Restriction spectrum imaging improves MRI-based prostate cancer detection

PURPOSE

To compare the diagnostic performance of restriction spectrum imaging (RSI), with that of conventional multi-parametric (MP) magnetic resonance imaging (MRI) for prostate cancer (PCa) detection in a blinded reader-based format.

METHODS

Three readers independently evaluated 100 patients (67 with proven PCa) who underwent MP-MRI and RSI within 6 months of systematic biopsy (N = 67; 23 with targeting performed) or prostatectomy (N = 33). Imaging was performed at 3 Tesla using a phased-array coil. Readers used a five-point scale estimating the likelihood of PCa present in each prostate sextant. Evaluation was performed in two separate sessions, first using conventional MP-MRI alone then immediately with MP-MRI and RSI in the same session. Four weeks later, another scoring session used RSI and T2-weighted imaging (T2WI) without conventional diffusion-weighted or dynamic contrast-enhanced imaging. Reader interpretations were then compared to prostatectomy data or biopsy results. Receiver operating characteristic curves were performed, with area under the curve (AUC) used to compare across groups.

RESULTS

MP-MRI with RSI achieved higher AUCs compared to MP-MRI alone for identifying high-grade (Gleason score greater than or equal to 4 + 3=7) PCa (0.78 vs. 0.70 at the sextant level; P < 0.001 and 0.85 vs. 0.79 at the hemigland level; P = 0.04). RSI and T2WI alone achieved AUCs similar to MP-MRI for high-grade PCa (0.71 vs. 0.70 at the sextant level). With hemigland analysis, high-grade disease results were similar when comparing RSI + T2WI with MP-MRI, although with greater AUCs compared to the sextant analysis (0.80 vs. 0.79).

CONCLUSION

Including RSI with MP-MRI improves PCa detection compared to MP-MRI alone, and RSI with T2WI achieves similar PCa detection as MP-MRI.

Discriminating rectal cancer grades using restriction spectrum imaging

PURPOSE

Restriction spectrum imaging (RSI) is a novel diffusion MRI model that separates water diffusion into several microscopic compartments. The restricted compartment correlating to the tumor cellularity is expected to be a potential indicator of rectal cancer aggressiveness. Our aim was to assess the ability of RSI model for rectal tumor grading.

METHODS

Fifty-eight patients with different rectal cancer grading confirmed by biopsy were involved in this study. DWI acquisitions were performed using single-shot echo-planar imaging (SS-EPI) with multi-b-values at 3 T. We applied a three-compartment RSI model, along with ADC model and diffusion kurtosis imaging (DKI) model, to DWI images of 58 patients. ROC and AUC were used to compare the performance of the three models in differentiating the low grade (G1 + G2) and high grade (G3). Mean ± standard deviation, ANOVA, ROC analysis, and correlation analysis were used in this study.

RESULTS

The volume fraction of restricted compartment C₁ from RSI was significantly correlated with grades (r = 0.403, P = 0.002). It showed significant difference between G1 and G3 (P = 0.008) and between G2 and G3 (P = 0.01). As for the low-grade and high-grade discrimination, significant difference was found in C₁ (P < 0.001). The AUC of C₁ for differentiation between low-grade and high-grade groups was 0.753 with a sensitivity of 72.0% and a specificity of 70.0%.

CONCLUSION

The three-compartment RSI model was able to discriminate the rectal cancer of low and high grades. The results outperform the traditional ADC model and DKI model in rectal cancer grading.

Diagnostic utility of Restriction Spectrum Imaging in the characterization of the peritumoral brain zone in glioblastoma: Analysis of overall and progression-free survival

PURPOSE

We studied the ability of Restriction Spectrum Imaging (RSI), a novel advanced diffusion imaging technique, to estimate levels of cellularity in different glioblastoma regions, evaluated their prognostic value compared with established clinical diffusion metrics such as fractional anisotropy (FA) and mean diffusivity (MD).

