Single-shot Echo-planar Diffusion-weighted Imaging Research Articles

Comparison of Diffusion-weighted MRI using Singe-Shot Echo-planar Imaging (SS-EPI) and Split Acquisition of Fast Spin Echo Signal (SPLICE) Imaging, a non-EPI technique, in Tumors of the Head and Neck.

Diffusion-weighted imaging (DWI) using single-shot echo planar imaging (DW-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, Split acquisition of fast spin echo signals for diffusion imaging (DWSPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DW-EPI through quantitative and qualitative analyses. The DW-SPLICE sequence was incorporated into the standard 3.0T head and neck MRI protocol with DW-EPI. Retrospective analysis was conducted on two subgroups: firstly benign or malignant lesions, and secondly post-treatment SCC recurrence. In both subgroups Image quality and distortion were scored by two independent radiologists, blinded for DW-technique, and evaluated using mixed-effect linear models. Lesion apparent diffusion coefficient (ADC) values were assessed with inter-class correlation (ICC) and Bland-Altman analyses. DWI's delineation geometric similarity to T1-weighted post-contrast (T1Wc) MRI was evaluated using the Dice Similarity Coefficient (DSC) before and after registration. Recurrence in post-treatment SCC scans was evaluated by the same two radiologists blinded for DW-technique. Recurrence detection rates were then compared between DW-SPLICE and DW-EPI using mixed logistic regression at six months and at one-year post-scan follow-up data. From August 2020 to January 2022, 55 benign or malignant lesion scans (55 patients) and 74 post-treatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DW-EPI (0.04<p<0.001). There was high ADC measurement reliability (ICC=0.93, p<0.001), though a proportional bias was also observed (β=0.11, p=0.03), indicating the bias increases as ADC values rise. DWSPLICE exhibited greater geometric similarity to T1Wc before registration (DSC 0.63 vs 0.47, p<0.001) and outperformed DW-EPI by more accurately identifying recurrences after one year (OR=0.96, p=0.05) but not after six months (OR=0.72, p=0.13). DW-SPLICE surpasses DW-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the HN. Consistent use of one method for follow-up is advised, as ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice. ANTs = Advanced Normalization Tools; DSC = Dice Similarity Coefficient; DW-EPI = Diffusion-weighted single-shot echo planar imaging; DW-MS-EPI = Diffusion-weighted multi-shot echo planar imaging; DW-SPLICE = Diffusion-weighted split acquisition of fast spin echo signals for diffusion imaging; DW-TSE = Diffusion-weighted Turbo Spin Echo; ICC = Intraclass Correlation Coefficient; ROC = Receiver Operating Characteristic; SCC = Squamous cell carcinoma; T1WIc = T1 weighted imaging with gadolinium contrast.

Prospective Comparison of FOCUS MUSE and Single-Shot Echo-Planar Imaging for Diffusion-Weighted Imaging in Evaluating Thyroid-Associated Ophthalmopathy.

To prospectively compare single-shot (SS) echo-planar imaging (EPI) and field-of-view optimized and constrained undistorted single-shot multiplexed sensitivity-encoding (FOCUS MUSE) for diffusion-weighted imaging (DWI) in evaluating thyroid-associated ophthalmopathy (TAO). SS EPI and FOCUS MUSE DWIs were obtained from 39 patients with TAO (18 male; mean ± standard deviation: 48.3 ± 13.3 years) and 26 healthy controls (9 male; mean ± standard deviation: 43.0 ± 18.5 years). Two radiologists scored the visual image quality using a 4-point Likert scale. The image quality score, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) of extraocular muscles (EOMs) were compared between the two DWIs. Differences in the ADC of EOMs were also evaluated. The performance of discriminating active from inactive TAO was assessed using receiver operating characteristic curves. The correlation between ADC and clinical activity score (CAS) was analyzed using Spearman correlation. Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated significantly higher image quality scores (P < 0.001), a higher SNR and CNR on the lateral rectus muscle (LRM) and medial rectus muscle (MRM) (P < 0.05), and a non-significant difference in the ADC of the LRM and MRM. Active TAO showed higher ADC than inactive TAO and healthy controls with both SS EPI and FOCUS MUSE DWIs (P < 0.001). Inactive TAO and healthy controls did not show a significant ADC difference with both DWIs. Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated better discrimination of active from inactive TAO (AUC: 0.925 vs. 0.779; P = 0.007). The ADC was significantly correlated with CAS in SS EPI DWI (r = 0.391, P < 0.001) and FOCUS MUSE DWI (r = 0.645, P < 0.001). FOCUS MUSE DWI provides better images for evaluating EOMs and better performance in diagnosing active TAO than SS EPI DWI. The application of FOCUS MUSE will facilitate the DWI evaluation of TAO.

