SPICER: Self-supervised learning for MRI with automatic coil sensitivity estimation and reconstruction.

PURPOSE: To introduce a novel deep model-based architecture (DMBA), SPICER, that uses pairs of noisy and undersampled k-space measurements of the same object to jointly train a model for MRI reconstruction and automatic coil sensitivity estimation. METHODS: SPICER consists of two modules to simultaneously reconstructs accurate MR images and estimates high-quality coil sensitivity maps (CSMs). The first module, CSM estimation module, uses a convolutional neural network (CNN) to estimate CSMs from the raw measurements. The second module, DMBA-based MRI reconstruction module, forms reconstructed images from the input measurements and the estimated CSMs using both the physical measurement model and learned CNN prior. With the benefit of our self-supervised learning strategy, SPICER can be efficiently trained without any fully sampled reference data. RESULTS: We validate SPICER on both open-access datasets and experimentally collected data, showing that it can achieve state-of-the-art performance in highly accelerated data acquisition settings (up to 10 × $$ 10\times $$ ). Our results also highlight the importance of different modules of SPICER-including the DMBA, the CSM estimation, and the SPICER training loss-on the final performance of the method. Moreover, SPICER can estimate better CSMs than pre-estimation methods especially when the ACS data is limited. CONCLUSION: Despite being trained on noisy undersampled data, SPICER can reconstruct high-quality images and CSMs in highly undersampled settings, which outperforms other self-supervised learning methods and matches the performance of the well-known E2E-VarNet trained on fully sampled ground-truth data.

Resting state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats.

The kidneys maintain fluid-electrolyte balance and excrete waste in the presence of constant fluctuations in plasma volume and systemic blood pressure. The kidneys perform these functions to control capillary perfusion and glomerular filtration by modulating the mechanisms of autoregulation. An effect of these modulations are spontaneous, natural fluctuations in nephron perfusion. Numerous other mechanisms can lead to fluctuations in perfusion and flow. The ability to monitor these spontaneous physiological fluctuations in vivo could facilitate the early detection of kidney disease. The goal of this work was to investigate the use of resting- state magnetic resonance imaging (rsMRI) to detect spontaneous physiological fluctuations in the kidney. We performed rsMRI of rat kidneys in vivo over 10 minutes, applying motion correction to resolve time series in each voxel. We observed spatially variable, spontaneous fluctuations in rsMRI signal between 0-0.3 Hz, in frequency bands also associated with autoregulatory mechanisms. We further applied rsMRI to investigate changes in these fluctuations in a rat model of diabetic nephropathy. Spectral analysis was performed on time series of rsMRI signal in kidney cortex and medulla. Power from spectra in specific frequency bands from kidney cortex correlated with severity of glomerular pathology caused by diabetic nephropathy. Finally, we investigated the feasibility of using rsMRI of the human kidney in two participants, observing the presence of similar, spatially variable fluctuations. This approach may enable a range of preclinical and clinical investigations of kidney function, and facilitate the development of new therapies to improve outcomes in patients with kidney disease.

Comparison of cerebral oxygen extraction fraction using ASE and TRUST methods in patients with sickle cell disease and healthy controls.

Abnormal oxygen extraction fraction (OEF), a putative biomarker of cerebral metabolic stress, may indicate compromised oxygen delivery and ischemic vulnerability in patients with sickle cell disease (SCD). Elevated OEF was observed at the tissue level across the brain using an asymmetric spin echo (ASE) MR method, while variable global OEFs were found from the superior sagittal sinus (SSS) using a T2-relaxation-under-spin-tagging (TRUST) MRI method with different calibration models. In this study, we aimed to compare the average ASE-OEF in the SSS drainage territory and TRUST-OEF in the SSS from the same SCD patients and healthy controls. 74 participants (SCD: N = 49; controls: N = 25) underwent brain MRI. TRUST-OEF was quantified using the Lu-bovine, Bush-HbA and Li-Bush-HbS models. ASE-OEF and TRUST-OEF were significantly associated in healthy controls after controlling for hematocrit using the Lu-bovine or the Bush-HbA model. However, no association was found between ASE-OEF and TRUST-OEF in patients with SCD using either the Bush-HbA or the Li-Bush-HbS model. Plausible explanations include a discordance between spatially volume-averaged oxygenation brain tissue and flow-weighted volume-averaged oxygenation in SSS or sub-optimal calibration in SCD. Further work is needed to refine and validate non-invasive MR OEF measurements in SCD.