METHODS

Forty-two patients with untreated glioblastoma, IDH-wildtype, were examined with an advanced MRI tumor protocol. The region of interest (ROI) was obtained from the contrast-enhancing part of tumor and the peritumoral brain zones and then co-registered with RSI-cellularity index, FA and MD maps. Histogram parameters of diffusion metrics were assessed for all ROI locations and compared to MGMT promoter methylation status and survival. The ability of RSI-cellularity index, FA, and MD to stratify survival and were assessed by Cox proportional hazard regression, adjusted for significant clinical predictors.

RESULTS

The highest RSI-cellularity index was measured in contrast-enhancing tumor core with a negative gradient from tumor core to the periphery of peritumoral zone with predictive accuracy 81 % (P < 0.001). Shorter overall survival was significant associated with higher RSI-cellularity index (hazard ratio (HR) 3.6, 95 % confidence interval (CI) 1.3-9.5, P = 0.002) with synchronal decrease in MD (HR 0.31, 95 %CI 0.1-0.8, P = 0.008) in the contrast-enhanced tumor core. This association was also consistent for RSI-cellularity index value measured in the peri-enhancing zone (HR 3.6, 95 % CI 1.0-12.3, P = 0.041). No statistically significant differences were noted between RSI-cellularity index, FA, nor MD and MGMT promoter methylation.

CONCLUSION

RSI-cellularity index may be used as prognostic biomarker to improve risk stratification in patients with glioblastoma.

New prostate MRI techniques and sequences

Prostate MRI has seen increasing interest in recent years and has led to the development of new MRI techniques and sequences to improve prostate cancer (PCa) diagnosis which are reviewed in this article. Numerous studies have focused on improving image quality (segmented DWI) and faster acquisition (compressed sensing, k-t-SENSE, PROPELLER). An increasing number of studies have developed new quantitative and computer-aided diagnosis methods including artificial intelligence (PROSTATEx challenge) that mitigate the subjective nature of mpMRI interpretation. MR fingerprinting allows rapid, simultaneous generation of quantitative maps of multiple physical properties (T1, T2), where PCa are characterized by lower T1 and T2 values. New techniques like luminal water imaging (LWI), restriction spectrum imaging (RSI), VERDICT and hybrid multi-dimensional MRI (HM-MRI) have been developed for microstructure imaging, which provide information similar to histology. The distinct MR properties of tissue components and their change with the presence of cancer is used to diagnose prostate cancer. LWI is a T2-based imaging technique where long T2-component corresponding to luminal water is reduced in PCa. RSI and VERDICT are diffusion-based techniques where PCa is characterized by increased signal from intra-cellular restricted water and increased intracellular volume fraction, respectively, due to increased cellularity. VERDICT also reveal loss of extracellular-extravascular space in PCa due to loss of glandular structure. HM-MRI measures volumes of prostate tissue components, where PCa has reduced lumen and stromal and increased epithelium volume similar to results shown in histology. Similarly, molecular imaging using hyperpolarized ¹³C imaging has been utilized.

Diagnostic utility of restriction spectrum imaging (RSI) in glioblastoma patients after concurrent radiation-temozolomide treatment: A pilot study

Discriminating between tumor recurrence and treatment effects in glioblastoma patients undergoing radiation-temozolomide (RT/TMZ) therapy remains a major clinical challenge. Here, we report a pilot study to determine the utility of restriction spectrum imaging (RSI), an advanced diffusion-weighted MRI (DWI) technique that affords meso-scale resolution of cell density, in this assessment. A retrospective review of 31 patients with glioblastoma treated between 2011 and 2017 who underwent surgical resection or biopsy over radiographic concern for tumor recurrence following RT/TMZ was performed. All patients underwent RSI prior to surgical resection. Diagnostic utility of RSI for tumor recurrence was determined in comparison to histopathology. Analysis of surgical specimens revealed treatment effects in 6/31 patients (19%) and tumor recurrence in 25/31 patients (81%). There was general concordance between the measured RSI signal and histopathologic diagnosis. RSI was negative in 5/6 patients (83%) in patients with histological evidence of treatment effects. RSI was positive in 21/25 patients (84%) in patients with tumor recurrence. The sensitivity, specificity, positive and negative predictive values of RSI for glioblastoma recurrence were 84%, 86%, 95%, and 60%, respectively. Histopathologic review showed agreement between the RSI signal and cellularity of the tumor specimen. These data support the use of RSI in the evaluation of treatment effects versus tumor recurrence in glioblastoma patients after RT-TMZ therapy.

Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI

Current challenges of using serum prostate-specific antigen (PSA) level-based screening, such as the increased false positive rate, inability to detect clinically significant prostate cancer (PCa) with random biopsy, multifocality in PCa, and the molecular heterogeneity of PCa, can be addressed by integrating advanced multiparametric MR imaging (mpMRI) approaches into the diagnostic workup of PCa. The standard method for diagnosing PCa is a transrectal ultrasonography (TRUS)-guided systematic prostate biopsy, but it suffers from sampling errors and frequently fails to detect clinically significant PCa. mpMRI not only increases the detection of clinically significant PCa, but it also helps to reduce unnecessary biopsies because of its high negative predictive value. Furthermore, non-Cartesian image acquisition and compressed sensing have resulted in faster MR acquisition with improved signal-to-noise ratio, which can be used in quantitative MRI methods such as dynamic contrast-enhanced (DCE)-MRI. With the growing emphasis on the role of pre-biopsy mpMRI in the evaluation of PCa, there is an increased demand for innovative MRI methods that can improve PCa grading, detect clinically significant PCa, and biopsy guidance. To meet these demands, in addition to routine T1-weighted, T2-weighted, DCE-MRI, diffusion MRI, and MR spectroscopy, several new MR methods such as restriction spectrum imaging, vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) method, hybrid multi-dimensional MRI, luminal water imaging, and MR fingerprinting have been developed for a better characterization of the disease. Further, with the increasing interest in combining MR data with clinical and genomic data, there is a growing interest in utilizing radiomics and radiogenomics approaches. These big data can also be utilized in the development of computer-aided diagnostic tools, including automatic segmentation and the detection of clinically significant PCa using machine learning methods.

Prenatal and childhood air pollution exposure, cellular immune biomarkers, and brain connectivity in early adolescents

Introduction

Ambient air pollution is a neurotoxicant with hypothesized immune-related mechanisms. Adolescent brain structural and functional connectivity may be especially vulnerable to ambient pollution due to the refinement of large-scale brain networks during this period, which vary by sex and have important implications for cognitive, behavioral, and emotional functioning. In the current study we explored associations between air pollutants, immune markers, and structural and functional connectivity in early adolescence by leveraging cross-sectional sex-stratified data from the Adolescent Brain Cognitive Development℠ Study®.

Methods

Pollutant concentrations of fine particulate matter, nitrogen dioxide, and ozone were assigned to each child's primary residential address during the prenatal period and childhood (9-10 years-old) using an ensemble-based modeling approach. Data collected at 11-13 years-old included resting-state functional connectivity of the default mode, frontoparietal, and salience networks and limbic regions of interest, intracellular directional and isotropic diffusion of available white matter tracts, and markers of cellular immune activation. Using partial least squares correlation, a multivariate data-driven method that identifies important variables within latent dimensions, we investigated associations between 1) pollutants and structural and functional connectivity, 2) pollutants and immune markers, and 3) immune markers and structural and functional connectivity, in each sex separately.

Results

Air pollution exposure was related to white matter intracellular directional and isotropic diffusion at ages 11-13 years, but the direction of associations varied by sex. There were no associations between pollutants and resting-state functional connectivity at ages 11-13 years. Childhood exposure to nitrogen dioxide was negatively correlated with white blood cell count in males. Immune biomarkers were positively correlated with white matter intracellular directional diffusion in females and both white matter intracellular directional and isotropic diffusion in males. Lastly, there was a reliable negative correlation between lymphocyte-to-monocyte ratio and default mode network resting-state functional connectivity in females, as well as a compromised immune marker profile associated with lower resting-state functional connectivity between the salience network and the left hippocampus in males. In post-hoc exploratory analyses, we found that the PLSC-identified white matter tracts and resting-state networks related to processing speed and cognitive control performance from the NIH Toolbox.

