Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke.

Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To investigate the interchangeability of DL-accelerated MRI with conventional MRI in patients with suspected acute ischemic stroke at 1.5 T. Materials and Methods In this prospective study, 211 participants with suspected acute stroke underwent clinically indicated MRI at 1.5 T between June 2022 and March 2023. For each participant, conventional MRI (including T1-weighted, T2-weighted, T2*-weighted, T2 fluid-attenuated inversion-recovery, and diffusion-weighted imaging; 14 minutes 18 seconds) and DL-accelerated MRI (same sequences; 3 minutes 4 seconds) were performed. The primary end point was the interchangeability between conventional and DL-accelerated MRI for acute ischemic infarction detection. Secondary end points were interchangeability regarding the affected vascular territory and clinically relevant secondary findings (eg, microbleeds, neoplasm). Three readers evaluated the overall occurrence of acute ischemic stroke, affected vascular territory, clinically relevant secondary findings, overall image quality, and diagnostic confidence. For acute ischemic lesions, size and signal intensities were assessed. The margin for interchangeability was chosen as 5%. For interrater agreement analysis and interrater reliability analysis, multirater Fleiss κ and the intraclass correlation coefficient, respectively, was determined. Results The study sample consisted of 211 participants (mean age, 65 years ± 16 [SD]); 123 male and 88 female). Acute ischemic stroke was confirmed in 79 participants. Interchangeability was demonstrated for all primary and secondary end points. No individual equivalence indexes (IEIs) exceeded the interchangeability margin of 5% (IEI, -0.002 [90% CI: -0.007, 0.004]). Almost perfect interrater agreement was observed (P > .91). DL-accelerated MRI provided higher overall image quality (P < .001) and diagnostic confidence (P < .001). The signal properties of acute ischemic infarctions were similar in both techniques and demonstrated good to excellent interrater reliability (intraclass correlation coefficient, ≥0.8). Conclusion Despite being four times faster, DL-accelerated brain MRI was interchangeable with conventional MRI for acute ischemic lesion detection. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Haller in this issue.

In Vivo Microstructure Imaging in Oropharyngeal Squamous Cell Carcinoma Using the Random Walk With Barriers Model.

BACKGROUND: Apparent diffusion coefficient is not specifically sensitive to tumor microstructure and therapy-induced cellular changes. PURPOSE: To investigate time-dependent diffusion imaging with the short-time-limit random walk with barriers model (STL-RWBM) for quantifying microstructure parameters and early cancer cellular response to therapy. STUDY TYPE: Prospective. POPULATION: Twenty-seven patients (median age of 58 years and 7.4% of females) with p16+/p16- oropharyngeal/oral cavity squamous cell carcinomas (OPSCC/OCSCC) underwent MRI scans before therapy, of which 16 patients had second scans at 2 weeks of the 7-weeks chemoradiation therapy (CRT). FIELD STRENGTH/SEQUENCE: 3-T, diffusion sequence with oscillating gradient spine echo (OGSE) and pulse gradient spin echo (PGSE). ASSESSMENT: Diffusion weighted images were acquired using OGSE and PGSE. Effective diffusion times were derived for the STL-RWBM to estimate free diffusion coefficient D0 , volume-to-surface area ratio of cellular membranes V/S, and cell membrane permeability κ. Mean values of these parameters were calculated in tumor volumes. STATISTICAL TESTS: Tumor microstructure parameters were compared with clinical stages of p16+ I-II OPSCC, p16+ III OPSCC, and p16- IV OCSCC by Spearman's rank correlation and with digital pathological analysis of a resected tissue sample. Tumor microstructure parameter responses during CRT in the 16 patients were assessed by paired t-tests. A P-value of <0.05 was considered statistically significant. RESULTS: The derived effective diffusion times affected estimated values of V/S and κ by 40%. The tumor V/S values were significantly correlated with clinical stages (r = 0.47) as an increase from low to high clinical stages. The in vivo estimated cell size agreed with one from pathological analysis of a tissue sample. Early tumor cellular responses showed a significant increase in D0 (14%, P = 0.03) and non-significant increases in κ (56%, P = 0.6) and V/S (10%, P = 0.1). DATA CONCLUSION: Effective diffusion time estimation might impact microstructure parameter estimation. The tumor V/S was correlated with OPSCC/OCSCC clinical stages. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient.