Respiratory motion management using a single rapid MRI scan for a 0.35 T MRI-Linac system.

BACKGROUND: MRI has a rapidly growing role in radiation therapy (RT) for treatment planning, real-time image guidance, and beam gating (e.g., MRI-Linac). Free-breathing 4D-MRI is desirable in respiratory motion management for therapy. Moreover, high-quality 3D-MRIs without motion artifacts are needed to delineate lesions. Existing MRI methods require multiple scans with lengthy acquisition times or are limited by low spatial resolution, contrast, and signal-to-noise ratio. PURPOSE: We developed a novel method to obtain motion-resolved 4D-MRIs and motion-integrated 3D-MRI reconstruction using a single rapid (35-45 s scan on a 0.35 T MRI-Linac. METHODS: Golden-angle radial stack-of-stars MRI scans were acquired from a respiratory motion phantom and 12 healthy volunteers (n = 12) on a 0.35 T MRI-Linac. A self-navigated method was employed to detect respiratory motion using 2000 (acquisition time = 5-7 min) and the first 200 spokes (acquisition time = 35-45 s). Multi-coil non-uniform fast Fourier transform (MCNUFFT), compressed sensing (CS), and deep-learning Phase2Phase (P2P) methods were employed to reconstruct motion-resolved 4D-MRI using 2000 spokes (MCNUFFT2000) and 200 spokes (CS200 and P2P200). Deformable motion vector fields (MVFs) were computed from the 4D-MRIs and used to reconstruct motion-corrected 3D-MRIs with the MOtion Transformation Integrated forward-Fourier (MOTIF) method. Image quality was evaluated quantitatively using the structural similarity index measure (SSIM) and the root mean square error (RMSE), and qualitatively in a blinded radiological review. RESULTS: Evaluation using the respiratory motion phantom experiment showed that the proposed method reversed the effects of motion blurring and restored edge sharpness. In the human study, P2P200 had smaller inaccuracy in MVFs estimation than CS200. P2P200 had significantly greater SSIMs (p < 0.0001) and smaller RMSEs (p < 0.001) than CS200 in motion-resolved 4D-MRI and motion-corrected 3D-MRI. The radiological review found that MOTIF 3D-MRIs using MCNUFFT2000 exhibited the highest image quality (scoring > 8 out of 10), followed by P2P200 (scoring > 5 out of 10), and then motion-uncorrected (scoring < 3 out of 10) in sharpness, contrast, and artifact-freeness. CONCLUSIONS: We have successfully demonstrated a method for respiratory motion management for MRI-guided RT. The method integrated self-navigated respiratory motion detection, deep-learning P2P 4D-MRI reconstruction, and a motion integrated reconstruction (MOTIF) for 3D-MRI using a single rapid MRI scan (35-45 s) on a 0.35 T MRI-Linac system.

Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease.