Conclusions

We identified novel links between childhood nitrogen dioxide and cellular immune activation in males, and brain network connectivity and immune markers in both sexes. Future research should explore the potentially mediating role of immune activity in how pollutants affect neurological outcomes as well as the potential consequences of immune-related patterns of brain connectivity in service of improved brain health for all.

Automated Patient-level Prostate Cancer Detection with Quantitative Diffusion Magnetic Resonance Imaging

Background

Multiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSI_rs).

Objective

To evaluate RSI_rs for automated patient-level detection of csPCa.

Design setting and participants

We retrospectively studied all patients (n = 151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI.

Intervention

We calculated the maximum RSI_rs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records.

Outcome measurements and statistical analysis

We compared the performance of RSI_rs, ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α = 0.05. We also explored whether the combination of PI-RADS and RSI_rs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones.

Results and limitations

AUC values for ADC, RSI_rs, and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSI_rs and PI-RADS were each superior to ADC for patient-level detection of csPCa (p < 0.0001). RSI_rs alone was comparable with PI-RADS (p = 0.8). The combination of PI-RADS and RSI_rs had an AUC of 0.85 (0.78, 0.91) and was superior to either PI-RADS or RSI_rs alone (p < 0.05). Similar patterns were seen in the peripheral and transition zones.

Conclusions

RSI_rs is a promising quantitative marker for patient-level csPCa detection, warranting a prospective study.

Patient summary

We evaluated a rapid, advanced prostate magnetic resonance imaging technique called restriction spectrum imaging to see whether it could give an automated score that predicted the presence of clinically significant prostate cancer. The automated score worked about as well as expert radiologists' interpretation. The combination of the radiologists' scores and automated score might be better than either alone.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Longitudinal Evidence of a Vicious Cycle Between Nucleus Accumbens Microstructure and Childhood Weight Gain

PURPOSE

Pediatric obesity is a growing public health concern. Previous work has observed diet to impact nucleus accumbens (NAcc) inflammation in rodents, measured by the reactive proliferation of glial cells. Recent work in humans has demonstrated a relationship between NAcc cell density-a proxy for neuroinflammation-and weight gain in youth; however, the directionality of this relationship in the developing brain and association with diet remains unknown.

METHODS

Waist circumference (WC) and NAcc cell density were collected in a large cohort of children (n > 2,000) participating in the Adolescent Brain Cognitive Development (ABCD) Study (release 3.0) at baseline (9-10 y) and at a Year 2 follow-up (11-12 y). Latent change score modeling (LCSM) was used to disentangle contributions of baseline measures to two-year changes in WC percentile and NAcc cellularity. In addition, the role of NAcc cellularity in mediating the relationship between diet and WC percentile was assessed using dietary intake data collected at Year 2.

RESULTS

LCSM indicates that baseline WC percentile influences change in NAcc cellularity and that baseline NAcc cell density influences change in WC percentile. NAcc cellularity was significantly associated with WC percentile at Year 2 and mediated the relationship between dietary fat consumption and WC percentile.

CONCLUSIONS

These results implicate a vicious cycle whereby NAcc cell density biases longitudinal changes in WC percentile and vice versa. Moreover, NAcc cell density may mediate the relationship between diet and weight gain in youth. These findings suggest that diet-induced inflammation of reward circuitry may lead to behavioral changes that further contribute to weight gain.

Premature white matter microstructure in female children with a history of concussion

Childhood concussion may interfere with neurodevelopment and influence cognition. Females are more likely to experience persistent symptoms after concussion, yet the sex-specific impact of concussion on brain microstructure in children is understudied. This study examined white matter and cortical microstructure, based on neurite density (ND) from diffusion-weighted MRI, in 9-to-10-year-old children in the Adolescent Brain Cognitive Development Study with (n = 336) and without (n = 7368) a history of concussion, and its relationship with cognitive performance. Multivariate regression was used to investigate relationships between ND and group, sex, and age in deep and superficial white matter, subcortical structures, and cortex. Partial least square correlation was performed to identify associations between ND and performance on NIH Toolbox tasks in children with concussion. All tissue types demonstrated higher ND with age, reflecting brain maturation. Group comparisons revealed higher ND in deep and superficial white matter in females with concussion. In female but not male children with concussion, there were significant associations between ND and performance on cognitive tests. These results demonstrate a greater long-term impact of childhood concussion on white matter microstructure in females compared to males that is associated with cognitive function. The increase in ND in females may reflect premature white matter maturation.