Optimization of motion-corrected liver diffusion-weighted imaging at 3 Tesla (3T): incorporating complex averaging and reparametrized sinc fatsat pulse with optimized water excitation pulse.

In liver diffusion-weighted imaging (DWI), single-shot echo-planar imaging (SS-EPI) sequences are susceptible to motion artifacts, resulting in image blurring and decreased lesion detection rates. This study aimed to develop and optimize a motion-corrected (MOCO) technique for liver DWI at 3 Tesla (3T). The technique incorporates motion correction, complex averaging, and a combination of a reparametrized sinc fatsat pulse with an optimized water excitation pulse. This prospective cross-sectional study performed at Fujian Medical University Union Hospital included 42 healthy volunteers who underwent four SS-EPI DWI sequences on a 3T magnetic resonance imaging (MRI) system between January 2023 and March 2023. The sequences included a navigator-triggered (NT) MOCO-DWI, two free-breathing (FB) MOCO-DWI, and an FB conventional DWI (FB cDWI) sequence. Motion correction and complex averaging were performed for both MOCO-DWI sequences, and fat suppression was achieved using either a sinc fatsat pulse with optimized water excitation or a conventional spectral attenuated inversion recovery (SPAIR) pulse. Liver signal-to-noise ratio (SNR) was measured at b=1,000 s/mm2. Qualitative parameters were independently evaluated by three radiologists using 5-point Likert scales. Quantitative parameters were assessed using the Kolmogorov-Smirnov test, and variance homogeneity was assessed using Levene's test. Regarding the qualitative analysis, the Friedman test was used to compare subjective scores among the four techniques. The SNRs of the liver were significantly higher with FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). In the superior-inferior direction, the SNRs of the inferior level of the liver were higher than those of the superior level in NT MOCO-DWI. The qualitative results showed significantly higher ratings for NT MOCO-DWI and FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). Regarding the apparent diffusion coefficient (ADC) quantification, the ADC values of the left lobe were higher than those of the right lobe in all four techniques. The proposed EPI DWI technique, incorporating motion correction, complex averaging, and a modified fat suppression scheme using spectral fat saturation and binomial water excitation, was found to be clinically feasible for liver MRI. The FB MOCO-DWI sequence, with its superior SNR and excellent image quality, is recommended for liver DW imaging at 3T in clinical routine.

Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer.

Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive bladder carcinoma (NMIBC). However, the European Organization for Research and Treatment of Cancer (EORTC) model exhibits poor performance. To investigate whether integrating multiparametric MRI (mp-MRI) with clinical factors improves NMIBC 5-year recurrence risk assessment. Retrospective. One hundred ninety-one patients (median age, 65 years; age range, 54-73 years; 27 females) underwent mp-MRI between 2011 and 2017, and received ≥5-year follow-ups. They were divided into a training cohort (N = 115) and validation/testing cohorts (N = 38 in each). Recurrence rates were 23.5% (27/115) in the training cohort and 23.7% (9/38) in both validation and testing cohorts. 3-T, fast spin echo T2-weighted imaging (T2WI), single-shot echo planar diffusion-weighted imaging (DWI), and volumetric spoiled gradient echo dynamic contrast-enhanced (DCE) sequences. Radiomics and deep learning (DL) features were extracted from the combined region of interest (cROI) including intratumoral and peritumoral areas on mp-MRI. Four models were developed, including clinical, cROI-based radiomics, DL, and clinical-radiomics-DL (CRDL) models. Student's t-tests, DeLong's tests with Bonferroni correction, receiver operating characteristics with the area under the curves (AUCs), Cox proportional hazard analyses, Kaplan-Meier plots, SHapley Additive ExPlanations (SHAP) values, and Akaike information criterion for clinical usefulness. A P-value <0.05 was considered statistically significant. The cROI-based CRDL model showed superior performance (AUC 0.909; 95% CI: 0.792-0.985) compared to other models in the testing cohort for assessing 5-year recurrence in NMIBC. It achieved the highest Harrell's concordance index (0.804; 95% CI: 0.749-0.859) for estimating recurrence-free survival. SHAP analysis further highlighted the substantial role (22%) of the radiomics features in NMIBC recurrence assessment. Integrating cROI-based radiomics and DL features from preoperative mp-MRI with clinical factors could improve 5-year recurrence risk assessment in NMIBC. 3 TECHNICAL EFFICACY: Stage 3.