Children with sickle cell disease (SCD) demonstrate cerebral hemodynamic stress and are at high risk of strokes. We hypothesized that curative hematopoietic stem cell transplant (HSCT) normalizes cerebral hemodynamics in children with SCD compared with pre-transplant baseline. Whole-brain cerebral blood flow (CBF) and oxygen extraction fraction (OEF) were measured by magnetic resonance imaging 1 to 3 months before and 12 to 24 months after HSCT in 10 children with SCD. Three children had prior overt strokes, 5 children had prior silent strokes, and 1 child had abnormal transcranial Doppler ultrasound velocities. CBF and OEF of HSCT recipients were compared with non-SCD control participants and with SCD participants receiving chronic red blood cell transfusion therapy (CRTT) before and after a scheduled transfusion. Seven participants received matched sibling donor HSCT, and 3 participants received 8 out of 8 matched unrelated donor HSCT. All received reduced-intensity preparation and maintained engraftment, free of hemolytic anemia and SCD symptoms. Pre-transplant, CBF (93.5 mL/100 g/min) and OEF (36.8%) were elevated compared with non-SCD control participants, declining significantly 1 to 2 years after HSCT (CBF, 72.7 mL/100 g per minute; P = .004; OEF, 27.0%; P = .002), with post-HSCT CBF and OEF similar to non-SCD control participants. Furthermore, HSCT recipients demonstrated greater reduction in CBF (-19.4 mL/100 g/min) and OEF (-8.1%) after HSCT than children with SCD receiving CRTT after a scheduled transfusion (CBF, -0.9 mL/100 g/min; P = .024; OEF, -3.3%; P = .001). Curative HSCT normalizes whole-brain hemodynamics in children with SCD. This restoration of cerebral oxygen reserve may explain stroke protection after HSCT in this high-risk patient population.

Deep-learning synthesized pseudo-CT for MR high-resolution pediatric cranial bone imaging (MR-HiPCB).

PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo-CT (pCT) images for MR high-resolution pediatric cranial bone imaging to eliminating ionizing radiation from CT. METHODS: 3D golden-angle stack-of-stars MRI were obtained from 44 pediatric participants. Two patch-based residual UNets were trained using paired MR and CT patches randomly selected from the whole head (NetWH) or in the vicinity of bone, fractures/sutures, or air (NetBA) to synthesize pCT. A third residual UNet was trained to generate a binary brain mask using only MRI. The pCT images from NetWH (pCTNetWH ) in the brain area and NetBA (pCTNetBA ) in the nonbrain area were combined to generate pCTCom . A manual processing method using inverted MR images was also employed for comparison. RESULTS: pCTCom (68.01 ± 14.83 HU) had significantly smaller mean absolute errors (MAEs) than pCTNetWH (82.58 ± 16.98 HU, P < 0.0001) and pCTNetBA (91.32 ± 17.2 HU, P < 0.0001) in the whole head. Within cranial bone, the MAE of pCTCom (227.92 ± 46.88 HU) was significantly lower than pCTNetWH (287.85 ± 59.46 HU, P < 0.0001) but similar to pCTNetBA (230.20 ± 46.17 HU). Dice similarity coefficient of the segmented bone was significantly higher in pCTCom (0.90 ± 0.02) than in pCTNetWH (0.86 ± 0.04, P < 0.0001), pCTNetBA (0.88 ± 0.03, P < 0.0001), and inverted MR (0.71 ± 0.09, P < 0.0001). Dice similarity coefficient from pCTCom demonstrated significantly reduced age dependence than inverted MRI. Furthermore, pCTCom provided excellent suture and fracture visibility comparable to CT. CONCLUSION: MR high-resolution pediatric cranial bone imaging may facilitate the clinical translation of a radiation-free MR cranial bone imaging method for pediatric patients.

Cranial vault imaging for pediatric head trauma using a radial VIBE MRI sequence.

OBJECTIVE: Head trauma is the most common indication for a CT scan. In this pilot study, the authors assess the feasibility of a 5-minute high-resolution 3D golden-angle (GA) stack-of-stars radial volumetric interpolated breath-hold examination (VIBE) MRI sequence (GA-VIBE) to obtain clinically acceptable cranial bone images and identify cranial vault fractures compared to CT. METHODS: Patients younger than 18 years of age presenting after head trauma were eligible for the study. Three clinicians reviewed and assessed 1) slice-by-slice volumetric CT and inverted MR images, and 2) 3D reconstructions obtained from inverted MR images and the gold standard (CT). For each image set, reviewers noted on 5-point Likert scales whether they recommended that a repeat scan be performed and the presence or absence of cranial vault fractures. RESULTS: Thirty-one patients completed MRI after a clinical head CT scan was performed. Based on CT imaging, 8 of 31 patients had cranial fractures. Two of 31 patients were sedated as part of their clinical MRI scan. In 30 (97%) of 31 MRI reviews, clinicians agreed (or strongly agreed) that the image quality was acceptable for clinical diagnosis. Overall, comparing MRI to acceptable gold-standard CT, sensitivity and specificity of fracture detection were 100%. Furthermore, there were no discrepancies between CT and MRI in classification of fracture type or location. CONCLUSIONS: When compared with the gold standard (CT), the volumetric and 3D reconstructed images using the GA-VIBE sequence were able to produce clinically acceptable cranial images with excellent ability to detect cranial vault fractures.