Utility of quantitative measurement of T2 using restriction spectrum imaging for detection of clinically significant prostate cancer

The Restriction Spectrum Imaging restriction score (RSIrs) has been shown to improve the accuracy for diagnosis of clinically significant prostate cancer (csPCa) compared to standard DWI. Both diffusion and T2 properties of prostate tissue contribute to the signal measured in DWI, and studies have demonstrated that each may be valuable for distinguishing csPCa from benign tissue. The purpose of this retrospective study was to (1) determine whether prostate T2 varies across RSI compartments and in the presence of csPCa, and (2) evaluate whether csPCa detection with RSIrs is improved by acquiring multiple scans at different TEs to measure compartmental T2 (cT2). Data includes two cohorts scanned for csPCa with 3T multi-b-value diffusion-weighted sequences acquired at multiple TEs. cT2 values were computed from multi-TE RSI data and compared by compartment. CsPCa detection was compared between RSIrs and a logistic regression model (LRM) to predict the probability of csPCa using cT2 in combination with RSI measurements. Two-sample t-tests (α = 0.05) and the area under the receiver operating characteristic curve (AUC) were used for the statistical analyses. In both cohorts, T2 was different (p < 0.05) across the four RSI compartments (C1, C2, C3, C4). Voxel-level, cohort 1: T2 was different in csPCa for C1, C2, C3 (p < 0.001). Patient-level, cohort 1: T2 was different in csPCa patients in C3 (p = 0.02); cohort 2: T2 differed in csPCa patients in C1 (p = 0.01), C3 (p = 0.01) and C4 (p < 0.01). Voxel-level csPCa detection: cT2 did not improve discrimination over RSIrs alone (p = 0.9). Patient-level: RSIrs and the LRM performed better than diffusion alone (p < 0.001), but the difference in AUCs between RSIrs and the LRM was not significantly different (p = 0.54). In conclusion, significant differences in cT2 were observed between normal and cancerous prostatic tissue. With our data, however, consideration of cT2 in addition to diffusion did not significantly improve cancer detection performance.

Disrupted Maturation of White Matter Microstructure After Concussion Is Associated With Internalizing Behavior Scores in Female Children

BACKGROUND

Some children who experience concussions, particularly females, develop long-lasting emotional and behavioral problems. Establishing the potential contribution of preexisting behavioral problems and disrupted white matter maturation has been challenging due to a lack of preinjury data.

METHODS

From the Adolescent Brain Cognitive Development cohort, 239 (90 female) children age 12.1 ± 0.6 years who experienced a concussion after study entry at 10.0 ± 0.6 years were compared to 6438 (3245 female) children without head injuries who were age 9.9 ± 0.6 years at baseline and 12.0 ± 0.6 years at follow-up. The Child Behavior Checklist was used to assess internalizing and externalizing behavior at study entry and follow-up. In the children with magnetic resonance imaging data available (concussion n = 134, comparison n = 3520), deep and superficial white matter was characterized by neurite density from restriction spectrum image modeling of diffusion magnetic resonance imaging. Longitudinal ComBat harmonization removed scanner effects. Linear regressions modeled 1) behavior problems at follow-up controlling for baseline behavior, 2) impact of concussion on white matter maturation, and 3) contribution of deviations in white matter maturation to postconcussion behavior problems.

RESULTS

Only female children with concussion had higher internalizing behavior problem scores. The youngest children with concussion showed less change in superficial white matter neurite density over 2 years than children with no concussion. In females with concussion, less change in superficial white matter neurite density was correlated with increased internalizing behavior problem scores.

CONCLUSIONS

Concussions in female children are associated with emotional problems beyond preinjury levels. Injury to superficial white matter may contribute to persistent internalizing behavior problems in females.

Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging

BACKGROUND

To compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue.

METHODS

This prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model.

RESULTS

Almost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively).

CONCLUSIONS

Quantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.