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver.

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

Effect of Phase Encoding Direction on Image Quality in Single-Shot EPI Diffusion-Weighted Imaging of the Breast.

In breast diffusion-weighted imaging (DWI), distortion and physiologic artifacts affect clinical interpretation. Image quality can be optimized by addressing the effect of phase encoding (PE) direction on these artifacts. To compare distortion artifacts in breast DWI acquired with different PE directions and polarities, and to discuss their clinical implications. Prospective. Eleven healthy volunteers (median age: 47 years old; range: 22-74 years old) and a breast phantom. Single-shot echo planar DWI and three-dimensional fast gradient echo sequences at 3 T. All DWI data were acquired with left-right, right-left, posterior-anterior, and anterior-posterior PE directions. In phantom data, displacement magnitude was evaluated by comparing the location of landmarks in anatomical and DWI images. Three breast radiologists (5, 17, and 23 years of experience) assessed the presence or absence of physiologic artifacts in volunteers' DWI datasets and indicated their PE-direction preference. Analysis of variance with post-hoc tests were used to assess differences in displacement magnitude across DWI datasets and observers. A binomial test and a chi-squared test were used to evaluateif each in vivo DWI dataset had an equal probability (25%) of being preferred by radiologists. Inter-reader agreement was evaluated using Gwet's AC1 agreement coefficient. A P-value <0.05 was considered statistically significant. In the phantom study, median displacement was the significantly largest in posterior-anterior data. While the displacement in the anterior-posterior and left-right data were equivalent (P = 0.545). In the in vivo data, there were no physiological artifacts observed in any dataset, regardless of PE direction. In the reader study, there was a significant preference for the posterior-anterior datasets which were selected 94% of the time. There was good agreement between readers (0.936). This study showed the impact of PE direction on distortion artifacts in breast DWI. In healthy volunteers, the posterior-to-anterior PE direction was preferred by readers. 2 TECHNICAL EFFICACY: Stage 1.

Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvements in clinically significant prostate cancer (csPCa) risk assessments are required. To develop and validate machine learning (ML) models based on clinical and imaging parameters for csPCa detection in patients with PI-RADS v2.1 ≥ 3. Retrospective. One thousand eighty-three patients with PI-RADS v2.1 ≥ 3, randomly split into training (70%, N = 759) and validation (30%, N = 324) datasets, and 147 patients enrolled prospectively for testing. 3.0 T scanners/T2-weighted fast spin echo sequence and DWI with diffusion-weighted single-shot gradient echo planar imaging sequence. The factors evaluated for csPCa detection were age, prostate specific antigen, prostate volume, and the diameter and location of the index lesion, PI-RADSv2.1. Five ML models for csPCa detection were developed: logistic regression (LR), extreme gradient boosting, random forest (RF), decision tree, and support vector machines. The csPCa was defined as Gleason grade ≥2. Univariable and multivariable LR analyses to identify parameters associated with csPCa. Area under the receiver operating characteristic curve (AUC), Brier score, and DeLong test were used to assess and compare the csPCa diagnostic performance with the LR model. The significance level was defined as 0.05. The RF model exhibited the highest AUC (0.880-0.904) and lowest Brier score (0.125-0.133) among the ML models in the validation and testing cohorts, however, there was no difference when compared to the LR model (P = 0.453 and 0.548). The sensitivity and negative predictive values in the validation and testing cohorts were 93.8%-97.6% and 82.7%-95.1%, respectively, at a threshold of 0.450 (99% sensitivity of the RF model). The RF model might help for assessing the risk of csPCa and preventing overdiagnosis and unnecessary biopsy for men with PI-RADSv2.1 ≥ 3. 3 TECHNICAL EFFICACY: Stage 2.

