T2-weighted Turbo Spin-echo Images Research Articles

Impact of MRI radiomic feature normalization for prognostic modelling in uterine endometrial and cervical cancers

Widespread clinical use of MRI radiomic tumor profiling for prognostication and treatment planning in cancers faces major obstacles due to limitations in standardization of radiomic features. The purpose of the current work was to assess the impact of different MRI scanning- and normalization protocols for the statistical analyses of tumor radiomic data in two patient cohorts with uterine endometrial-(EC) (n = 136) and cervical (CC) (n = 132) cancer. 1.5 T and 3 T, T1-weighted MRI 2 min post-contrast injection, T2-weighted turbo spin echo imaging, and diffusion-weighted imaging were acquired. Radiomic features were extracted from within manually segmented tumors in 3D and normalized either using z-score normalization or a linear regression model (LRM) accounting for linear dependencies with MRI acquisition parameters. Patients were clustered into two groups based on radiomic profile. Impact of MRI scanning parameters on cluster composition and prognostication were analyzed using Kruskal–Wallis tests, Kaplan–Meier plots, log-rank test, random survival forests and LASSO Cox regression with time-dependent area under curve (tdAUC) (α = 0.05). A large proportion of the radiomic features was statistically associated with MRI scanning protocol in both cohorts (EC: 162/385 [42%]; CC: 180/292 [62%]). A substantial number of EC (49/136 [36%]) and CC (50/132 [38%]) patients changed cluster when clustering was performed after z-score-versus LRM normalization. Prognostic modeling based on cluster groups yielded similar outputs for the two normalization methods in the EC/CC cohorts (log-rank test; z-score: p = 0.02/0.33; LRM: p = 0.01/0.45). Mean tdAUC for prognostic modeling of disease-specific survival (DSS) by the radiomic features in EC/CC was similar for the two normalization methods (random survival forests; z-score: mean tdAUC = 0.77/0.78; LRM: mean tdAUC = 0.80/0.75; LASSO Cox; z-score: mean tdAUC = 0.64/0.76; LRM: mean tdAUC = 0.76/0.75). Severe biases in tumor radiomics data due to MRI scanning parameters exist. Z-score normalization does not eliminate these biases, whereas LRM normalization effectively does. Still, radiomic cluster groups after z-score- and LRM normalization were similarly associated with DSS in EC and CC patients.

Evaluating the Efficacy of Volume Isotropic Turbo Spin Echo Acquisition Versus T2-Weighted Turbo Spin Echo Imaging in the Diagnosis of Nerve Root and Perineuronal Pathologies in Spinal Disorders.

Background While two-dimensional (2D) turbo spin echo (TSE) sequences offer better through-plane resolution than three-dimensional (3D) isotropic TSE sequences images, with a narrower thickness of the slice, 3D isotropic TSE sequences are known to have a weaker in-plane resolution as well as blurring of the image. These elements may make it more difficult to distinguish between nearby structures that may affect nerve roots and small nerve roots during spinal imaging. This study aimedto analyze the accuracy of T2 TSE sequence and volumetric isotropic TSE acquisition in determining the indentation of nerve roots and perineural diseases such as nerve sheath tumors and Tarlov cysts. Methods Fifty patients who attended the Department of Radiodiagnosis for magnetic resonance (MR) spine participated in this prospective study. Routine MR lumbosacral (LS) spine sequences, such as survey, coronal T2short-tau inversion recovery (STIR), sagittal T2 TSE, sagittal T1 TSE, and axial T2 TSE, were carried out after a localizer was acquired. More sequences from volume isotropic turbo spin echo acquisition (VISTA) were acquired. For both 2D and 3D sequences, the visibility ratings for perineural cysts, spinal canal stenosis, and nerve root indentation were evaluated. Visibility ratings ranged from zero to four. Results In the cases of perineural cyst, spinal canal stenosis, and nerve root impingement, the mean difference between the VISTA and T2 TSE visibility scores was 0.04, 0.54, and 0.56, respectively. The VISTA and T2 TS had standard deviation differences of 0.006, 0.026, and 0.06, respectively. The "t" values for nerve root impingement, spinal canal stenosis, and perineural cysts were, in order, 50, 180, and 70. Because the p-value was <0.01, a statistically significant variation has been observed. Conclusion In the diagnosis of neural and perineuronal disorders, the visibility scores for 3D T2 TSE (VISTA) were considerably better than those for 2D T2 TSE in identifying perineural cysts, spinal canal stenosis, and nerve root indentation.