BACKGROUND: This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters. METHODS: A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices. RESULTS: In enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs. CONCLUSIONS: Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer.

BACKGROUND: Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer. PURPOSE: To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI. STUDY TYPE: Retrospective. SUBJECTS: Sixty-three women (mean age: 58 [range: 32-85] years) with endometrial cancer. FIELD STRENGTH/SEQUENCE: 3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences. ASSESSMENT: Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADCOGSE ) and PGSE (ADCPGSE ) as well as the ADC ratio (ADCOGSE /ADCPGSE ) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated. STATISTICAL TESTS: Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADCOGSE , ADCPGSE , and ADCOGSE /ADCPGSE with prognostic factors were examined using the Kendall rank correlation coefficient, Mann-Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant. RESULTS: Compared with ADCOGSE and ADCPGSE , ADCOGSE /ADCPGSE was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADCOGSE /ADCPGSE for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83-0.98; observer 2, 0.84, 95% CI: 0.73-0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68-0.89; observer 2, 0.76, 95% CI: 0.63-0.86) were significantly higher than that of ADCOGSE and ADCPGSE . DATA CONCLUSION: The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI.

BACKGROUND: This study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases. METHODS: A retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz - ADC0Hz and the relative ADC change (rcADC): (ADC50Hz - ADC0Hz)/ ADC0Hz × 100 (%). RESULTS: The mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10-3mm2/s vs. 0.14 ± 0.03 × 10-3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001). CONCLUSIONS: The time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

Investigation of time-dependent diffusion in extra-axial brain tumors using oscillating-gradient spin-echo.

Oscillating gradient spin-echo (OGSE) sequences provide access to short diffusion times and may provide insight into micro-scale internal structures of pathologic lesions based on an analysis of changes in diffusivity with differing diffusion times. We hypothesized that changes in diffusivity acquired with a shorter diffusion time may permit elucidation of properties related to the internal structure of extra-axial brain tumors. This study aimed to investigate the utility of changes in diffusivity between short and long diffusion times for characterizing extra-axial brain tumors. In total, 12 patients with meningothelial meningiomas, 13 patients with acoustic neuromas, and 11 patients with pituitary adenomas were scanned with a 3 T magnetic resonance imaging (MRI) scanner with diffusion-weighted imaging (DWI) using OGSE and pulsed gradient spin-echo (PGSE) (effective diffusion times [Δeff]: 6.5 ms and 35.2 ms) with b-values of 0 and 1000 s/mm2. Relative percentage changes between shorter and longer diffusion times were calculated using region-of-interest (ROI) analysis of brain tumors on λ1, λ2, λ3, and mean diffusivity (MD) maps. The diffusivities of PGSE, OGSE, and relative percentage changes were compared among each tumor type using a multiple comparisons Steel-Dwass test. The mean (standard deviation) MD at Δeff of 6.5 ms was 1.07 ± 0.23 10-3 mm2/s, 1.19 ± 0.18 10-3 mm2/s, 1.19 ± 0.21 10-3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) MD at Δeff of 35.2 ms was 0.93 ± 0.22 10-3 mm2/s, 1.07 ± 0.19 10-3 mm2/s, 0.82 ± 0.21 10-3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) of the relative percentage change was 15.7 ± 4.4%, 12.4 ± 8.2%, 46.8 ± 11.3% for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. Compared to meningiomas and acoustic neuromas, pituitary adenoma exhibited stronger diffusion time-dependence with diffusion times between 6.5 ms and 35.2 ms (P < 0.05). In conclusion, differences in diffusion time-dependence may be attributed to differences in the internal structures of brain tumors. DWI with a short diffusion time may provide additional information on the microstructure of each tumor and contribute to tumor diagnosis.