Understanding ADC variation by fat content effect using a dual-function MRI phantom

BackgroundA dual-function phantom designed to quantify the apparent diffusion coefficient (ADC) in different fat contents (FCs) and glass bead densities (GBDs) to simulate the human tissues has not been documented yet. We propose a dual-function phantom to quantify the FC and to measure the ADC at different FCs and different GBDs.MethodsA fat-containing diffusion phantom comprised by 30 glass-bead-containing fat-water emulsions consisting of six different FCs (0, 10, 20, 30, 40, and 50%) multiplied by five different GBDs (0, 0.1, 0.25, 0.5, and 1.0 g/50 mL). The FC and ADC were measured by the “iterative decomposition of water and fat with echo asymmetry and least squares estimation-IQ,” IDEAL-IQ, and single-shot echo-planar diffusion-weighted imaging, SS-EP-DWI, sequences, respectively. Linear regression analysis was used to evaluate the relationship among the fat fraction (FF) measured by IDEAL-IQ, GBD, and ADC.ResultsThe ADC was significantly, negatively, and linearly associated with the FF (the linear slope ranged from -0.005 to -0.017, R2 = 0.925 to 0.986, all p < 0.001). The slope of the linear relationship between the ADC and the FF, however, varied among different GBDs (the higher the GBD, the lower the slope). ADCs among emulsions across different GBDs and FFs were overlapped. Emulsions with low GBDs plus high FFs shared a same lower ADC range with those with median or high GBDs plus median or lower FFs.ConclusionsA novel dual-function phantom simulating the human tissues allowed to quantify the influence of FC and GBD on ADC.Relevance statementThe study developed an innovative dual-function MRI phantom to explore the impact of FC on ADC variation that can affect clinical results. The results revealed the superimposed effect on FF and GBD density on ADC measurements.Key points• A dual-function phantom made of glass bead density (GBD) and fat fraction (FF) emulsion has been developed.• Apparent diffusion coefficient (ADC) values are determined by GBD and FF.• The dual-function phantom showed the mutual ADC addition between FF and GBD.Graphical

Utility of Prostate Health Index Density for Biopsy Strategy in Biopsy-Naïve Patients With PI-RADS v2.1 Category 3 Lesions.

Category 3 lesions in PI-RADSv2.1 pose diagnostic challenges, complicating biopsy decisions. Recent biomarkers like prostate health index (PHI) have shown higher specificity in detecting clinically significant prostate cancer (csPCa) than prostate-specific antigen (PSA). Yet their integration with MRI remains understudied. To evaluate the utility of PSA and PHI with its derivatives for detecting csPCa in biopsy-naïve patients with category 3 lesion on initial prostate MRI scan. Retrospective. One hundred ninety-three biopsy-naïve patients who underwent MRI, PSA, and PHI testing, followed by both targeted and systematic biopsies. Turbo spin-echo T2-weighted imaging, diffusion-weighted single-shot echo-planar imaging, and dynamic contrast-enhanced T1-weighted fast field echo sequence imaging in 3 T. PHI density (PHID) and PSA density (PSAD) derived by dividing serum PHI and PSA with prostate volume (MRI based methodology suggested by PI-RADSv2.1). Risk-stratified models to evaluate the utility of markers in triaging patients for biopsy, including low-, intermediate-, and high-risk groups. Independent t-test, Mann-Whitney U test, Mantel-Haenszel test, generalized estimating equation, and receiver operating characteristic (ROC) curve analysis were used. Statistical significance defined as P < 0.05. CsPCa was found in 16.6% (32/193) of patients. PHID had the highest area under the ROC curve (AUROC) of 0.793, followed by PHI of 0.752, PSAD of 0.750, and PSA of 0.654. PHID with two cut-off points (0.88/mL and 1.82/mL) showed the highest potential biopsy avoidance of 47.7% (92/193) with 5% missing csPCa, and the lowest intermediate-risk group (borderline decision group) at 38.9% (75/193), compared to PSA and PHI. PHID demonstrated better potential in triaging patients with category 3 lesions, possibly aiding more selective and confident biopsy decisions for csPCa detection, than traditional markers. 4 TECHNICAL EFFICACY: Stage 5.

The Value of Amide Proton Transfer MRI in the Diagnosis of Malignant and Benign Urinary Bladder Lesions: Comparison With Diffusion-Weighted Imaging.

Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB. To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI. Prospective. Eighty patients with UB lesions. A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging. Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTRasym). MTRasym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions. Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05. Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTRasym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10-3 mm2/s vs. 1.43 ± 0.22 × 10-3 mm2/s) than benign UB lesions. The MTRasym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722). APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI. 3 TECHNICAL EFFICACY: Stage 2.

