T1-weighted Gradient-echo Sequence Research Articles

MRI Investigation of Kidneys, Ureters and Urinary Bladder in Rabbits.

Twelve clinically healthy and sexually mature New Zealand White rabbits were studied. The non-contrast imaging included T1-weighted and T2-weighted spin-echo and gradient-echo sequences in the transverse, sagittal and dorsal planes. Transverse MRI (T2-weighted image) through L1 demonstrated only the right kidney. The transverse T2-weighted image through L2 showed both kidneys. The cranial part of the urinary bladder on T1-weighted transverse scans through L4 was flexed to the left. The T2-weighted sagittal image 30 mm to the right of the median plane showed the right kidney, the right ureter and the urinary bladder. The T2-weighted sagittal image 30 mm to the left of the median plane showed part of the left kidney, the left ureter and the urinary bladder. The T2-weighted sagittal image 45 mm to the left of the median plane presented the lateral part of the left kidney. The dorsal MRI image (T2-weighted sequence) through the horizontal plane 30 mm ventral to the spine demonstrated the whole organs. These data will be useful in imaging anatomy and diagnostic studies of various pathologies of the excretory system in rabbits and other mammalian species.

MRI Tomoelastography to Assess the Combined Status of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma.

Integrating vessels encapsulating tumor clusters (VETC) and microvascular invasion (MVI) (VM hereafter) is potentially useful in risk stratification of hepatocellular carcinoma (HCC). However, noninvasive assessment methods for VM are lacking. To investigate the diagnostic performance of tomoelastography in assessing the VM status in HCC. Retrospective. One hundred sixty-eight patients with surgically confirmed HCC consisting of 115 training and 53 validation cohorts, divided into negative-VM and positive-VM groups with mild or severe-VMs. Of them, 127 patients completed the follow-up (median: 26.1 months). 3D multifrequency tomoelastography with a single-shot spin-echo echo-planar imaging sequence, and liver MRI including T1-weighted in-phase and opposed-phase gradient echo (GRE), T2-weighted turbo spin echo, diffusion-weighted imaging and dynamic contrast-enhanced T1-weighted GRE sequences at 3.0 T. Shear wave speed (c) and phase angle of the shear modulus (φ) were calculated on tomoelastograms. Imaging features were visually analyzed and clinical features were collected. Conventional models used clinical and imaging features while nomograms combined tomoelastography, clinical and imaging features. Univariable and multivariable logistic regression analyses, nomogram, area under the receiver operating characteristic curve (AUC), DeLong test, Kaplan-Meier analysis and log-rank test. P < 0.05 was considered statistically significant. Tumor-to-liver parenchyma ratio of c (cr) and tumor c were independent risk factors for positive-VM and severe-VM, respectively. In validation cohort, the nomograms including cr and tumor c performed significantly better than the conventional models for diagnosing positive-VM (0.84 [95% CI: 0.72-0.93] vs. 0.77 [95% CI: 0.64-0.88]) and severe-VM (0.86 [95% CI: 0.68-0.96] vs. 0.75 [95% CI: 0.55-0.89]). Patients with estimated positive-VM (9.3 months)/severe-VM (9.2 months) based on nomograms had shorter median recurrence-free survival than those with estimated negative-VM (>20.0 months)/mild-VM (18.0 months) in validation cohort. Tomoelastography based-nomograms showed good performance for noninvasively assessing VM status in patients with HCC. 3 TECHNICAL EFFICACY: Stage 2.

Effect of metallic materials on magnetic resonance image uniformity: a quantitative experimental study.

To assess quantitatively the effect of metallic materials on MR image uniformity using a standardized method. Six types of 1cm cubic metallic materials (i.e., Au, Ag, Al, Au-Ag-Pd alloy, Ti, and Co-Cr alloy) embedded in a glass phantom filled were examined and compared with no metal condition inserted as a reference. The phantom was scanned five times under each condition using a 1.5-T MR superconducting magnet scanner with an 8-channel phased-array brain coil and head and neck coil. For each examination, the phantom was scanned in three planes: axial, coronal, and sagittal using T1-weighted spin echo (SE) and gradient echo (GRE) sequences in accordance with the American Society for Testing and Materials (ASTM) F2119-07 standard. Image uniformity was assessed using the non-uniformity index (NUI), which was developed by the National Electrical Manufacturers Association (NEMA), as an appropriate standardized measure for investigating magnetic field uniformity. T1-GRE images with Co-Cr typically elicited the lowest uniformity, followed by T1-GRE images with Ti, while all other metallic materials did not affect image uniformity. In particular, T1-GRE images with Co-Cr showed significantly higher NUI values as far as 6.6cm at maximum equivalent to 11 slices centering around it in comparison with the measurement uncertainty from images without metallic materials. We found that MR image uniformity was influenced by the scanning sequence and coil type when Co-Cr and Ti were present. It is assumed that the image non-uniformity in Co-Cr and Ti is caused by their high magnetic susceptibility.