Evaluation of left atrial function and tissue after pulmonary vein isolation - initial results of The EVALUATE-PVI STUDY

Abstract Background Pulmonary vein (PV) isolation (PVI) by catheter ablation is a well-established treatment for atrial fibrillation (AF). Currently, the direct and long-term impact of ablation injury on left atrial (LA) function and tissue is poorly understood. Purpose The aim of this study is to evaluate the acute and long-term impact of radiofrequency (RF) PVI ablation on LA function and corresponding tissue changes as assessed with cardiac magnetic resonance imaging (CMR). Methods Seventeen patients (76.5% male, 60.8±9.7 years) with AF who underwent primo RF PVI as part of the EVALUATE-PVI STUDY underwent three sequential CMR scans prior to PVI, and &amp;lt;72 hours and 3 months after PVI ablation. T2-weighted turbo spin echo imaging was applied to assess post-ablation edema. High-resolution three-dimensional (3D) late gadolinium-enhancement (LGE) images were acquired to study acute LA wall injury and chronic fibrosis formation. LA volume and function were derived from two-chamber and four-chamber SSFP cine images. Maximum and minimal LA volume was indexed to body surface area to compute LAVimax and LAVimin. Longitudinal LA strain was calculated using feature tracking, and subdivided into reservoir, conduit, and contractile strain. Results Acutely post-PVI, T2w images showed increased signal intensity and thickening throughout the entire LA wall. LGE images showed diffuse increased signal intensity, without distinct focal high signal intensity areas (Fig. 1). Functional assessment at this stage showed significantly reduced LA emptying fraction (EF), LA reservoir, and contractile strain compared to pre-PVI (54.8±11.1% vs. 48.5±7.9%, p=0.01; 18.6±5.6% vs. 14.6±2.0%, p&amp;lt;0.01; 8.5±3.5% vs. 5.2±1.8%, p&amp;lt;0.001, respectively), while LA conduit strain, LAVimin, and LAVimax did not differ significantly (Fig. 2). The LGE images acquired at 3 months, displayed clear, focal, high signal intensity areas surrounding the PVs. At this stage post-PVI, a significant increase in LA strain was observed (LA reservoir strain 14.6±2.0% vs. 16.9±3.5%, p&amp;lt;0.01; and contractile strain 5.2±1.8% vs. 6.7±2.9%, p&amp;lt;0.01; respectively). LAVimax was significantly reduced at 3 months compared to acutely post-PVI (Fig. 2). LAVimin and LA conduit strain did not differ between the pre- and post-PVI stages. Conclusion PVI ablation resulted in temporary reduced LA function acutely post-PVI, likely due to edema and thickening of the LA wall. At three months, LGE images revealed clearly visible increased signal intensity in the ablated segments. At this stage, LA function improved, though full recovery did not occur as evidenced by the persistent slightly reduced contractile strain, possibly due to the ablation-induced loss of LA myocardium and formation of fibrosis. The decrease in LAVimax indicates reverse remodeling as a result of the ablation.

Investigating MRI-Associated Biological Aspects of Racial Disparities in Prostate Cancer for African American and White Men.

Understanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes. To investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men. Retrospective. One hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy. 3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence. The diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume. Weighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively. A total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P < 0.01). This study demonstrated race-related differences in the diagnostic performances and quantitative MRI measures of csPCa that were not reflected in age, PSA, and prostate volume. 3 TECHNICAL EFFICACY: Stage 2.

Evaluation of the performance of a 7-T 8 × 2 transceiver array.