Diffusion-weighted Echo Planar Imaging with Compressed SENSE (EPICS-DWI) for Pancreas Assessment: A Multicenter Study.

This study aimed to evaluate the feasibility of single-shot echo planar diffusion-weighted imaging with compressed SENSE (EPICS-DWI) for pancreas assessment by comparing with single-shot echo planar DWI with parallel imaging (PI-DWI). This multicenter prospective study included 27 consecutive participants with untreated pancreatic ductal adenocarcinoma (PDAC) (15 men; mean age, 67 ± 10 years) who underwent pancreatic protocol MRI including both PI-DWI and EPICS-DWI. Two radiologists independently and randomly reviewed the high b-value DWI images and qualitatively assigned confidence scores for overall image quality, image noise, pancreas conspicuity, and PDAC conspicuity using a 5-point scale. One radiologist measured the PDAC-to-pancreas contrast-to-noise-ratio (CNR) on high b-value DWI images and the apparent diffusion coefficient (ADC) value of PDAC. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon signed-rank test. The confidence scores for overall image quality (P < 0.001 in both radiologists) and image noise (P < 0.001 in both radiologists) were higher in EPICS-DWI than in PI-DWI. The pancreas conspicuity was better in EPICS-DWI than in PI-DWI in one of the radiologists (P = 0.02 and 0.06). The PDAC conspicuity was comparable between PI-DWI and EPICS-DWI (P > 0.99 in both radiologists). The PDAC-to-pancreas CNR was higher in EPICS-DWI than in PI-DWI (P = 0.02), while the ADC value of PDAC in PI-DWI was not significantly different compared to that in EPICS-DWI (P = 0.48). The image quality and PDAC-to-pancreas CNR was improved in EPICS-DWI compared to PI-DWI. However, the conspicuity and ADC value of PDAC were comparable between PI-DWI and EPICS-DWI.

Exploring Radial Asymmetry in MR Diffusion Tensor Imaging and Its Impact on the Interpretation of Glymphatic Mechanisms.

Diffusion imaging holds great potential for the non-invasive assessment of the glymphatic system in humans. One technique, diffusion tensor imaging along the perivascular space (DTI-ALPS), has introduced the ALPS-index, a novel metric for evaluating diffusivity within the perivascular space. However, it still needs to be established whether the observed reduction in the ALPS-index reflects axonal changes, a common occurrence in neurodegenerative diseases. To determine whether axonal alterations can influence change in the ALPS-index. Retrospective. 100 participants (78 cognitively normal and 22 with mild cognitive impairments) aged 50-90 years old. 3T; diffusion-weighted single-shot spin-echo echo-planar imaging sequence, T1-weighted images (MP-RAGE). The ratio of two radial diffusivities of the diffusion tensor (i.e., λ2/λ3) across major white matter tracts with distinct venous/perivenous anatomy that fulfill (ALPS-tracts) and do not fulfill (control tracts) ALPS-index anatomical assumptions were analyzed. To investigate the correlation between λ2/λ3 and age/cognitive function (RAVLT) while accounting for the effect of age, linear regression was implemented to remove the age effect from each variable. Pearson correlation analysis was conducted on the residuals obtained from the linear regression. Statistical significance was set at p < 0.05. λ2 was ~50% higher than λ3 and demonstrated a consistent pattern across both ALPS and control tracts. Additionally, in both ALPS and control tracts a reduction in the λ2/λ3 ratio was observed with advancing age (r = -0.39, r = -0.29, association and forceps tract, respectively) and decreased memory function (r = 0.24, r = 0.27, association and forceps tract, respectively). The results unveil a widespread radial asymmetry of white matter tracts that changes with aging and neurodegeration. These findings highlight that the ALPS-index may not solely reflect changes in the diffusivity of the perivascular space but may also incorporate axonal contributions. 3 TECHNICAL EFFICACY: Stage 2.