Patient specific distortion detection and mitigation in MR images used for stereotactic radiosurgery.

Objective.In MRI-based radiation therapy planning, mitigating patient-specific distortion with standard high bandwidth scans can result in unnecessary sacrifices of signal to noise ratio. This study investigates a technique for distortion detection and mitigation on a patient specific basis.Approach.Fast B0 mapping was performed using a previously developed technique for high-resolution, large dynamic range field mapping without the need for phase unwrapping algorithms. A phantom study was performed to validate the method. Distortion mitigation was validated by reducing geometric distortion with increased acquisition bandwidth and confirmed by both the B0 mapping technique and manual measurements. Images and contours from 25 brain stereotactic radiosurgery patients and 95 targets were analyzed to estimate the range of geometric distortions expected in the brain and to estimate bandwidth required to keep all treatment targets within the ±0.5 mm iso-distortion contour.Main Results.The phantom study showed, at 3 T, the technique can measure distortions with a mean absolute error of 0.12 mm (0.18 ppm), and a maximum error of 0.37 mm (0.6 ppm). For image acquisition at 3 T and 1.0 mm resolution, mean absolute distortion under 0.5 mm in patients required bandwidths from 109 to 200 Hz px-1for patients with the least and most distortion, respectively. Maximum absolute distortion under 0.5 mm required bandwidths from 120 to 390 Hz px-1.Significance.The method for B0 mapping was shown to be valid and may be applied to assess distortion clinically. Future work will adapt the readout bandwidth to prospectively mitigate distortion with the goal to improve radiosurgery treatment outcomes by reducing healthy tissue exposure.

The Rate of Apparent Diffusion Coefficient Change With Diffusion Time on Breast Diffusion-Weighted Imaging Depends on Breast Tumor Types and Molecular Prognostic Biomarker Expression.

INTRODUCTION: The aim of this study was to investigate the variation of apparent diffusion coefficient (ADC) values with diffusion time according to breast tumor type and prognostic biomarkers expression. MATERIALS AND METHODS: A total of 201 patients with known or suspected breast tumors were prospectively enrolled in this study, and 132 breast tumors (86 malignant and 46 benign) were analyzed. Diffusion-weighted imaging scans with 2 diffusion times were acquired on a clinical 3-T magnetic resonance imaging scanner using oscillating and pulsed diffusion-encoding gradients (effective diffusion times, 4.7 and 96.6 milliseconds) and b values of 0 and 700 s/mm2. Diagnostic performances to differentiate malignant and benign breast tumors for ADC values at short and long diffusion times (ADCshort and ADClong), ΔADC (the rate of change in ADC values with diffusion time), ADC0-1000 (ADC value from a standard protocol), and standard reading including dynamic contrast-enhanced magnetic resonance imaging (BI-RADS) were investigated. The correlations of ADCshort, ADClong, and ΔADC values with hormone receptor expression and breast cancer subtypes were also analyzed. RESULTS: The ADC values were lower, and ΔADC was higher in malignant tumors compared with benign tumors. The specificity of ADC values at all diffusion times and ΔADC values for differentiating malignant and benign breast tumors was superior to that of BI-RADS (87.0%-95.7% vs 73.9%), whereas the sensitivity was inferior (87.2%-90.7% vs 100%). Lower ADCshort and ADC0-1000 in ER-positive compared with ER-negative cancers (false discovery rate [FDR]-adjusted P = 0.037 and 0.018, respectively) and lower ADCshort, ADClong, and ADC0-1000 in progesterone receptor-positive compared with progesterone receptor-negative cancers (FDR-adjusted P = 0.037, 0.036, and 0.018, respectively) were found. Ki-67-positive cancers had larger ΔADCs than Ki-67-negative cancers (FDR-adjusted P = 0.018). CONCLUSIONS: The ADC values vary with different diffusion time and vary in correlation with molecular biomarkers, especially Ki-67. Those results suggest that the diffusion time, which should be reported, might be a useful parameter to consider for breast cancer management.