Deformation-Compensated Learning for Image Reconstruction Without Ground Truth.

Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has shown the potential of using multiple noisy measurements of the same object as an alternative to having a ground-truth. However, existing N2N-based methods are not suitable for learning from the measurements of an object undergoing nonrigid deformation. This paper addresses this issue by proposing the deformation-compensated learning (DeCoLearn) method for training deep reconstruction networks by compensating for object deformations. A key component of DeCoLearn is a deep registration module, which is jointly trained with the deep reconstruction network without any ground-truth supervision. We validate DeCoLearn on both simulated and experimentally collected magnetic resonance imaging (MRI) data and show that it significantly improves imaging quality.

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan. METHODS: The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI-based MVFs were derived from either 2000 spokes (MoCo2000 , 5-6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCoP2P200 , 30-40 s acquisition time) using a deep-learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUVmax , SUVpeak , SUVmean , lesion volume) and a blinded radiological review on lesion conspicuity. RESULTS: MRI-assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo2000 and MoCoP2P200 PET images had significantly higher SUVmax , SUVpeak , SUVmean and significantly lower lesion volume than non-motion-corrected (non-MoCo) PET images. There was no statistical difference between MoCo2000 and MoCoP2P200 PET images for SUVmax , SUVpeak , SUVmean or lesion volume. Both radiological reviewers found that MoCo2000 and MoCoP2P200 PET significantly improved lesion conspicuity. CONCLUSION: An MRI-assisted PET MoCo method was evaluated using the ground truth in a phantom study. In patients with hepatic lesions, PET MoCo images improved quantitative and qualitative metrics based on only 30-40 s of MRI motion modeling data.

Cerebral Oxygen Metabolic Stress, Microstructural Injury, and Infarction in Adults With Sickle Cell Disease.

OBJECTIVE: To determine the patient- and tissue-based relationships between cerebral hemodynamic and oxygen metabolic stress, microstructural injury, and infarct location in adults with sickle cell disease (SCD). METHODS: Control participants and patients with SCD underwent brain MRI to quantify cerebral blood flow (CBF), oxygen extraction fraction (OEF), mean diffusivity (MD), and fractional anisotropy (FA) within normal-appearing white matter (NAWM) and infarcts on fluid-attenuated inversion recovery. Multivariable linear regression examined the patient- and voxel-based associations between hemodynamic and metabolic stress (defined as elevated CBF and OEF, respectively), white matter microstructure, and infarct location. RESULTS: Of 83 control participants and patients with SCD, adults with SCD demonstrated increased CBF (50.9 vs 38.8 mL/min/100 g, p < 0.001), increased OEF (0.35 vs 0.25, p < 0.001), increased MD (0.76 vs 0.72 × 10-3 mm2s-1, p = 0.005), and decreased FA (0.40 vs 0.42, p = 0.021) within NAWM compared to controls. In multivariable analysis, increased OEF (ß = 0.19, p = 0.035), but not CBF (ß = 0.00, p = 0.340), independently predicted increased MD in the SCD cohort; neither were predictors in controls. On voxel-wise regression, the SCD cohort demonstrated widespread OEF elevation, encompassing deep white matter regions of elevated MD and reduced FA, which spatially extended beyond high-density infarct locations from the SCD cohort. CONCLUSION: Elevated OEF, a putative index of cerebral oxygen metabolic stress, may provide a metric of ischemic vulnerability that could enable individualization of therapeutic strategies in SCD. The patient- and tissue-based relationships between elevated OEF, elevated MD, and cerebral infarcts suggest that oxygen metabolic stress may underlie microstructural injury prior to the development of cerebral infarcts in SCD.