The decoupled 8 × 2 transceiver array has been shown to achieve a mean B1 + of 11.7 uT with a coefficient of variation of ~11% over the intracranial brain volume for 7-T MR imaging. However, this array may be thought to give lower signal-to-noise ratio (SNR) and higher g-factors for parallel imaging compared with a radio frequency (RF) receive-only coil due to the latter's higher coil count and use of coil overlap to reduce the mutual impedance. Nonetheless, because the transceiver's highly decoupled design (pertinent for transmission) should also be constructive for reception, we measured the noise correlation, g-factors, and SNR for the decoupled transceiver in comparison with a commercial reference coil. We found that although the transceiver has half the number of receive elements in comparison with the reference coil (16 vs. 32), comparable g-factors and SNR over the head were obtained. From five subjects, the transceiver versus reference coil SNR was 65 ± 10 versus 67 ± 15. The mean noise correlation for all coil pairs was 10% ± 5% and 12% ± 9% (transceiver and reference coil, respectively). As changes in load impedance may alter the S parameters, we also examined the performance of the transceiver with tuned and matched (TM) versus untuned and unmatched (UTM) conditions on five subjects. We found that the noise correlation and SNR are robust to load variation; a noise correlation of 10% ± 5% and 10% ± 6% was determined with TM versus UTM conditions (SNRUTM/SNRTM = 0.97 ± 0.08). Finally, we demonstrate the performance of the array in human brain using T2-weighted turbo spin echo imaging, finding excellent SNR performance in both caudal and rostral brain regions.

Deep learning-accelerated T2-weighted imaging versus conventional T2-weighted imaging in the female pelvic cavity: image quality and diagnostic performance.

The deep learning (DL)-based reconstruction algorithm reduces noise in magnetic resonance imaging (MRI), thereby enabling faster MRI acquisition. To compare the image quality and diagnostic performance of conventional turbo spin-echo (TSE) T2-weighted (T2W) imaging with DL-accelerated sagittal T2W imaging in the female pelvic cavity. This study evaluated 149 consecutive female pelvic MRI examinations, including conventional T2W imaging with TSE (acquisition time = 2:59) and DL-accelerated T2W imaging with breath hold (DL-BH) (1:05 [0:14 × 3 breath-holds]) in the sagittal plane. In 294 randomly ordered sagittal T2W images, two radiologists independently assessed image quality (sharpness, subjective noise, artifacts, and overall image quality), made a diagnosis for uterine leiomyomas, and scored diagnostic confidence. For the uterus and piriformis muscle, quantitative imaging analysis was also performed. Wilcoxon signed rank tests were used to compare the two sets of T2W images. In the qualitative analysis, DL-BH showed similar or significantly higher scores for all features than conventional T2W imaging (P <0.05). In the quantitative analysis, the noise in the uterus was lower in DL-BH, but the noise in the muscle was lower in conventional T2W imaging. In the uterus and muscle, the signal-to-noise ratio was significantly lower in DL-BH than in conventional T2W imaging (P <0.001). The diagnostic performance of the two sets of T2W images was not different for uterine leiomyoma. DL-accelerated sagittal T2W imaging obtained with three breath-holds demonstrated superior or comparable image quality to conventional T2W imaging with no significant difference in diagnostic performance for uterine leiomyomas.

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.

Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer.

The aim of this study was to investigate the potential of multiparametric 18F-FDG PET/MR imaging as a platform for radiomics analysis and machine learning algorithms based on primary cervical cancers to predict N- and M-stage in patients. A total of 30 patients with histopathological confirmation of primary and untreated cervical cancer were prospectively enrolled for a multiparametric 18F-FDG PET/MR examination, comprising a dedicated protocol for imaging of the female pelvis. The primary tumor in the uterine cervix was manually segmented on post-contrast T1-weighted images. Quantitative features were extracted from the segmented tumors using the Radiomic Image Processing Toolbox for the R software environment for statistical computing and graphics. 45 different image features were calculated from non-enhanced as well as post-contrast T1-weighted TSE images, T2-weighted TSE images, the ADC map, the parametric Ktrans, Kep, Ve and iAUC maps and PET images, respectively. Statistical analysis and modeling was performed using Python 3.5 and the scikit-learn software machine learning library for the Python programming language. Prediction of M-stage was superior when compared to N-stage. Prediction of M-stage using SVM with SVM-RFE as feature selection obtained the highest performance providing sensitivity of 91 % and specificity of 92 %. Using receiver operating characteristic (ROC) analysis of the pooled predictions, the area under the curve (AUC) was 0.97. Prediction of N-stage using RBF-SVM with MIFS as feature selection reached sensitivity of 83 %, specificity of 67 % and an AUC of 0.82. M- and N-stage can be predicted based on isolated radiomics analyses of the primary tumor in cervical cancers, thus serving as a template for noninvasive tumor phenotyping and patient stratification using high-dimensional feature vectors extracted from multiparametric PET/MRI data. · Radiomics analysis based on multiparametric PET/MRI enables prediction of the metastatic status of cervical cancers. · Prediction of M-stage is superior to N-stage. · Multiparametric PET/MRI displays a valuable platform forradiomics analyses .