Differentiation of high-grade and low-grade intra-axial brain tumors by time-dependent diffusion MRI.

INTRODUCTION: Oscillating gradient spin-echo (OGSE) sequences enable acquisitions with shorter diffusion times. There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) values in patients with cancer. However, little evidence exists regarding its usefulness for differentiating between high-grade and low-grade brain tumors. The purpose of this study is to investigate the utility of changes in the ADC value between short and long diffusion times in distinguishing low-grade and high-grade brain tumors. MATERIAL AND METHODS: Eleven patients with high-grade brain tumors and ten patients with low-grade brain tumors were scanned using a 3 T magnetic resonance imaging with diffusion-weighted imaging (DWI) using OGSE and PGSE (effective diffusion time [Δeff]: 6.5 ms and 35.2 ms) and b-values of 0 and 1000 s/mm2. Using a region of interest (ROI) analysis of the brain tumors, we measured the ADC for two Δeff (ADCΔeff) values and computed the subtraction ADC (ΔADC = ADC6.5 ms - ADC35.2 ms) and the relative ADC (ΔADC = (ADC6.5 ms - ADC35.2 ms) / ADC35.2 ms × 100). The maximum values for the subtraction ADC (ΔADCmax) and the relative ADC (rADCmax) on the ROI were compared between low-grade and high-grade tumors using the Wilcoxon rank-sum test. A P-value <.05 was considered significant. The ROIs were also placed in the normal white matter of patients with high- and low-grade brain tumors, and ΔADCmax values were determined. RESULTS: High-grade tumors had significantly higher ΔADCmax and rADCmax than low-grade tumors. The ΔADCmax values of the normal white matter were lower than the ΔADCmax of high- and low-grade brain tumors. CONCLUSION: The dependence of ADC values on diffusion time between 6.5 ms and 35.2 ms was stronger in high-grade tumors than in low-grade tumors, suggesting differences in internal tissue structure. This finding highlights the importance of reporting diffusion times in ADC evaluations and might contribute to the grading of brain tumors using DWI.

Exploratory study of geometric distortion correction of prostate diffusion-weighted imaging using B0 map acquisition.

BACKGROUND: Evaluation of prostate MRI relies on diffusion-weighted imaging (DWI), commonly distorted by susceptibility artifacts, thereby creating a need for approaches to correct such distortion. PURPOSE: To compare geometric distortion on prostate MRI between standard DWI and a geometric distortion correction method for DWI described as static distortion correction DWI (SDC DWI). STUDY TYPE: Retrospective case study. POPULATION: Thirty patients (ages 31-81 years) undergoing prostate MRI. SEQUENCE: Geometric distortions from echo planar imaging were corrected with the SDC DWI protocol, which first acquires a B0 -field map to estimate geometric distortions. ASSESSMENT: Contours of the prostate were placed on axial T2 -weighted imaging (T2 WI) as an anatomic standard. Pixel shifts and apparent diffusion coefficient (ADC) values were compared between prostate contours applied to the SDC DWI and standard DWI sequences. Detailed characterization of the impact of SDC DWI was performed in three representative patients. STATISTICAL TESTS: One-way analysis of variance (ANOVA) test, Spearman correlation test, and Bland-Altman plots were calculated. RESULTS: There was significantly greater overlap of the SDC DWI prostate region of interest (ROI) with T2 WI than standard DWI with T2 WI (10.56 cm2 ± 3.14, P < 0.05). R2 of ADC values from standard DWI vs. SDC DWI in the 30 patients ranged from 0.02-0.94 (mean 0.60). A patient without susceptibility artifact demonstrated minimal pixel shift ranging from 0.6-1.3 mm and high correlation of ADC values (R2 = 0.89) between SDC DWI and standard DWI. A patient with rectal gas showed greater pixel shift (range: -2.5 to -0.5 mm) and less ADC value correlation (R2 = 0.69). A patient with a pelvic phlebolith adjacent to the prostate showed an even greater pixel shift (range: 10-16 mm) and decreased ADC correlation (R2 = 0.21). DATA CONCLUSION: SDC DWI appears to correct for susceptibility-related pixel shifts in the prostate compared with standard DWI, which may have value for assessing prostate lesions obscured by geometric warping. Level of Evidence 4 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2019;50:1614-1619.