Deep learning-based k-space-to-image reconstruction and super resolution for diffusion-weighted imaging in whole-spine MRI

PurposeTo assess the feasibility of deep learning (DL)-based k-space-to-image reconstruction and super resolution for whole-spine diffusion-weighted imaging (DWI). MethodThis retrospective study included 97 consecutive patients with hematologic and/or oncologic diseases who underwent DL-processed whole-spine MRI from July 2022 to March 2023. For each patient, conventional (CONV) axial single-shot echo-planar DWI (b = 50, 800 s/mm2) was performed, followed by DL reconstruction and super resolution processing. The presence of malignant lesions and qualitative (overall image quality and diagnostic confidence) and quantitative (nonuniformity [NU], lesion contrast, signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], and ADC values) parameters were assessed for DL and CONV DWI. ResultsUltimately, 67 patients (mean age, 63.0 years; 35 females) were analyzed. The proportions of vertebrae with malignant lesions for both protocols were not significantly different (P: [0.55–0.99]). The overall image quality and diagnostic confidence scores were higher for DL DWI (all P ≤ 0.002) than CONV DWI. The NU, lesion contrast, SNR, and CNR of each vertebral segment (P ≤ 0.04) but not the NU of the sacral segment (P = 0.51) showed significant differences between protocols. For DL DWI, the NU was lower, and lesion contrast, SNR, and CNR were higher than those of CONV DWI (median values of all segments; 19.8 vs. 22.2, 5.4 vs. 4.3, 7.3 vs. 5.5, and 0.8 vs. 0.7). Mean ADC values of the lesions did not significantly differ between the protocols (P: [0.16–0.89]). ConclusionsDL reconstruction can improve the image quality of whole-spine diffusion imaging.

Highly accelerated multi-shot intravoxel incoherent motion diffusion-weighted imaging in brain enabled by parametric POCS-based multiplexed sensitivity encoding.

Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm2 . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.

Magnetic Resonance Imaging-Based Classification Systems for Informing Better Outcomes of Adenomyosis After Ultrasound-Guided High-Intensity Focused Ultrasound Ablating Surgery.

A referenced MRI-based classification associated with focused ultrasound ablation surgery (FUAS) outcomes is lacking in adenomyosis. To identify an MRI-based classification system for informing the FUAS outcomes. Retrospective. Patients with FUAS for adenomyosis, were divided into a training set (N = 643; 355 with post-FUAS gonadotropin-releasing hormone/levonorgestrel, 288 without post-FUAS therapy) and an external validation set (N = 135; all without post-FUAS therapy). 1.5 T, turbo spin-echo T2-weighted imaging and single-shot echo-planar diffusion-weighted imaging sequences. Five MRI-based adenomyosis classifications: classification 1 (C1) (diffuse, focal, and mild), C2 (intrinsic, extrinsic, intramural, and indeterminate), C3 (internal, adenomyomas, and external), C4 (six subtypes on areas [internal or external] and volumes [<1/3 or ≥2/3]), and C5 (internal [asymmetric or symmetric], external, intramural, full thickness [asymmetric or symmetric]) for FUAS outcomes (symptom relief and recurrence). The optimal classification was significantly associated with the most subtypes of FUAS outcomes. Relating to the timing of recurrence was measured using Cox regression analysis and median recurrence time was estimated by a Kaplan-Meier curve. A P value <0.05 was considered statistically significant. Dysmenorrhea relief and recurrence were only associated with C2 in training patients undergoing FUAS alone. Compared with other subtypes, the extrinsic subtype of C2 was significantly associated with dysmenorrhea recurrence in the FUAS group. Besides, the median dysmenorrhea recurrence time of extrinsic subtype was significantly shorter than that of other subtypes (42.0 months vs. 50.3 months). In the validation cohort, C2 was confirmed as the optimal system and its extrinsic subtype was confirmed to have a significantly shorter dysmenorrhea recurrence time than other subtypes. Classification 2 can inform dysmenorrhea relief and recurrence in patients with adenomyosis undergoing FAUS only. Itsextrinsic subtype was associated with an earlier onset of dysmenorrhea recurrence after treatment. 3 TECHNICAL EFFICACY: Stage 5.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging and Venous Tumor Thrombus Consistency in Renal Cell Carcinoma.