Two-center validation of Pilot Tone based cardiac triggering of a comprehensive cardiovascular magnetic resonance examination.

The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. To evaluate the performance of PTC triggering in a comprehensive CMR exam. Fifteen volunteers and 20 patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.

The Characteristics of Extracranial Internal Carotid Artery and Their Relationship With Surgical Outcomes in Patients With Moyamoya Disease: A Combined Head-and-Neck Vessel Wall MR Imaging Study.

The features of intracranial arteries in patients with Moyamoya disease (MMD) have been widely investigated. However, the MR characteristics of extracranial internal carotid artery (EICA) and their effect on outcomes of revascularization treatment are not fully understood. To investigate the characteristics of EICA and their relationship with outcomes of revascularization treatment in adult patients with MMD based on higher-resolution MRI (HRMRI). Prospective interventional outcomes. Two hundred eighty-eight consecutive patients with MMD (mean age: 43.7 ± 11.2 years; 140 male). Turbo inversion recovery magnitude T1-weighted imaging and turbo spin echo (TSE) T2-weighted imaging, three-dimensional time-of-flight MR angiography, T2-fluid attenuated inversion recovery, and 3D T1-SPACE vessel wall imaging at 3.0 T. The HRMRI characteristics of EICA were determined. The relationship between the characteristics of EICA (proximal stenosis, diffuse wall thickening, carotid plaques, and luminal thrombosis) and stroke outcomes of revascularization treatment in patients with MMD was analyzed. The discriminative ability of EICA characteristics in combination with intracranial carotid artery features (involvement of vessel segments, bilateral involvement, and Suzuki stage) to determine stroke outcomes was compared with that of intracranial artery features alone during a mean 8.0 months follow-up period. Cox proportional hazards models and Kaplan-Meier curves to calculate the hazard ratios (HRs) for stroke with 95% confidence intervals (CIs). Area under the receiver operating characteristic curve (AUC) for assessing discriminative performance. A P value <0.05 was considered statistically significant. During a mean 8.0 ± 2.2 months follow-up, of the 288 participants, 137 had proximal stenosis (47.6%), 106 had diffuse wall thickening (36.8%), 60 had carotid plaques (20.8%), and 27 had luminal thrombosis (9.4%) of EICA. Of these features, proximal stenosis (HR = 2.86; 95% CI = 1.13-7.29) and diffuse wall thickening (HR = 2.62; 95% CI = 1.16-5.94) of EICA were significantly associated with stroke after surgery, before and after adjusting for confounding factors. In discriminating the stroke outcomes after surgery, combining characteristics of EICA with features of intracranial arteries resulted in a significant incremental improvement (DeLong test, P < 0.05) in the AUC over that obtained with features of intracranial arteries alone (AUC: 0.73 vs. 0.60-0.64). Proximal stenosis and diffuse wall thickening of EICA were significantly associated with stroke outcomes after surgery in patients with MMD. Our findings suggest that understanding the characteristics of EICA has added value for intracranial vessels in predicting future events after surgery in patients with MMD. 2 TECHNICAL EFFICACY: Stage 4.

Comparison of standard T2-weighted turbo spin echo and volumetric interpolated breath-hold examination magnetic resonance imaging sequences in the assessment of articular process dysplasia in Pug dogs with thoracolumbar myelopathy.