Choroid plexus cysts analyzed using diffusion-weighted imaging with short diffusion-time.

INTRODUCTION: Oscillating gradient spin-echo (OGSE) sequences can shorten diffusion times by replacing the long-lasting diffusion-sensitizing gradients used in pulsed gradient spin-echo (PGSE) methods with rapidly oscillating gradients. To obtain information regarding the internal structure of choroid plexus cysts that appear hyperintense on diffusion-weighted imaging (DWI), we investigated the apparent diffusion coefficient (ADC) values acquired with a shorter diffusion time using an OGSE sequence. MATERIAL AND METHODS: Twenty-seven patients with choroid plexus cysts were scanned using a 3 T magnetic resonance scanner. DWI was performed with both OGSE and PGSE, with effective diffusion times (Δeff) of 6.5 and 35.2 ms, respectively. ADC values for choroid plexus cysts, white matter (WM), and cerebrospinal fluid (CSF) were measured. The ADC values obtained with the shorter and longer diffusion times were compared using the Wilcoxon signed-rank test. P < .05 was considered significant. RESULTS: The ADC values of choroid plexus cysts and WM were significantly higher at the Δeff of 6.5 ms on OGSE than with the Δeff of 35.2 ms on PGSE. The ADC values of CSF were significantly lower at the Δeff of 6.5 ms on OGSE than with the Δeff of 35.2 ms on PGSE. The ADC values of choroid plexus cysts were lower than the ADC values of CSF with Δeff of 35.2 and 6.5 ms. CONCLUSIONS: The dependence of ADC values on the diffusion time in choroid plexus cysts suggested spatially restricted diffusion. In measurements obtained with short diffusion times, the lower ADC values for choroid plexus cysts in comparison with the CSF indicated the presence of spatially restricted diffusion and increased cyst viscosity.

Time-dependent diffusion MRI to distinguish malignant from benign head and neck tumors.

BACKGROUND: There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) values in cancers; however, little evidence exists regarding its utility to differentiate malignant from benign head and neck tumors. PURPOSE: To investigate the utility of ADC value changes in distinguishing between malignant and benign head and neck tumors using the different diffusion times obtained from oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) MRI sequences. STUDY TYPE: Prospective. SUBJECTS: Thirty-one consecutive patients with suspected head and neck tumors and a phantom. FIELD STRENGTH/SEQUENCE: 3T MRI with diffusion-weighted imaging (DWI) using OGSE (effective diffusion time: 4.3 msec) and PGSE (effective diffusion time: 82.6 msec) sequences and b-values of 0 and 700 s/mm2 . ASSESSMENT: ADC values using OGSE (ADCOGSE ) and PGSE (ADCPGSE ) and relative ADC value changes between ADCOGSE and ADCPGSE . STATISTICAL TESTS: Wilcoxon test, Mann-Whitney test, and McNemar test. RESULTS: Relative ADC changes for each polyvinylpyrrolidone (PVP) and water in the phantom between OGSE and PGSE sequences were small (relative ADC change within 0.6%). Malignant tumors had significantly smaller ADCOGSE and ADCPGSE values than benign tumors (P < 0.001 and < 0.0001, respectively). Significantly larger relative ADC changes were observed in malignant compared with benign head and neck tumors (P < 0.0001). ADCPGSE values were significantly lower than ADCOGSE values in both malignant and benign head and neck tumors (0.97 vs. 1.28 × 10-3 mm2 /s: P < 0.0001 and 1.93 vs. 1.99 × 10-3 mm2 /s: P = 0.0056, respectively). Relative ADC change and ADCPGSE tended to have higher diagnostic performance than ADCOGSE , with area under the curve (AUC) values of 0.97, 0.96, and 0.89, respectively. DATA CONCLUSION: ADC values obtained using the PGSE sequence were lower than those obtained with OGSE. This difference was larger for malignant than benign tumors, suggesting differences in tissue structure (diffusion hindrance) or cell permeability, revealed by changes in diffusion time. The results underline the potential importance of reporting diffusion time for interpretation of head and neck diffusion MRI. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:88-95.