MRI susceptibility artefacts caused by orthodontic wire.

To evaluate magnetic susceptibility artefacts produced by orthodontic wires on MRI and the influence of wire properties and MRI image sequences on the magnitude of the artefact. Arch form orthodontic wires [four stainless steels (SS), one cobalt chromium (CC) alloy, 13 titanium (Ti) alloys] were embedded in a polyester phantom, and scanned using a 1.5-T superconducting magnet scanner with an eight-channel phased-array coil. All wires were scanned with T1-weighted spin echo (SE) and gradient echo (GRE) sequences according to the American Society for Testing and Materials (ASTM) F2119-07 standard. The phantom also scanned other eight sequences. Artefacts were measured using the ASTM F2119-07 definition and OsiriX software. Artefact volume was analysed according to metal composition, wire length, number of wires, wire thickness, and imaging sequence as factors. With SE/GRE, black/white artefacts volumes from all SS wires were significantly larger than those produced by CC and Ti wires (P < .01). With the GRE, the black artefacts volume was the highest with the SS wires. With the SE, the black artefacts volume was small, whereas white artefacts were noticeable. The cranio-caudal extent of the artefacts was significantly longer with SS wires (P < .01). Although a direct relationship of wire length, number of wires, and wire thickness with artefact volume was noted, these factors did not influence artefact extension in the cranio-caudal direction. Ferromagnetic/paramagnetic orthodontic wires create artefacts due to local alteration of magnetic field homogeneity. The SS-type wires produced the largest artefacts followed by CC and Ti.

Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study.

Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized selection of therapeutic approaches. To develop and validate a machine learning (ML) model based on clinicopathological and MRI characteristics for assessing pALN burden and survival in patients with cT1-T2 stage breast cancer. Retrospective. A total of 506 females (range: 24-83 years) with cT1-T2 stage breast cancer from two institutions, forming the training (N = 340), internal validation (N = 85), and external validation cohorts (N = 81), respectively. This study used 1.5-T, axial fat-suppressed T2-weighted turbo spin-echo sequence and axial three-dimensional dynamic contrast-enhanced fat-suppressed T1-weighted gradient echo sequence. Four ML methods (eXtreme Gradient Boosting [XGBoost], Support Vector Machine, k-Nearest Neighbor, Classification and Regression Tree) were employed to develop models based on clinicopathological and MRI characteristics. The performance of these models was evaluated by their discriminative ability. The best-performing model was further analyzed to establish interpretability and used to calculate the pALN score. The relationships between the pALN score and disease-free survival (DFS) were examined. Chi-squared test, Fisher's exact test, univariable logistic regression, area under the curve (AUC), Delong test, net reclassification improvement, integrated discrimination improvement, Hosmer-Lemeshow test, log-rank, Cox regression analyses, and intraclass correlation coefficient were performed. A P-value <0.05 was considered statistically significant. The XGB II model, developed based on the XGBoost algorithm, outperformed the other models with AUCs of 0.805, 0.803, and 0.818 in the three cohorts. The Shapley additive explanation plot indicated that the top variable in the XGB II model was the Node Reporting and Data System score. In multivariable Cox regression analysis, the pALN score was significantly associated with DFS (hazard ratio: 4.013, 95% confidence interval: 1.059-15.207). The XGB II model may allow to evaluate pALN burden and could provide prognostic information in cT1-T2 stage breast cancer patients. 3 TECHNICAL EFFICACY: Stage 2.