A retrospective study to compare the classification, as normal, hypoplastic or aplastic, of thoracic (T10-T13) caudal articular process (CAP) morphology in Pug dogs with a thoracolumbar myelopathy as normal, hypoplastic or aplastic, between T2 weighted Turbo Spin Echo (T2W-TSE), in sagittal and transverse planes, and Volumetric Interpolated Breath-hold Examination (VIBE) Magnetic Resonance Imaging (MRI) sequences, in comparison to Computed Tomography (CT). We hypothesized a stronger agreement for VIBE in comparison to T2W-TSE. Diagnostic accuracy of T2W-TSE was inferior to VIBE for aplastic (60%, 95% CI 0.561-0.639 vs. 78%, 95%CI 0.744-0.815) hypoplastic (44%, 95%CI 0.427-0.452 vs. 62.5%, 95%CI 0.595-0.655) and normal CAP (70%, 95%CI 0.655-0.744 vs. 87%, 95%CI 0.848-0.892). Superior accuracy of classification using VIBE vs. T2W-TSE sequences using the McNemar Chi squared test was significant for aplastic (p = 0.0002) and normal CAP (p = 0.004). VIBE sequences had a sensitivity of 96% and specificity of 75% to detect CAP abnormality and with T2W-TSE imaging sensitivity 81% and specificity of 75%. Three-dimensionally reconstructable VIBE sequences were significantly more accurate than traditional T2W-TSE MRI sequences in classifying CAP morphology, which should reduce the need for CT for pre-operative assessment.

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.

Utility of accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction in female pelvic MRI: a multi-reader study.

To determine the clinical feasibility of T2-weighted turbo spin-echo (T2-TSE) imaging with deep learning reconstruction (DLR) in female pelvic MRI compared with conventional T2 TSE in terms of image quality and scan time. Between May 2021 and September 2021, 52 women (mean age, 44years ± 12) who underwent 3-T pelvic MRI with additional T2-TSE using a DLR algorithm were included in this single-center prospective study with patient's informed consents. Conventional, DLR, and DLR T2-TSE images with reduced scan times were independently assessed and compared by four radiologists. The overall image quality, differentiation of anatomic details, lesion conspicuity, and artifacts were evaluated using a 5-point scale. Inter-observer agreement of the qualitative scores was compared and reader protocol preferences were then evaluated. In the qualitative analysis of all readers, fast DLR T2-TSE showed significantly better overall image quality, differentiation of anatomic regions, lesion conspicuity, and lesser artifacts than conventional T2-TSE and DLR T2-TSE, despite approximately 50% reduction in scan time (all p < 0.05). The inter-reader agreement for the qualitative analysis was moderate to good. All readers preferred DLR over conventional T2-TSE regardless of scan time and preferred fast DLR T2-TSE (57.7-78.8%), except for one who preferred DLR over fast DLR T2-TSE (53.8% vs. 46.1%). In female pelvic MRI, image quality and accelerated image acquisition for T2-TSE can be significantly improved by using DLR compared to conventional T2-TSE. Fast DLR T2-TSE was non-inferior to DLR T2-TSE in terms of reader preference and image quality. DLR of T2-TSE in female pelvic MRI enables fast imaging along with maintaining optimal image quality compared with parallel imaging-based conventional T2-TSE. • Conventional T2 turbo spin-echo based on parallel imaging has limitations for accelerated image acquisition while maintaining good image quality. • Deep learning image reconstruction showed better image quality in both images obtained using the same or accelerated image acquisition parameters compared with conventional T2 turbo spin-echo in female pelvic MRI. • Deep learning image reconstruction enables accelerated image acquisition while maintaining good image quality in the T2-TSE of female pelvic MRI.

Optimizing imaging resolution in brain MRI: understanding the impact of technical factors.