Multiparametric Whole-body MRI with Diffusion-weighted Imaging and ADC Mapping for the Identification of Visceral and Osseous Metastases From Solid Tumors.

RATIONALE AND OBJECTIVES: The purpose of this study was to investigate the use of multiparametric, whole-body, diffusion-weighted imaging (WB-DWI) and apparent diffusion coefficient (ADC) maps with T2-weighted magnetic resonance imaging (MRI) at 3T for the detection and monitoring of metastatic disease in patients. MATERIALS AND METHODS: Fifty-four participants (32 healthy subjects and 22 patients) were scanned with WB-DWI methods using a 3T MRI scanner. Axial, sagittal, or coronal fat-suppressed T2-weighted (T2WI), T1-weighted (T1WI), and DWI images were acquired. Total MRI acquisition and set-up time was approximately 45 minutes. Metastatic disease on MRI was confirmed based on T2WI characteristics. The number of lesions was established on computed tomography (CT) or positron emission tomography (PET-CT). Whole-body ADC maps and T2WI were constructed, and region-of-interests were drawn in normal and abnormal-appearing tissue for quantitative analysis. Statistical analysis was performed using a paired t tests and P < .05 was considered statistically significant. RESULTS: There were 91 metastatic lesions detected from the CT or PET-CT with a missed recurrent lesion in the prostate. Multiparametric WB-MRI had excellent sensitivity (96%) for detection of metastatic lesions compared to CT. ADC map values and the ADC ratio in metastatic bone lesions were significantly increased (P < .05) compared to normal bone. In soft tissue, ADC map values and ratios in metastatic lesions were decreased compared to normal soft tissue. CONCLUSION: We have demonstrated that multiparametric WB-MRI is feasible for oncologic staging to identify bony and visceral metastasis in breast, prostate, pancreatic, and colorectal cancers. WB-MRI can be tailored to fit the patient, such that an "individualized patient sequence" can be developed for a comprehensive evaluation for staging and response during treatment.

Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings.

PURPOSE: To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). METHODS: Four patients were scanned using 13 b-values up to 3,000 s/mm2 and diffusion times ranging 18-52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots. RESULTS: ADC and IVIM did not fit the data well, failing to capture the signal at high b-values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly (p < 0.004) with the intracellular diffusion coefficient (r = 0.48), intracellular volume fraction (r = -0.21), and perfusion fraction (r = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter (r = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient (r = 0.18) and cell radius (r = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis. CONCLUSION: Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high b-values in the latter two models. The Kurtosis and VERDICT models captured information at high b using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases.

REnal Flow and Microstructure AnisotroPy (REFMAP) MRI in Normal and Peritumoral Renal Tissue.