Dynamic contrast enhanced MRI of the head and neck region using a VIBE sequence with Cartesian undersampling and compressed sensing

ObjectivesCompressed sensing allows for image reconstruction from sparsely sampled k-space data, which is particularly useful in dynamic contrast enhanced MRI (DCE-MRI). The aim of the study was to assess the diagnostic value of a volume-interpolated 3D T1-weighted spoiled gradient-echo sequence with variable density Cartesian undersampling and compressed sensing (CS) for head and neck MRI. MethodsSeventy-one patients with clinical indications for head and neck MRI were included in this study. DCE-MRI was performed at 3 Tesla magnet using CS-VIBE (variable density undersampling, temporal resolution 3.4 s, slice thickness 1 mm). Image quality was compared to standard Cartesian VIBE. Three experienced readers independently evaluated image quality and lesion conspicuity on a 5-point Likert scale and determined the DCE-derived time intensity curve (TIC) types. ResultsCS-VIBE demonstrated higher image quality scores compared to standard VIBE with respect to overall image quality (4.3 ± 0.6 vs. 4.2 ± 0.7, p = 0.682), vessel contour (4.6 ± 0.4 vs. 4.4 ± 0.6, p < 0.001), muscle contour (4.4 ± 0.5 vs. 4.5 ± 0.6, p = 0.302), lesion conspicuity (4.5 ± 0.7 vs. 4.3 ± 0.9, p = 0.024) and showed improved fat saturation (4.8 ± 0.3 vs. 3.8 ± 0.4, p < 0.001) and movement artifacts were significantly reduced (4.6 ± 0.6 vs. 3.7 ± 0.7, p < 0.001). Standard VIBE outperformed CS-VIBE in the delineation of pharyngeal mucosa (4.2 ± 0.5 vs. 4.6 ± 0.6, p < 0.001). Lesion size in cases where a focal lesion was identified was similar for all readers for CS-VIBE and standard VIBE (p = 0.101). TIC curve assessment showed good interobserver agreement (k=0.717). ConclusionCS-VIBE with variable density Cartesian undersampling allows for DCE-MRI of the head and neck region with diagnostic, high image quality and high temporal resolution.

Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry.

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer's disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < -0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.

Linac- and CyberKnife-based MRI-only treatment planning of prostate SBRT using an optimized synthetic CT calibration curve.

CT Hounsfield Units (HUs) are converted to electron density using a calibration curve obtained from physical measurements of an electron density phantom. HU values assigned to an MRI-derived synthetic computed tomography (sCT) may present a different relationship with electron density compared to CT HU. Correct assignment of sCT HU values is critical for accurate dose calculation and delivery. The goals of this work were to develop a sCT calibration curve using patient data acquired on a clinically commissioned CT scanner and assess for CyberKnife- and volumetric modulated arc therapy (VMAT)-based MR-only treatment planning of prostate SBRT. Same-day CT and MRI simulation in the treatment position were performed on 10 patients treated with SBRT to the prostate. Dixon in-phase and out-of-phase MRIs were acquired on a 3T scanner using a 3D T1-weighted gradient-echo sequence to generate sCTs using a commercial sCT algorithm. CT and sCT datasets were co-registered and HU values compared using mean absolute error (MAE). An optimized HU-to-density calibration curve was created based on average HU values across an institutional patient database for each of the four sCT tissue types. Clinical CyberKnife and VMAT treatment plans were generated on each patient CT and recomputed onto corresponding sCTs. Dose distributions computed using CT and sCT were compared using gamma criteria and dose-volume-histograms. For the optimized calibration curve, HU values were -96, 37, 204, and 1170 and relative electron densities were 0.95, 1.04, 1.1, and 1.7 for adipose, soft tissue, inner bone, and outer bone, respectively. The proposed sCT protocol produced total MAE of 94±20HU. Gamma values mean±std (min-max) were 98.9%±0.9% (97.1%-100%) and 97.7%±1.3% (95.3%-99.3%) for VMAT and CyberKnife plans, respectively. MRI-derived sCT using the proposed approach shows excellent dosimetric agreement with conventional CT simulation, demonstrating the feasibility of MRI-derived sCT for prostate SBRT treatment planning.

Artificial Intelligence Quantification of Enhanced Synovium Throughout the Entire Hand in Rheumatoid Arthritis on Dynamic Contrast-Enhanced MRI.