Magnetic resonance imaging (MRI) exams are essential for diagnostic procedures, but their lengthy duration and associated costs limit their accessibility. Shorter scan times would reduce expenses and allow for more MRI exams, expanding the range of diagnostic procedures. This study investigated technical factors that could decrease scan time without compromising image quality, including field-of-view (FOV), phase field of view, phase oversampling, cross-talk, brain MRI imaging resolution, and scan time. Data were collected from September 2021 to June 2022. All patients underwent brain scans in the transverse plane following a standardized protocol using a 1.5-tesla Siemens Avanto MRI scanner. The protocol employed T2-weighted Turbo Spin Echo imaging. Twenty-four cases were included in this study. Initially, all participants underwent brain MRI scans using the original protocols with axial sections. The results indicated that altering the FOV phase and phase oversampling significantly affected the scan time, whereas other factors did not have a direct impact. The original protocol had a scan time of 3.47 minutes with a FOV of 230 mm, 90% FOV phase, and 0% phase oversampling. After implementing the modified protocol, the scan time was reduced to 2.18 minutes with a FOV of 217 mm and 93.98% phase oversampling of 13.96%. Statistical analysis confirmed the high significance of FOV phase and phase oversampling in reducing scan time. By optimizing these technical factors, MRI exams can be performed more efficiently, resulting in shorter scan times and potentially reducing costs. This would enhance patient comfort and enable a greater number of MRI exams, facilitating a more comprehensive range of diagnostic procedures.

Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS. To explore whether DLR from MRI can be used to identify pregnancies with PAS. Retrospective. 324 pregnant women (mean age, 33.3 years) suspected PAS (170 training and 72 validation from institution 1, 82 external validation from institution 2) with clinicopathologically proved PAS (206 PAS, 118 non-PAS). 3-T, turbo spin-echo T2-weighted images. The DLR features were extracted using the MedicalNet. An MRI-based DLR model incorporating DLR signature, clinical model (different clinical characteristics between PAS and non-PAS groups), and MRI morphologic model (radiologists' binary assessment for the PAS diagnosis) was developed. These models were constructed in the training dataset and then validated in the validation datasets. The Student t-test or Mann-Whitney U, χ2 or Fisher exact test, Kappa, dice similarity coefficient, intraclass correlation coefficients, least absolute shrinkage and selection operator logistic regression, multivariate logistic regression, receiver operating characteristic (ROC) curve, DeLong test, net reclassification improvement (NRI) and integrated discrimination improvement (IDI), calibration curve with Hosmer-Lemeshow test, decision curve analysis (DCA). P < 0.05 indicated a significant difference. The MRI-based DLR model had a higher area under the curve than the clinical model in three datasets (0.880 vs. 0.741, 0.861 vs. 0.772, 0.852 vs. 0.675, respectively) or MRI morphologic model in training and independent validation datasets (0.880 vs. 0.760, 0.861, vs. 0.781, respectively). The NRI and IDI were 0.123 and 0.104, respectively. The Hosmer-Lemeshow test had nonsignificant statistics (P = 0.296 to 0.590). The DCA offered a net benefit at any threshold probability. An MRI-based DLR model may show better performance in diagnosing PAS than a clinical or MRI morphologic model. 3 TECHNICAL EFFICACY STAGE: 2.

Quantification of Endometrial Fibrosis Using Noninvasive MRI T2 Mapping: Initial Findings.