Phase2Phase: Respiratory Motion-Resolved Reconstruction of Free-Breathing Magnetic Resonance Imaging Using Deep Learning Without a Ground Truth for Improved Liver Imaging.

OBJECTIVES: Respiratory binning of free-breathing magnetic resonance imaging data reduces motion blurring; however, it exacerbates noise and introduces severe artifacts due to undersampling. Deep neural networks can remove artifacts and noise but usually require high-quality ground truth images for training. This study aimed to develop a network that can be trained without this requirement. MATERIALS AND METHODS: This retrospective study was conducted on 33 participants enrolled between November 2016 and June 2019. Free-breathing magnetic resonance imaging was performed using a radial acquisition. Self-navigation was used to bin the k-space data into 10 respiratory phases. To simulate short acquisitions, subsets of radial spokes were used in reconstructing images with multicoil nonuniform fast Fourier transform (MCNUFFT), compressed sensing (CS), and 2 deep learning methods: UNet3DPhase and Phase2Phase (P2P). UNet3DPhase was trained using a high-quality ground truth, whereas P2P was trained using noisy images with streaking artifacts. Two radiologists blinded to the reconstruction methods independently reviewed the sharpness, contrast, and artifact-freeness of the end-expiration images reconstructed from data collected at 16% of the Nyquist sampling rate. The generalized estimating equation method was used for statistical comparison. Motion vector fields were derived to examine the respiratory motion range of 4-dimensional images reconstructed using different methods. RESULTS: A total of 15 healthy participants and 18 patients with hepatic malignancy (50 ± 15 years, 6 women) were enrolled. Both reviewers found that the UNet3DPhase and P2P images had higher contrast (P < 0.01) and fewer artifacts (P < 0.01) than the CS images. The UNet3DPhase and P2P images were reported to be sharper than the CS images by 1 reviewer (P < 0.01) but not by the other reviewer (P = 0.22, P = 0.18). UNet3DPhase and P2P were similar in sharpness and contrast, whereas UNet3DPhase had fewer artifacts (P < 0.01). The motion vector lengths for the MCNUFFT800 and P2P800 images were comparable (10.5 ± 4.2 mm and 9.9 ± 4.0 mm, respectively), whereas both were significantly larger than CS2000 (7.0 ± 3.9 mm; P < 0.0001) and UNnet3DPhase800 (6.9 ± 3.2; P < 0.0001) images. CONCLUSIONS: Without a ground truth, P2P can reconstruct sharp, artifact-free, and high-contrast respiratory motion-resolved images from highly undersampled data. Unlike the CS and UNet3DPhase methods, P2P did not artificially reduce the respiratory motion range.

Bulk volume susceptibility difference between deoxyhemoglobin and oxyhemoglobin for HbA and HbS: A comparative study.

PURPOSE: Sickle cell anemia is a blood disorder that alters the morphology and the oxygen affinity of the red blood cells. Cerebral oxygen extraction fraction measurements using quantitative BOLD contrast have been used for assessing inadequate oxygen delivery and the subsequent risk of ischemic stroke in sickle cell anemia. The BOLD signal in MRI studies relies on Δχdo , the bulk volume susceptibility difference between fully oxygenated and fully deoxygenated blood. Several studies have measured Δχdo for normal hemoglobin A (HbA). However, it is not known whether the value is different for sickle hemoglobin. In this study, Δχdo was measured for both HbA and sickle hemoglobin. METHODS: Six sickle cell anemia patients and 6 controls were recruited. Various blood oxygenation levels were achieved through in vivo manipulations to keep the blood close to its natural state. To account for the differences in oxygen affinity, Hill's equations were used to translate partial pressure of oxygen to oxygen saturation for HbA, sickle hemoglobin, and fetal hemoglobin (HbF) separately. The pH and PCO2 corrections were performed. Temperature and magnetic field drift were controlled for. A multivariate generalized linear mixed model with random participant effect was used. RESULTS: Assuming that Δχdo is similar for HbA and HbF and that ΔχmetHb is 5/4 of Δχdo for HbA, it was found that the Δχdo values for HbA and sickle hemoglobin were not statistically significantly different from each other. CONCLUSION: The same Δχdo value can be used for both types of hemoglobin in quantitative BOLD analysis.