Challenges persist in achieving automatic and efficient inflammation quantification using dynamic contrast-enhanced (DCE) MRI in rheumatoid arthritis (RA) patients. To investigate an automatic artificial intelligence (AI) approach and an optimized dynamic MRI protocol for quantifying disease activity in RA in whole hands while excluding arterial pixels. Retrospective. Twelve RA patients underwent DCE-MRI with 27 phases for creating the AI model and tested on images with a variable number of phases from 35 RA patients. 3.0 T/DCE T1-weighted gradient echo sequence (mDixon, water image). The model was trained with various DCE-MRI time-intensity number of phases. Evaluations were conducted for similarity between AI segmentation and manual outlining in 51 ROIs with synovitis. The relationship between synovial volume via AI segmentation with rheumatoid arthritis magnetic resonance imaging scoring (RAMRIS) across whole hands was then evaluated. The reference standard was determined by an experienced musculoskeletal radiologist. Area under the curve (AUC) of receiver operating characteristic (ROC), Dice and Spearman's rank correlation coefficients, and interclass correlation coefficient (ICC). A P-value <0.05 was considered statistically significant. A minimum of 15 phases (acquisition time at least 2.5 minutes) was found to be necessary. AUC ranged from 0.941 ± 0.009 to 0.965 ± 0.009. The Dice score was 0.557-0.615. Spearman's correlation coefficients between the AI model and ground truth were 0.884-0.927 and 0.736-0.831, for joint ROIs and whole hands, respectively. The Spearman's correlation coefficient for the additional test set between the model trained with 15 phases and RAMRIS was 0.768. The AI-based classification model effectively identified synovitis pixels while excluding arteries. The optimal performance was achieved with at least 15 phases, providing a quantitative assessment of inflammatory activity in RA while minimizing acquisition time. 3 TECHNICAL EFFICACY: Stage 2.

Auditory Effects of Acoustic Noise From 3-T Brain MRI in Neonates With Hearing Protection.

Neonates with immature auditory function (eg, weak/absent middle ear muscle reflex) could conceivably be vulnerable to noise-induced hearing loss; however, it is unclear if neonates show evidence of hearing loss following MRI acoustic noise exposure. To explore the auditory effects of MRI acoustic noise in neonates. Prospective. Two independent cohorts of neonates (N = 19 and N = 18; mean gestational-age, 38.75 ± 2.18 and 39.01 ± 1.83 weeks). T1-weighted three-dimensional gradient-echo sequence, T2-weighted fast spin-echo sequence, single-shot echo-planar imaging-based diffusion-tensor imaging, single-shot echo-planar imaging-based diffusion-kurtosis imaging and T2-weighted fluid-attenuated inversion recovery sequence at 3.0 T. All neonates wore ear protection during scan protocols lasted ~40 minutes. Equivalent sound pressure levels (SPLs) were measured for both cohorts. In cohort1, left- and right-ear auditory brainstem response (ABR) was measured before (baseline) and after (follow-up) MRI, included assessment of ABR threshold, wave I, III and V latencies and interpeak interval to determine the functional status of auditory nerve and brainstem. In cohort2, baseline and follow-up left- and right-ear distortion product otoacoustic emission (DPOAE) amplitudes were assessed at 1.2 to 7.0 kHz to determine cochlear function. Wilcoxon signed-rank or paired t-tests with Bonferroni's correction were used to compare the differences between baseline and follow-up ABR and DPOAE measures. Equivalent SPLs ranged from 103.5 to 113.6 dBA. No significant differences between baseline and follow-up were detected in left- or right-ear ABR measures (P > 0.999, Bonferroni corrected) in cohort1, or in DPOAE levels at 1.2 to 7.0 kHz in cohort2 (all P > 0.999 Bonferroni corrected except for left-ear levels at 3.5 and 7.0 kHz with corrected P = 0.138 and P = 0.533). A single 40-minute 3-T MRI with equivalent SPLs of 103.5-113.6 dBA did not result in significant transient disruption of auditory function, as measured by ABR and DPOAE, in neonates with adequate hearing protection. 2. Stage 5.