Endometrial fibrosis may cause infertility. Accurate evaluation of endometrial fibrosis helps clinicians to schedule timely therapy. To explore T2 mapping for assessing endometrial fibrosis. Prospective. Ninety-seven women with severe endometrial fibrosis (SEF) and 21 patients with mild to moderate endometrial fibrosis (MMEF), diagnosed by hysteroscopy, and 37 healthy women. 3T, T2-weighted turbo spin echo (T2-weighted imaging) and multi-echo turbo spin echo (T2 mapping) sequences. Endometrial MRI parameters (T2, thickness [ET], area [EA], and volume [EV]) were measured by N.Z. and Q.H. (9- and 4-years' experience in pelvic MRI) and compared between the three subgroups. A multivariable model including MRI parameters and clinical variables (including age and body mass index [BMI]) was developed to predict endometrial fibrosis assessed by hysteroscopy. Kruskal-Wallis; ANOVA; Spearman's correlation coefficient (rho); area under the receiver operating characteristic curve (AUC); binary logistic regression; intraclass correlation coefficient (ICC). P value <0.05 for statistical significance. Endometrial T2, ET, EA, and EV of MMEF patients (185 msec, 8.2 mm, 168 mm2 , and 2181 mm3 ) and SEF patients (164 msec, 6.7 mm, 120 mm2 , and 1762 mm3 ) were significantly lower than those of healthy women (222 msec, 11.7 mm, 316 mm2 , and 3960 mm3 ). Endometrial T2 and ET of SEF patients were significantly lower than those of MMEF patients. Endometrial T2, ET, EA, and EV were significantly correlated to the degree of endometrial fibrosis (rho = -0.623, -0.695, -0.694, -0.595). There were significant strong correlations between ET, EA, and EV in healthy women and MMEF patients (rho = 0.850-0.908). Endometrial MRI parameters and the multivariable model accurately distinguished MMEF or SEF from normal endometrium (AUCs >0.800). Age, BMI, and MRI parameters in univariable analysis and age and T2 in multivariable analysis significantly predicted endometrial fibrosis. The reproducibility of MRI parameters was excellent (ICC, 0.859-0.980). T2 mapping has potential to noninvasively and quantitatively evaluate the degree of endometrial fibrosis. 2 Technical Efficacy: Stage 2.

Diagnostic performance of multiparametric magnetic resonance imaging in the differentiation of clear cell renal cell cancer.

This study aimed to evaluate the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI) in the differentiation of renal cell carcinoma (RCC) subtypes. This is a retrospective diagnostic performance study, in which the diagnostic performances of mpMRI features were evaluated to differentiate clear cell RCC (ccRCC) from non-clear cell RCC (non-ccRCC). Adult patients who were evaluated using a 3-Tesla dynamic contrast-enhanced mpMRI before undergoing partial or radical nephrectomy for possible malignant renal tumors were included in the study. Signal intensity change percentages (SICP) between contrast-enhanced phases and pre-administration period for both the tumor and normal renal cortex, and tumor-to-cortex enhancement index (TCEI); tumor apparent diffusion coefficient (ADC) values; tumor-to-cortex ADC ratio; and a scale which was developed according to the tumor signal intensities on the axial fat-suppressed T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) images were used in ROC analysis to estimate the presence of ccRCC in the patients. The reference test positivity was the histopathologic examination of the surgical specimens. Ninety-eight tumors from 91 patients were included in the study, and 59 of them were ccRCC, 29 were pRCC, and 10 were chRCC. The mpMRI features that had the three highest sensitivity rates were excretory phase SICP, T2-weighted HASTE scale score, and corticomedullary phase TCEI (93.2%, 91.5%, and 86.4%, respectively). However, those with the three highest specificity rates were nephrographic phase TCEI, excretory phase TCEI, and tumor ADC value (94.9%, 94.9%, and 89.7%, respectively). Several parameters on mpMRI showed an acceptable performance to differentiate ccRCC from non-ccRCC.

Diagnostic performance of magnetic resonance imaging in preoperative local staging of rectal cancer after neoadjuvant chemoradiotherapy

This paper aims to investigate the diagnostic performance of magnetic resonance imaging (MRI) in predicting the pathologic stage of locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (CRT) and the role of MRI in selecting patients with a pathologic complete response (ypCR). Restaging MRI (yMRI) examinations of 136 patients with LARC treated with neoadjuvant CRT followed by surgery were retrospectively analyzed by two radiologists. All examinations were performed on a 1.5 Tesla MRI machine with a pelvic phased-array coil. T2-weighted turbo spin-echo images and diffusion-weighted imaging were obtained. Histopathologic reports of the surgical specimens were the reference standard. The accuracy, sensitivity, specificity, positive and negative predictive values (PPV and NPV) of yMRI in predicting the pathologic T-stage (ypT), N-stage, and ypCR were calculated. The inter-observer agreement was evaluated using kappa statistics. The yMRI results showed 67% accuracy, 59% sensitivity, 80% specificity, 81% PPV, and 56% NPV in identifying ypT (ypT0-2 versus ypT3-4). In predicting the nodal status, the yMRI results revealed 63% accuracy, 60% sensitivity, 65% specificity, 47% PPV, and 75% NPV. In predicting ypCR, the yMRI results showed 84% accuracy, 20% sensitivity, 92% specificity, 23% PPV, and 90% NPV. The kappa statistics revealed substantial agreement between the two radiologists. Utilization of yMRI showed high specificity and PPV in predicting the tumor stage and high NPV in predicting the nodal stage; in addition, yMRI revealed moderate accuracy in the T and N classifications, mainly due to underestimating the tumor stage and overestimating the nodal status. Finally, yMRI revealed high specificity and NPV but low sensitivity in predicting the complete response.