Venous tumor thrombus (VTT) consistency of renal cell carcinoma (RCC) is an important consideration in nephrectomy plus thrombectomy. However, evaluation of VTT consistency through preoperative MR imaging is lacking. To evaluate VTT consistency of RCC through intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI) derived parameters (Dt , Dp , f, and ADC) and the apparent diffusion coefficient (ADC) value. Retrospective. One hundred and nineteen patients (aged 55.8 ± 11.5 years, 85 male) with histologically-proven RCC and VTT who underwent radical resection. 3.0-T; two-dimensional single-shot diffusion-weighted echo planar imaging sequence at 9 b-values (0-800 s/mm2 ). IVIM parameters and ADC values of the primary tumor and the VTT were calculated. The VTT consistency (friable vs. solid) was determined through intraoperative findings of two urologists. The accuracy of VTT consistency classification based on the individual IVIM parameters of primary tumors and of VTT, and based on models combining parameters, was assessed. Type of operation, intra-operative blood loss, and operation length were recorded. Shapiro-Wilk test; Mann-Whitney U test; Student's t-test; Chi-square test; Receiver operating characteristic (ROC) analysis. Statistical significance level was P < 0.05. Of the enrolled 119 patients, 33 patients (27.7%) had friable VTT. Patients with friable VTT were significantly more likely to experience open surgery, have significantly more intraoperative blood loss, and significantly longer operative duration. The area under the ROC curve (AUC) values of Dt of the primary tumor and VTT in classifying VTT consistency were 0.758 (95% CI 0.671-0.832) and 0.712 (95% CI 0.622-0.792), respectively. The AUC value of the model combining Dp and Dt of VTT was 0.800 (95% CI 0.717-0.868). Furthermore, the AUC of the model combining Dp and Dt of VTT and Dt of the primary tumor was 0.886 (95% CI 0.814-0.937). IVIM-derived parameters had the potential to predict VTT consistency of RCC. 3 Technical Efficacy: Stage 2.

Clinical utility of single-shot echo-planar diffusion-weighted imaging using L1-regularized iterative sensitivity encoding in prostate MRI.

We investigated the ability of echo-planar imaging with L1-regularized iterative sensitivity encoding-based diffusion-weighted imaging (DWI) to improve the image quality and reduce the scanning time in prostate magnetic resonance imaging. We retrospectively analyzed 109 cases of prostate magnetic resonance imaging. We compared variables in the quantitative and qualitative assessments among 3 imaging groups: conventional parallel imaging-based DWI (PI-DWI) with an acquisition time of 3 minutes 15 seconds; echo-planar imaging with L1-regularized iterative sensitivity encoding-based DWI (L1-DWI) with a normal acquisition time (L1-DWINEX12) of 3 minutes 15 seconds; and L1-DWI with a half acquisition time (L1-DWINEX6) of 1 minute 45 seconds. As a quantitative assessment, the signal-to-noise ratio (SNR) of DWI (SNR-DWI), the contrast-to-noise ratio (CNR) of DWI (CNR-DWI), and the CNR of apparent diffusion coefficient were measured. As a qualitative assessment, the image quality and visual detectability of prostate carcinoma were evaluated. In the quantitative analysis, L1-DWINEX12 showed significantly higher SNR-DWI than PI-DWI (P = .0058) and L1-DWINEX6 (P < .0001). In the qualitative analysis, the image quality score for L1-DWINEX12 was significantly higher than those of PI-DWI and L1-DWINEX6. A non-inferiority assessment demonstrated that L1-DWINEX6 was non-inferior to PI-DWI in terms of both quantitative CNR-DWI and qualitative grading of image quality with a <20% inferior margin. L1-DWI successfully demonstrated a reduced scanning time while maintaining good image quality.

RESOLVE-based radiomics in cervical cancer: improved image quality means better feature reproducibility?

To compare the reproducibility of apparent diffusion coefficient (ADC)-based radiomic features between readout-segmented echo-planar diffusion-weighted imaging (RESOLVE) and single-shot echo-planar diffusion-weighted imaging (SS-EPI DWI) in cervical cancer. The RESOLVE and SS-EPI DWI images of 36 patients with histopathologically confirmed cervical cancer were collected retrospectively. Two observers independently delineated the whole tumour on RESOLVE and SS-EPI DWI, and then copied them to the corresponding ADC maps. Shape, first-order, and texture features were extracted from ADC maps in the original and filtered (Laplacian of Gaussian [LoG] and wavelet) images. Thereafter, 1,316 features were generated in each RESOLVE and SS-EPI DWI, respectively. The reproducibility of radiomic features was assessed using intraclass correlation coefficient (ICC). In the original images, RESOLVE showed 92.86%, 66.67%, and 86.67% of features with excellent reproducibility in shape, first-order, and texture features, while SS-EPI DWI showed 85.71%, 72.22%, and 60% of features with excellent reproducibility, respectively. In the LoG and wavelet filtered images, RESOLVE had 56.77% and 65.32% of features with excellent reproducibility and SS-EPI DWI had 44.95% and 61.96% of features with excellent reproducibility, respectively. Compared with SS-EPI DWI, the feature reproducibility of RESOLVE was better in cervical cancer, especially for texture features. The filtered images cannot improve the feature reproducibility compared with the original images for both SS-EPI DWI and RESOLVE.