The feasibility of half-dose contrast-enhanced scanning of brain tumours at 5.0 T: a preliminary study

PurposeThis study investigated and compared the effects of Gd enhancement on brain tumours with a half-dose of contrast medium at 5.0 T and with a full dose at 3.0 T.MethodsTwelve subjects diagnosed with brain tumours were included in this study and underwent MRI after contrast agent injection at 3.0 T (full dose) or 5.0 T (half dose) with a 3D T1-weighted gradient echo sequence. The postcontrast images were compared by two independent neuroradiologists in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective image quality score on a ten-point Likert scale. Quantitative indices and subjective quality ratings were compared with paired Student's t tests, and interreader agreement was assessed with the intraclass correlation coefficient (ICC).ResultsA total of 16 enhanced tumour lesions were detected. The SNR was significantly greater at 5.0 T than at 3.0 T in grey matter, white matter and enhanced lesions (p < 0.001). The CNR was also significantly greater at 5.0 T than at 3.0 T for grey matter/tumour lesions, white matter/tumour lesions, and grey matter/white matter (p < 0.001). Subjective evaluation revealed that the internal structure and outline of the tumour lesions were more clearly displayed with a half-dose at 5.0 T (Likert scale 8.1 ± 0.3 at 3.0 T, 8.9 ± 0.3 at 5.0 T, p < 0.001), and the effects of enhancement in the lesions were comparable to those with a full dose at 3.0 T (7.8 ± 0.3 at 3.0 T, 8.7 ± 0.4 at 5.0 T, p < 0.001). All subjective scores were good to excellent at both 5.0 T and 3.0 T.ConclusionBoth quantitative and subjective evaluation parameters suggested that half-dose enhanced scanning via 5.0 T MRI might be feasible for meeting clinical diagnostic requirements, as the image quality remains optimal. Enhanced scanning at 5.0 T with a half-dose of contrast agents might benefit patients with conditions that require less intravenous contrast agent, such as renal dysfunction.

Cotyledon-Specific Flow Evaluation of Rhesus Macaque Placental Injury Using Ferumoxytol Dynamic Contrast-Enhanced MRI.

Recently, dynamic contrast-enhanced (DCE) MRI with ferumoxytol as contrast agent has recently been introduced for the noninvasive assessment of placental structure and function throughout. However, it has not been demonstrated under pathological conditions. To measure cotyledon-specific rhesus macaque maternal placental blood flow using ferumoxytol DCE MRI in a novel animal model for local placental injury. Prospective animal model. Placental injections of Tisseel (three with 0.5 mL and two with 1.5 mL), monocyte chemoattractant protein 1 (three with 100 μg), and three with saline as controls were performed in a total of 11 rhesus macaque pregnancies at approximate gestational day (GD 101). DCE MRI scans were performed prior (GD 100) and after (GD 115 and GD 145) the injection (term = GD 165). 3 T, T1-weighted spoiled gradient echo sequence (product sequence, DISCO). Source images were inspected for motion artefacts from the mother or fetus. Placenta segmentation and DCE processing were performed for the dynamic image series to measure cotyledon specific volume, flow, and normalized flow. Overall placental histopathology was conducted for controls, Tisseel, and MCP-1 animals and regions of tissue infarctions and necrosis were documented. Visual inspections for potential necrotic tissue were conducted for the two Tisseelx3 animals. Wilcoxon rank sum test, significance level P < 0.05. No motion artefacts were observed. For the group treated with 1.5 mL of Tisseel, significantly lower cotyledon volume, flow, and normalized flow per cotyledon were observed for the third gestational time point of imaging (day ~145), with mean normalized flow of 0.53 minute-1. Preliminary histopathological analysis shows areas of tissue necrosis from a selected cotyledon in one Tisseel-treated (single dose) animal and both Tisseelx3 (triple dose) animals. This study demonstrates the feasibility of cotyledon-specific functional analysis at multiple gestational time points and injury detection in a placental rhesus macaque model through ferumoxytol-enhanced DCE MRI. NA TECHNICAL EFFICACY: Stage 2.

Three-Dimensional Multifrequency MR Elastography for Microvascular Invasion and Prognosis Assessment in Hepatocellular Carcinoma.