Effectiveness and Accuracy of MRI-Ultrasound Fusion Targeted Biopsy Based on PI-RADS v2.1 Category in Transition/Peripheral Zone of the Prostate.

MRI-ultrasound fusion targeted biopsy (MRI-TBx) improves the clinically significant prostate cancer (csPCa) detection with fewer cores. However, whether systematic biopsy-guided by transrectal ultrasound (TRUS-SBx) can be omitted when undergoing MRI-TBx in transition zone (TZ) and peripheral zone (PZ) remains unclear. To assess the performance and effectiveness of MRI-TBx based on PI-RADS v2.1 for csPCa diagnosis in TZ and PZ, respectively. Retrospective. A total of 309 selected cases (median age 70 years) with 356 lesions who underwent both MRI-TBx and TRUS-SBx were enrolled. A 3.0 T, multiparametric MRI (mp-MRI) including T2-weighted turbo-spin echo imaging (T2WI), diffusion-weighted spin-echo echo planar imaging (DWI), dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging (DCE). Mp-MRI was assessed by two radiologists using PI-RADS v2.1. The csPCa detection rates provided by MRI-TBx, TRUS-SBx and combined biopsy in TZ and PZ were calculated, respectively. McNemar test was used to compare the csPCa detection rates in TZ and PZ, respectively. The frequencies and distribution of all detected prostate cancers by different biopsy methods were also compared. P < 0.05 was considered statistically significant. Among 356 lesions in 309 patients, 208 (68 in TZ, 140 in PZ) were pathologically confirmed as csPCa. In TZ, there were significant differences for csPCa detection with PI-RADS 3 between combined biopsy and TRUS-SBx (23.5% vs. 15.3%), MRI-TBx (23.5% vs. 16.3%), respectively. MRI-TBx detected 23% (19/83) cases missed by TRUS-SBx in which 68% (13/19) were csPCa. In PZ, there were no statistical differences between MRI-TBx and combined biopsy with PI-RADS 3-5 (P=0.21, 0.25, 0.07, respectively). In 9% (14/152) cases only detected by MRI-TBx, 86% (12/14) were clinically significant. Five percent (7/152) of cases only detected by TRUS-SBx were completely nonclinically significant. MRI-TBx played a positive role on csPCa diagnosis in TZ, but combined biopsy might be the best choice especially in the subgroup PI-RADS 3. In PZ, MRI-TBx had an advantage over TRUS-SBx for csPCa detection. 2. Stage 2.

Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG. This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images. Retrospective and prospective. For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males). 5T and 3T, T2-weighted turbo spin echo imaging. Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve. Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann-Whitney U test. A two-sided P value <0.05 was considered statistically significant. In the testing cohort, Dice coefficients of tumor segmentation using DL were 0.87 for diffuse midline brain and 0.81 for spinal cord gliomas. In the internal prospective testing dataset, the predictive accuracies, sensitivities, and specificities of H3 K27M mutation status were 92.1%, 98.2%, 82.9% in diffuse midline brain gliomas and 85.4%, 88.9%, 82.6% in spinal cord gliomas. Furthermore, this study showed that the performance generalizes to external institutions, with predictive accuracies of 85.7%-90.5%, sensitivities of 90.9%-96.0%, and specificities of 82.4%-83.3%. In this study, an automatic DL framework was developed and validated for accurately predicting H3 K27M mutation using T2-weighted images, which could contribute to the noninvasive determination of H3 K27M status for clinical decision-making. 2 Technical Efficacy: Stage 2.