Quantification of myocardial oxygen extraction fraction: A proof-of-concept study.

PURPOSE: To demonstrate a proof of concept for the measurement of myocardial oxygen extraction fraction (mOEF) by a cardiovascular magnetic resonance technique. METHODS: The mOEF measurement was performed using an electrocardiogram-triggered double-echo asymmetric spin-echo sequence with EPI readout. Seven healthy volunteers (22-37 years old, 5 females) were recruited and underwent the same imaging scans at rest on 2 different days for reproducibility assessment. Another 5 subjects (23-37 years old, 4 females) underwent cardiovascular magnetic resonance studies at rest and during a handgrip isometric exercise with a 25% of maximal voluntary contraction. Both mOEF and myocardial blood volume values were obtained in septal regions from respective maps. RESULTS: The reproducibility was excellent for the measurements of mOEF in septal myocardium (coefficient of variation: 3.37%) and moderate for myocardial blood volume (coefficient of variation: 19.7%). The average mOEF and myocardial blood volume of 7 subjects at rest were 0.61 ± 0.05 and 11.0 ± 4.3%, respectively. The mOEF agreed well with literature values that were measured by PET in healthy volunteers. In the exercise study, there was no significant change in mOEF (0.61 ± 0.06 vs 0.62 ± 0.07) or myocardial blood volume (12 ± 6% vs 13 ± 4%) from rest to exercise, as expected. CONCLUSION: The implemented cardiovascular magnetic resonance method shows potential for the quantitative assessment of mOEF in vivo. Future technical work is needed to improve image quality and to further validate mOEF measurements.

Functional Connectivity Decreases with Metabolic Stress in Sickle Cell Disease.

OBJECTIVE: Children with sickle cell disease (SCD) experience cognitive deficits even when unaffected by stroke. Using functional connectivity magnetic resonance imaging (MRI) as a potential biomarker of cognitive function, we tested our hypothesis that children with SCD would have decreased functional connectivity, and that children experiencing the greatest metabolic stress, indicated by elevated oxygen extraction fraction, would have the lowest connectivity. METHODS: We prospectively obtained brain MRIs and cognitive testing in healthy controls and children with SCD. RESULTS: We analyzed data from 60 participants (20 controls and 40 with sickle cell disease). There was no difference in global cognition or cognitive subdomains between cohorts. However, we found decreased functional connectivity within the sensory-motor, lateral sensory-motor, auditory, salience, and subcortical networks in participants with SCD compared with controls. Further, as white matter oxygen extraction fraction increased, connectivity within the visual (p = 0.008, parameter estimate = -0.760 [95% CI = -1.297, -0.224]), default mode (p = 0.012, parameter estimate = -0.417 [95% CI = -0.731, -0.104]), and cingulo-opercular (p = 0.009, parameter estimate = -0.883 [95% CI = -1.517, -0.250]) networks decreased. INTERPRETATION: We conclude that there is diminished functional connectivity within these anatomically contiguous networks in children with SCD compared with controls, even when differences are not seen with cognitive testing. Increased white matter oxygen extraction fraction was associated with decreased connectivity in select networks. These data suggest that elevated oxygen extraction fraction and disrupted functional connectivity are potentially presymptomatic neuroimaging biomarkers for cognitive decline in SCD. ANN NEUROL 2020;88:995-1008.

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.

3D pediatric cranial bone imaging using high-resolution MRI for visualizing cranial sutures: a pilot study.

