed-rank and paired t tests were used to compare results between different image reconstructions.ResultsPeristalsis-related streak artifacts were found in 49 (49%) of the DECT examinations. Artifacts were significantly more severe in 70, 120, and water(-iodine) images than in iodine(-water) images (qualitative readout P

In this work, we present a new ultrafast method for acquiring dynamic 2D EXchange SpectroscopY (EXSY) within a single acquisition. This technique reconstructs two-dimensional EXSY spectra from one-dimensional spectra based on the phase accrual during echo times. The Ultrafast-EXSY acquisition overcomes long acquisition times typically needed to acquire 2D NMR data by utilizing sparsity and phase dependence to dramatically undersample in the indirect time dimension. This allows for the acquisition of the 2D spectrum within a single shot. We have validated this method in simulations and hyperpolarized enzyme assay experiments separating the dehydration of pyruvate and lactate-to-pyruvate conversion. In a renal cell carcinoma cell (RCC) line, bidirectional exchange was observed. This new technique revealed decreased conversion of lactate-to-pyruvate with high expression of monocarboxylate transporter 4 (MCT4), known to correlate with aggressive cancer phenotypes. We also showed feasibility of this technique in vivo in a RCC model where bidirectional exchange was observed for pyruvate-lactate, pyruvate-alanine, and pyruvate-hydrate and were resolved in time. Broadly, the technique is well suited to investigate the dynamics of multiple exchange pathways and applicable to hyperpolarized substrates where chemical exchange has shown great promise across a range of disciplines.

ObjectiveThe purpose of this study was to determine whether contrast-enhanced CT quantification of the hepatic fractional extracellular space (ECS) correlates with the severity of diffuse liver disease.Materials and methodsThe cases of 70 patients without (46 men, 24 women; mean age, 59.1 years) and 36 patients with (23 men, 13 women; mean age, 63.1 years) cirrhosis who had undergone unenhanced and 10-minute delayed phase contrast-enhanced CT were retrospectively identified. By consensus one experienced radiologist and one trainee measured the CT attenuation of the liver and aorta to estimate the fractional ECS, defined as the ratio of the difference between the attenuation of the liver on 10-minute and unenhanced images to the difference between the attenuation of the aorta on 10-minute and unenhanced images multiplied by 1 minus the hematocrit. Findings were correlated with each patient's Model of End-Stage Liver Disease (MELD) score.ResultsThe mean MELD score was higher in patients with than in those without cirrhosis (14.3 ± 7.3 versus 7.20 ± 2.4, p < 0.0001). The mean fractional ECS was significantly greater in patients with cirrhosis than in those without cirrhosis (41.0% ± 9.0% versus 23.8% ± 6.3%, p < 0.0001). The fractional ECS correlated with the MELD score (r = 0.572, p < 0.0001) and was predictive of cirrhosis with an area under the receiver operating characteristic curve of 0.953 (p < 0.0001). The sensitivity and specificity of an expanded fractional ECS greater than 30% for the prediction of cirrhosis were 92% and 83%. Multivariate linear regression revealed that the fractional ECS is complementary to the MELD score as a predictor of cirrhosis (p < 0.0001).ConclusionNoninvasive contrast-enhanced CT quantification of the fractional ECS correlates with the MELD score, an indicator of the severity of liver disease, and merits further study.

We present an approach for the joint segmentation and classification of a time series. The segmentation is on the basis of a menu of possible statistical models: each of these must be describable in terms of a sufficient statistic, but there is no need for these sufficient statistics to be the same, and these can be as complex (for example, cepstral features or autoregressive coefficients) as fits. All that is needed is the probability density function (PDF) of each sufficient statistic under its own assumed model--presumably this comes from training data, and it is particularly appealing that there is no need at all for a joint statistical characterization of all the statistics. There is similarly no need for an a-priori specification of the number of sections, as the approach uses an appropriate penalization of an over-zealous segmentation. The scheme has two stages. In stage one, rough segmentations are implemented sequentially using a piecewise generalized likelihood ratio (GLR); in the second stage, the results from the first stage (both forward and backward) are refined. The computational burden is remarkably small, approximately linear with the length of the time series, and the method is nicely accurate in terms both of discovered number of segments and of segmentation accuracy. A hybrid of the approach with one based on Gibbs sampling is also presented; this combination is somewhat slower but considerably more accurate. Index Terms--Classification, class-specific, GLR, order selection, segmentation.

BACKGROUND: Optimal treatment selection for localized renal tumors is challenging because of their variable biologic behavior and limitations in the preoperative assessment of tumor aggressiveness. The authors investigated the emerging hyperpolarized (HP) 13C magnetic resonance imaging (MRI) technique to noninvasively assess tumor lactate production, which is strongly associated with tumor aggressiveness. METHODS: Eleven patients with renal tumors underwent HP 13C pyruvate MRI before surgical resection. Tumor 13C pyruvate and 13C lactate images were acquired dynamically. Five patients underwent 2 scans on the same day to assess the intrapatient reproducibility of HP 13C pyruvate MRI. Tumor metabolic data were compared with histopathology findings. RESULTS: Eight patients had tumors with a sufficient metabolite signal‐to‐noise ratio for analysis; an insufficient tumor signal‐to‐noise ratio was noted in 2 patients, likely caused by poor tumor perfusion and, in 1 patient, because of technical errors. Of the 8 patients, 3 had high‐grade clear cell renal cell carcinoma (ccRCC), 3 had low‐grade ccRCC, and 2 had chromophobe RCC. There was a trend toward a higher lactate‐to‐pyruvate ratio in high‐grade ccRCCs compared with low‐grade ccRCCs. Both chromophobe RCCs had relatively high lactate‐to‐pyruvate ratios. Good reproducibility was noted across the 5 patients who underwent 2 HP 13C pyruvate MRI scans on the same day. CONCLUSIONS: The current results demonstrate the feasibility of HP 13C pyruvate MRI for investigating the metabolic phenotype of localized renal tumors. The initial data indicate good reproducibility of metabolite measurements. In addition, the metabolic data indicate a trend toward differentiating low‐grade and high‐grade ccRCCs, the most common subtype of renal cancer. LAY SUMMARY: Renal tumors are frequently discovered incidentally because of the increased use of medical imaging, but it is challenging to identify which aggressive tumors should be treated.A new metabolic imaging technique was applied to noninvasively predict renal tumor aggressiveness.The imaging results were compared with tumor samples taken during surgery and showed a trend toward differentiating between low‐grade and high‐grade clear cell renal cell carcinomas, which are the most common type of renal cancers. A new metabolic imaging technique, hyperpolarized 13C pyruvate magnetic resonance imaging, is applied to predict renal tumor aggressiveness. The results demonstrate feasibility, reproducibility, and promising trends for risk stratifying renal tumors noninvasively. [ABSTRACT FROM AUTHOR]