Pretreatment identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is important when selecting treatment strategies. To improve models for predicting MVI and recurrence-free survival (RFS) by developing nomograms containing three-dimensional (3D) MR elastography (MRE). Prospective. 188 patients with HCC, divided into a training cohort (n = 150) and a validation cohort (n = 38). In the training cohort, 106/150 patients completed a 2-year follow-up. 1.5T 3D multifrequency MRE with a single-shot spin-echo echo planar imaging sequence, and 3.0T multiparametric MRI (mp-MRI), consisting of diffusion-weighted echo planar imaging, T2-weighted fast spin echo, in-phase out-of-phase T1-weighted fast spoiled gradient-recalled dual-echo and dynamic contrast-enhanced gradient echo sequences. Multivariable analysis was used to identify the independent predictors for MVI and RFS. Nomograms were constructed for visualization. Models for predicting MVI and RFS were built using mp-MRI parameters and a combination of mp-MRI and 3D MRE predictors. Student's t-test, Mann-Whitney U test, chi-squared or Fisher's exact tests, multivariable analysis, area under the receiver operating characteristic curve (AUC), DeLong test, Kaplan-Meier analysis and log rank tests. P < 0.05 was considered significant. Tumor c and liver c were independent predictors of MVI and RFS, respectively. Adding tumor c significantly improved the diagnostic performance of mp-MRI (AUC increased from 0.70 to 0.87) for MVI detection. Of the 106 patients in the training cohort who completed the 2-year follow up, 34 experienced recurrence. RFS was shorter for patients with MVI-positive histology than MVI-negative histology (27.1 months vs. >40 months). The MVI predicted by the 3D MRE model yielded similar results (26.9 months vs. >40 months). The MVI and RFS nomograms of the histologic-MVI and model-predicted MVI-positive showed good predictive performance. Biomechanical properties of 3D MRE were biomarkers for MVI and RFS. MVI and RFS nomograms were established. 2 TECHNICAL EFFICACY: Stage 2.

Multiphase MRI-Based Radiomics for Predicting Histological Grade of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer. Accurate preoperative prediction of histological grade holds potential for improving clinical management and disease prognostication. To evaluate the performance of a radiomics signature based on multiphase MRI in assessing histological grade in solitary HCC. Retrospective. A total of 405 patients with histopathologically confirmed solitary HCC and with liver gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI within 1 month of surgery. Contrast-enhanced T1-weighted spoiled gradient echo sequence (LAVA) at 1.5 or 3.0 T. Tumors were graded (low/high) according to results of histopathology. Basic clinical characteristics (including age, gender, serum alpha-fetoprotein (AFP) level, history of hepatitis B, and cirrhosis) were collected and tumor size measured. Radiomics features were extracted from Gd-EOB-DTPA-enhanced MRI data. Three feature selection strategies were employed sequentially to identify the optimal features: SelectFromModel (SFM), SelectPercentile (SP), and recursive feature elimination with cross-validation (RFECV). Probabilities of five single-phase radiomics-based models were averaged to generate a radiomics signature. A combined model was built by combining the radiomics signature and clinical predictors. Pearson χ2 test/Fisher exact test, Wilcoxon rank sum test, interclass correlation coefficient (ICC), univariable/multivariable logistic regression analysis, area under the receiver operating characteristic (ROC) curve (AUC), DeLong test, calibration curve, Brier score, decision curve, Kaplan-Meier curve, and log-rank test. A P-value <0.05 was considered statistically significant. High-grade HCCs were present in 33.8% of cases. AFP levels (odds ratio [OR] 1.89) and tumor size (>5 cm; OR 2.33) were significantly associated with HCC grade. The combined model had excellent performance in assessing HCC grade in the test dataset (AUC: 0.801), and demonstrated satisfactory calibration and clinical utility. A model that combined a radiomics signature derived from preoperative multiphase Gd-EOB-DTPA-enhanced MRI and clinical predictors showed good performance in assessing HCC grade. 3 TECHNICAL EFFICACY: Stage 5.

Specific Alterations in Brain White Matter Networks and Their Impact on Clinical Function in Pediatric Patients With Thoracolumbar Spinal Cord Injury.