BACKGROUND: Diffusion-weighted imaging (DWI) provides insight into the pathophysiology underlying renal dysfunction. Variants of DWI include intravoxel incoherent motion (IVIM), which differentiates between microstructural diffusion and vascular or tubular flow, and diffusion tensor imaging (DTI), which quantifies diffusion directionality. PURPOSE: To investigate the reproducibility of joint IVIM-DTI and compare controls to presurgical renal mass patients. STUDY TYPE: Prospective cross-sectional. SUBJECTS: Thirteen healthy controls and ten presurgical renal mass patients were scanned. Ten controls were scanned twice to investigate reproducibility. FIELD STRENGTH/SEQUENCE: Subjects were scanned on a 3T system using 10 b-values and 20 diffusion directions for IVIM-DTI in a study approved by the local Institutional Review Board. ASSESSMENT: Retrospective coregistration and measurement of joint IVIM-DTI parameters were performed. STATISTICAL ANALYSIS: Parameter reproducibility was defined as intraclass correlation coefficient (ICC) >0.7 and coefficient of variation (CV) <30%. Patient data were stratified by lesion side (contralateral/ipsilateral) for comparison with controls. Corticomedullary differentiation was evaluated. RESULTS: In controls, the reproducible subset of REnal Flow and Microstructure AnisotroPy (REFMAP) parameters had average ICC = 0.82 and CV = 7.5%. In renal mass patients, medullary fractional anisotropy (FA) was significantly lower than in controls (0.227 ± 0.072 vs. 0.291 ± 0.044, P = 0.016 for the kidney contralateral to the mass and 0.228 ± 0.070 vs. 0.291 ± 0.044, P = 0.018 for the kidney ipsilateral). In the kidney ipsilateral to the mass, cortical Dp,radial was significantly higher than in controls (P = 0.012). Conversely, medullary Dp,axial was significantly lower in contralateral than ipsilateral kidneys (P = 0.027) and normal controls (P = 0.044). DATA CONCLUSION: REFMAP-MRI parameters provide unique information regarding renal dysfunction. In presurgical renal mass patients, directional flow changes were noted that were not identified with IVIM analysis alone. Both contralateral and ipsilateral kidneys in patients show reductions in structural diffusivities and anisotropy, while flow metrics showed opposing changes in contralateral vs. ipsilateral kidneys. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Spatial Restriction within Intracranial Epidermoid Cysts Observed Using Short Diffusion-time Diffusion-weighted Imaging.

We report two cases of pathologically proven intracranial epidermoid cysts. Both cases were scanned with diffusion-weighted imaging using pulsed gradient spin-echo (PGSE) and oscillating gradient spin-echo (OGSE; 50 Hz) prototype sequences with diffusion times of 47.3 ms and 8.5 ms, respectively. The apparent diffusion coefficient measured by OGSE was higher than that measured by PGSE, indicating the spatial restriction of water diffusion in the laminated keratin layers within the cyst as demonstrated by histopathology.

Detection and monitoring of lung inflammation in cystic fibrosis during respiratory tract exacerbation using diffusion-weighted magnetic resonance imaging.

The aim was to investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects and monitors inflammatory and lung function changes during respiratory tract exacerbations (RTE) treatment in patients with cystic fibrosis (CF).29 patients with RTE underwent DWI pre- and post-antibiotic treatment. A control group of 27 stable patients, matched for age and sex, underwent DWI with the same time gap as those undergoing RTE treatment. Clinical status and lung function were assessed at each DWI time point. The CF-MRI scoring system was used to assess structural lung changes in both CF groups.Significant reduction in the DWI score over the course of antibiotic treatment (p<0.0001) was observed in patients with RTE, but not in the control group. DWI score had a strong inverse correlation with clinical status (r=-0.504, p<0.0001) and lung function (r=-0.635, p<0.0001) in patients with RTE. Interestingly, there were persistent significant differences in the CF-MRI score between the RTE and control group at both baseline and follow-up (p<0.001), while the differences in DWI score were only observed at baseline (p<0.001).DWI is a promising imaging method for noninvasive detection of pulmonary inflammation during RTE, and may be used to monitor treatment efficacy of anti-inflammatory treatment.

Stimulated echo diffusion tensor imaging (STEAM-DTI) with varying diffusion times as a probe of breast tissue.