OBJECTIVE: There is an unmet need to perform imaging in young children and obtain CT-equivalent cranial bone images without subjecting the patients to radiation. In this study, the authors propose using a high-resolution fast low-angle shot golden-angle 3D stack-of-stars radial volumetric interpolated breath-hold examination (GA-VIBE) MRI sequence that is intrinsically robust to motion and has enhanced bone versus soft-tissue contrast. METHODS: Patients younger than 11 years of age, who underwent clinical head CT scanning for craniosynostosis or other cranial malformations, were eligible for the study. 3D reconstructed images created from the GA-VIBE MRI sequence and the gold-standard CT scan were randomized and presented to 3 blinded reviewers. For all image sets, each reviewer noted the presence or absence of the 6 primary cranial sutures and recorded on 5-point Likert scales whether they recommended a second scan be performed. RESULTS: Eleven patients (median age 1.8 years) underwent MRI after clinical head CT scanning was performed. Five of the 11 patients were sedated. Three clinicians reviewed the images, and there were no cases, either with CT scans or MR images, in which a reviewer agreed a repeat scan was required for diagnosis or surgical planning. The reviewers reported clear imaging of the regions of interest on 99% of the CT reviews and 96% of the MRI reviews. With CT as the standard, the sensitivity and specificity of the GA-VIBE MRI sequence to detect suture closure were 97% and 96%, respectively (n = 198 sutures read). CONCLUSIONS: The 3D reconstructed images using the GA-VIBE sequence in comparison to the CT scans created clinically acceptable cranial images capable of detecting cranial sutures. Future directions include reducing the scan time, improving motion correction, and automating postprocessing for clinical utility.

Hydroxyurea reduces cerebral metabolic stress in patients with sickle cell anemia.

Chronic transfusion therapy (CTT) prevents stroke in selected patients with sickle cell anemia (SCA). We have shown that CTT mitigates signatures of cerebral metabolic stress, reflected by elevated oxygen extraction fraction (OEF), which likely drives stroke risk reduction. The region of highest OEF falls within the border zone, where cerebral blood flow (CBF) nadirs; OEF in this region was reduced after CTT. The neuroprotective efficacy of hydroxyurea (HU) remains unclear. To test our hypothesis that patients receiving HU therapy have lower cerebral metabolic stress compared with patients not receiving disease-modifying therapy, we prospectively obtained brain magnetic resonance imaging scans with voxel-wise measurements of CBF and OEF in 84 participants with SCA who were grouped by therapy: no disease-modifying therapy, HU, or CTT. There was no difference in whole-brain CBF among the 3 cohorts (P = .148). However, whole-brain OEF was significantly different (P < .001): participants without disease-modifying therapy had the highest OEF (median 42.9% [interquartile range (IQR) 39.1%-49.1%]), followed by HU treatment (median 40.7% [IQR 34.9%-43.6%]), whereas CTT treatment had the lowest values (median 35.3% [IQR 32.2%-38.9%]). Moreover, the percentage of white matter at highest risk for ischemia, defined by OEF greater than 40% and 42.5%, was lower in the HU cohort compared with the untreated cohort (P = .025 and P = .034 respectively), but higher compared with the CTT cohort (P = .018 and P = .029 respectively). We conclude that HU may offer neuroprotection by mitigating cerebral metabolic stress in patients with SCA, but not to the same degree as CTT.

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO).

Relative cerebral blood volume (rCBV) cannot be used as a response metric in clinical trials, in part, because of variations in biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and postprocessing methods (PMs). This study leveraged a dynamic susceptibility contrast magnetic resonance imaging digital reference object to characterize rCBV consistency across 12 sites participating in the Quantitative Imaging Network (QIN), specifically focusing on differences in site-specific imaging protocols (IPs; n = 17), and PMs (n = 19) and differences due to site-specific IPs and PMs (n = 25). Thus, high agreement across sites occurs when 1 managing center processes rCBV despite slight variations in the IP. This result is most likely supported by current initiatives to standardize IPs. However, marked intersite disagreement was observed when site-specific software was applied for rCBV measurements. This study's results have important implications for comparing rCBV values across sites and trials, where variability in PMs could confound the comparison of therapeutic effectiveness and/or any attempts to establish thresholds for categorical response to therapy. To overcome these challenges and ensure the successful use of rCBV as a clinical trial biomarker, we recommend the establishment of qualifying and validating site- and trial-specific criteria for scanners and acquisition methods (eg, using a validated phantom) and the software tools used for dynamic susceptibility contrast magnetic resonance imaging analysis (eg, using a digital reference object where the ground truth is known).