Breast Cancer Growth on Serial MRI: Volume Doubling Time Based on 3-Dimensional Tumor Volume Assessment.

The volume doubling time (VDT) of breast cancer was most frequently calculated using the two-dimensional (2D) diameter, which is not reliable for irregular tumors. It was rarely investigated using three-dimensional (3D) imaging with tumor volume on serial magnetic resonance imaging (MRI). To investigate the VDT of breast cancer using 3D tumor volume assessment on serial breast MRIs. Retrospective. Sixty women (age at diagnosis: 57 ± 10 years) with breast cancer, assessed by two or more breast MRI examinations. The median interval time was 791 days (range: 70-3654 days). 3-T, fast spin-echo T2-weighted imaging (T2WI), single-shot echo-planar diffusion-weighted imaging (DWI), and gradient echo dynamic contrast-enhanced imaging. Three radiologists independently reviewed the morphological, DWI, and T2WI features of lesions. The whole tumor was segmented to measure the volume on contrast-enhanced images. The exponential growth model was fitted in the 11 patients with at least three MRI examinations. The VDT of breast cancer was calculated using the modified Schwartz equation. Mann-Whitney U test, Kruskal-Wallis test, Chi-squared test, intraclass correlation coefficients, and Fleiss kappa coefficients. A P-value <0.05 was considered statistically significant. The exponential growth model was evaluated using the adjusted R2 and root mean square error (RMSE). The median tumor diameter was 9.7 mm and 15.2 mm on the initial and final MRI, respectively. The median adjusted R2 and RMSE of the 11 exponential models were 0.97 and 15.8, respectively. The median VDT was 540 days (range: 68-2424 days). For invasive ductal carcinoma (N=33), the median VDT of the non-luminal type was shorter than that of the luminal type (178 days vs. 478 days). On initial MRI, breast cancer manifesting as a focus or mass lesion showed a shorter VDT than that of a non-mass enhancement (NME) lesion (median VDT: 426 days vs. 665 days). A shorter VDT was observed in breast cancer manifesting as focus or mass as compared to an NME lesion. 3 TECHNICAL EFFICACY: Stage 2.

Deep-Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi-Parametric MRI.

Deep learning for diagnosing clinically significant prostate cancer (csPCa) is feasible but needs further evaluation in patients with prostate-specific antigen (PSA) levels of 4-10 ng/mL. To explore diffusion-weighted imaging (DWI), alone and in combination with T2-weighted imaging (T2WI), for deep-learning-based models to detect and localize visible csPCa. Retrospective. One thousand six hundred twenty-eight patients with systematic and cognitive-targeted biopsy-confirmation (1007 csPCa, 621 non-csPCa) were divided into model development (N=1428) and hold-out test (N=200) datasets. DWI with diffusion-weighted single-shot gradient echo planar imaging sequence and T2WI with T2-weighted fast spin echo sequence at 3.0-T and 1.5-T. The ground truth of csPCa was annotated by two radiologists in consensus. A diffusion model, DWI and apparent diffusion coefficient (ADC) as input, and a biparametric model (DWI, ADC, and T2WI as input) were trained based on U-Net. Three radiologists provided the PI-RADS (version 2.1) assessment. The performances were determined at the lesion, location, and the patient level. The performance was evaluated using the areas under the ROC curves (AUCs), sensitivity, specificity, and accuracy. A P value <0.05 was considered statistically significant. The lesion-level sensitivities of the diffusion model, the biparametric model, and the PI-RADS assessment were 89.0%, 85.3%, and 90.8% (P=0.289-0.754). At the patient level, the diffusion model had significantly higher sensitivity than the biparametric model (96.0% vs. 90.0%), while there was no significant difference in specificity (77.0%. vs. 85.0%, P=0.096). For location analysis, there were no significant differences in AUCs between the models (sextant-level, 0.895 vs. 0.893, P=0.777; zone-level, 0.931 vs. 0.917, P=0.282), and both models had significantly higher AUCs than the PI-RADS assessment (sextant-level, 0.734; zone-level, 0.863). The diffusion model achieved the best performance in detecting and localizing csPCa in patients with PSA levels of 4-10 ng/mL. 3 TECHNICAL EFFICACY: Stage 2.