PURPOSE: To explore the application of diffusion tensor imaging (DTI) for breast tissue and breast pathologies using a stimulated-echo acquisition mode (STEAM) with variable diffusion times. MATERIALS AND METHODS: In this Health Insurance Portability and Accountability Act-compliant study, approved by the local institutional review board, eight patients and six healthy volunteers underwent an MRI examination at 3 Tesla including STEAM-DTI with several diffusion times ranging from 68.5 to 902.5 ms. A DTI model was fitted to the data for each diffusion time, and parametric maps of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for healthy fibroglandular tissue (FGT) and lesions. The median value of radial diffusivity for FGT was fitted to a linear decay to obtain an estimation of the surface-to-volume ratio, from which the radial diameter was calculated. RESULTS: For healthy FGT, radial diffusivity presented a linear decay with the square root of the diffusion time resulting in a range of estimated radial diameters from 202 to 496 µm, while axial diffusivity presented a nearly time-independent diffusion. Residual fat signal was reduced at longer diffusion times due to the shorter T1 of fat. Residual fat signal to the overall signal in the healthy volunteers' FGT was found to range from 2.39% to 2.55% (shortest mixing time), and from 0.40% to 0.51% (longest mixing time) for the b500 images. CONCLUSION: The use of variable diffusion times may provide an in vivo noninvasive tool to probe diffusion lengths in breast tissue and breast pathology, and might aid by improving fat suppression at longer diffusion times. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:84-93.

Voxelwise analysis of simultaneously acquired and spatially correlated 18 F-fluorodeoxyglucose (FDG)-PET and intravoxel incoherent motion metrics in breast cancer.

PURPOSE: Diffusion-weighted imaging (DWI) and 18 F-fluorodeoxyglucose-positron emission tomography (18 F-FDG-PET) independently correlate with malignancy in breast cancer, but the relationship between their structural and metabolic metrics is not completely understood. This study spatially correlates diffusion, perfusion, and glucose avidity in breast cancer with simultaneous PET/MR imaging and compares correlations with clinical prognostics. METHODS: In this Health Insurance Portability and Accountability Act-compliant prospective study, with written informed consent and approval of the institutional review board and using simultaneously acquired FDG-PET and DWI, tissue diffusion (Dt ), and perfusion fraction (fp ) from intravoxel incoherent motion (IVIM) analysis were registered to FDG-PET within 14 locally advanced breast cancers. Lesions were analyzed using 2D histograms and correlation coefficients between Dt , fp , and standardized uptake value (SUV). Correlations were compared with prognostics from biopsy, metastatic burden from whole-body PET, and treatment history. RESULTS: SUV||Dt correlation coefficient significantly distinguished treated (0.11 ± 0.24) from nontreated (-0.33 ± 0.26) patients (P = 0.005). SUV||fp correlations were on average negative for the whole cohort (-0.17 ± 0.13). CONCLUSION: Simultaneously acquired and registered FDG-PET/DWI allowed quantifiable descriptions of breast cancer microenvironments that may provide a framework for monitoring and predicting response to treatment. Magn Reson Med 78:1147-1156, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

T2-adjusted computed diffusion-weighted imaging: A novel method to enhance tumour visualisation.

PURPOSE: To introduce T2-adjusted computed DWI (T2-cDWI), a method that provides synthetic images at arbitrary b-values and echo times (TEs) that improve tissue contrast by removing or increasing T2 contrast in diffusion-weighted images. MATERIALS AND METHODS: In addition to the standard DWI acquisition protocol T2-weighted echo-planar images at multiple (≥2) echo times were acquired. This allows voxelwise estimation of apparent diffusion coefficient (ADC) and T2 values, permitting synthetic images to be generated at any chosen b-value and echo time. An analytical model is derived for the noise properties in T2-cDWI, and validated using a diffusion test-object. Furthermore, we present T2-cDWI in two example clinical case studies: (i) a patient with mesothelioma demonstrating multiple disease tissue compartments and (ii) a patient with primary ovarian cancer demonstrating solid and cystic disease compartments. RESULTS: Measured image noise in T2-cDWI from phantom experiments conformed to the analytical model and demonstrated that T2-cDWI at high computed b-value/TE combinations achieves lower noise compared with conventional DWI. In patients, T2-cDWI with low b-value and long TE enhanced fluid signal while suppressing solid tumour components. Conversely, large b-values and short TEs overcome T2 shine-through effects and increase the contrast between tumour and fluid compared with conventional high-b-value DW images. CONCLUSION: T2-cDWI is a promising clinical tool for improving image signal-to-noise, image contrast, and tumour detection through suppression of T2 shine-through effects.