The alternation of brain white matter (WM) network has been studied in adult spinal cord injury (SCI) patients. However, the WM network alterations in pediatric SCI patients remain unclear. To evaluate WM network changes and their functional impact in children with thoracolumbar SCI (TSCI). Prospective. Thirty-five pediatric patients with TSCI (8.94 ± 1.86 years, 8/27 males/females) and 34 age- and gender-matched healthy controls (HCs) participated in this study. 3.0 T/DTI imaging using spin-echo echo-planar and T1-weighted imaging using 3D T1-weighted magnetization-prepared rapid gradient-echo sequence. Pediatric SCI patients were evaluated for motor and sensory scores, injury level, time since injury, and age at injury. The WM network was constructed using a continuous tracing method, resulting in a 90 × 90 matrix. The global and regional metrics were obtained to investigate the alterations of the WM structural network. topology. Two-sample independent t-tests, chi-squared test, Mann-Whitney U-test, and Spearman correlation. Statistical significance was set at P < 0.05. Compared with HCs, pediatric TSCI patients displayed decreased shortest path length (Lp = 1.080 ± 0.130) and normalized Lp (λ = 5.020 ± 0.363), and increased global efficiency (Eg = 0.200 ± 0.015). Notably, these patients also demonstrated heightened regional properties in the orbitofrontal cortex, limbic system, default mode network, and several audio-visual-related regions. Moreover, the λ and Lp values negatively correlated with sensory scores. Conversely, nodal efficiency values in the right calcarine fissure and surrounding cortex positively correlated with sensory scores. The age at injury positively correlated with node degree in the left parahippocampal gyrus and nodal efficiency in the right posterior cingulate gyrus. Reorganization of the WM networks in pediatric SCI patients is indicated by increased global and nodal efficiency, which may provide promising neuroimaging biomarkers for functional assessment of pediatric SCI. 2 TECHNICAL EFFICACY: Stage 5.

Evaluate the Microvascular Invasion of Hepatocellular Carcinoma (≤5 cm) and Recurrence Free Survival with Gadoxetate Disodium-Enhanced MRI-Based Habitat Imaging.

Tumors are heterogenous and consist of subregions, also known as tumoral habitats, each exhibiting varied biological characteristics. Each habitat corresponds to a cluster of tissue sharing similar structural, metabolic, or functional characteristics. The habitat imaging technique facilitates both the visualization and quantification of these tumoral habitats. To evaluate the microvascular invasion (MVI) in hepatocellular carcinoma (HCC) (≤5 cm) and assess the recurrence-free survival (RFS) using gadoxetate disodium-enhanced MRI-based habitat imaging. Retrospective. 180 patients (52.9 years ± 11.7, 156 men) with HCC. 1.5T/contrast-enhanced T1-weighted gradient-echo sequence. The enhancement ratio of signal intensity at the arterial phase (AER) and hepatobiliary phase (HBPER) were calculated. The HCC lesions and their peritumoral tissues of 3, 5, and 7 mm were encoded into four habitats. The volume fraction of each habitat was then quantified. The diagnostic performance was assessed using the receiver operating characteristic analysis with 5-fold cross-validation. The RFS was evaluated with Kaplan-Meier curves. Habitat 2 (with median to high AER and low HBPER) within the peritumoral tissue of 3 mm (f2-P3) and tumor diameter could serve as independent risk factors for MVI and showed the statistical significance (odds ratio (OR) of f2-P3 = 1.170, 95% CI = 1.099-1.246; OR of tumor diameter: 6.112, 95% CI = 2.162-17.280). A nomogram was developed by incorporating f2-P3 and tumor diameter, demonstrating high diagnostic accuracy. The area under the curve from 5-fold cross-validation ranged from 0.880 to 1.000. Additionally, the nomogram model demonstrated high efficacy in risk stratification for RFS. Habitat imaging of HCC and its peritumoral microenvironment has the potential for noninvasive and preoperative identification of MVI and prognostic assessment. 3 TECHNICAL EFFICACY: Stage 2.

Preoperative Subtyping of WHO Grade 1 Meningiomas Using a Single-Shot Ultrafast MR T2 Mapping.

Meningioma subtype is crucial in treatment planning and prognosis delineation, for grade 1 meningiomas. T2 relaxometry could provide detailed microscopic information but is often limited by long scanning times. To investigate the potential of T2 maps derived from multiple overlapping-echo detachment imaging (MOLED) for predicting meningioma subtypes and Ki-67 index, and to compare the diagnostic efficiency of two different region-of-interest (ROI) placements (whole-tumor and contrast-enhanced, respectively). Prospective. A phantom containing 11 tubes of MnCl2 at different concentrations, eight healthy volunteers, and 75 patients with grade 1 meningioma. 3 T scanner. MOLED, T2-weighted spin-echo sequence, T2-dark-fluid sequence, and postcontrast T1-weighted gradient echo sequence. Two ROIs were delineated: the whole-tumor area (ROI1) and contrast-enhanced area (ROI2). Histogram parameters were extracted from T2 maps. Meningioma subtypes and Ki-67 index were reviewed by a neuropathologist according to the 2021 classification criteria. Linear regression, Bland-Altman analysis, Pearson's correlation analysis, independent t test, Mann-Whitney U test, Kruskal-Wallis test with Bonferroni correction, and multivariate logistic regression analysis with the P-value significance level of 0.05. The MOLED T2 sequence demonstrated excellent accuracy for phantoms and volunteers (Meandiff = -1.29%, SDdiff = 1.25% and Meandiff = 0.36%, SDdiff = 2.70%, respectively), and good repeatability for volunteers (average coefficient of variance = 1.13%; intraclass correlation coefficient = 0.877). For both ROI1 and ROI2, T2 variance had the highest area under the curves (area under the ROC curve = 0.768 and 0.761, respectively) for meningioma subtyping. There was no significant difference between the two ROIs (P = 0.875). Significant correlations were observed between T2 parameters and Ki-67 index (r = 0.237-0.374). MOLED T2 maps can effectively differentiate between meningothelial, fibrous, and transitional meningiomas. Moreover, T2 histogram parameters were significantly correlated with the Ki-67 index. 1 TECHNICAL EFFICACY: Stage 2.

Application of a deep learning algorithm for three-dimensional T1-weighted gradient-echo imaging of gadoxetic acid-enhanced MRI in patients at a high risk of hepatocellular carcinoma.

To evaluate the efficacy of a vendor-specific deep learning reconstruction algorithm (DLRA) in enhancing image quality and focal lesion detection using three-dimensional T1-weighted gradient-echo images in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI) in patients at a high risk of hepatocellular carcinoma. In this retrospective analysis, 83 high-risk patients with hepatocellular carcinoma underwent gadoxetic acid-enhanced liver MRI using a 3-T scanner. Triple arterial phase, high-resolution portal venous phase, and high-resolution hepatobiliary phase images were reconstructed using conventional reconstruction techniques and DLRA (AIRTM Recon DL; GE Healthcare) for subsequent comparison. Image quality and solid focal lesion detection were assessed by three abdominal radiologists and compared between conventional and DL methods. Focal liver lesion detection was evaluated using figures of merit (FOMs) from a jackknife alternative free-response receiver operating characteristic analysis on a per-lesion basis. DLRA-reconstructed images exhibited significantly improved overall image quality, image contrast, lesion conspicuity, vessel conspicuity, and liver edge sharpness and reduced subjective image noise, ringing artifacts, and motion artifacts compared to conventionally reconstructed images (all P < 0.05). Although there was no significant difference in the FOMs of non-cystic focal liver lesions between the conventional and DL methods, DLRA-reconstructed images showed notably higher pooled sensitivity than conventionally reconstructed images (P < 0.05) in all phases and higher detection rates for viable post-treatment HCCs in the arterial and hepatobiliary phases (all P < 0.05). Implementing DLRA can enhance the image quality in 3D T1-weighted gradient-echo sequences of gadoxetic acid-enhanced liver MRI examinations, leading to improved detection of viable post-treatment HCCs.

Deep-learning-based image quality enhancement of CT-like MR imaging in patients with suspected traumatic shoulder injury

PurposeTo evaluate the diagnostic performance of CT-like MR images reconstructed with an algorithm combining compressed sense (CS) with deep learning (DL) in patients with suspected osseous shoulder injury compared to conventional CS-reconstructed images. MethodsThirty-two patients (12 women, mean age 46 ± 14.9 years) with suspected traumatic shoulder injury were prospectively enrolled into the study. All patients received MR imaging of the shoulder, including a CT-like 3D T1-weighted gradient-echo (T1 GRE) sequence and in case of suspected fracture a conventional CT. An automated DL-based algorithm, combining CS and DL (CS DL) was used to reconstruct images of the same k-space data as used for CS reconstructions. Two musculoskeletal radiologists assessed the images for osseous pathologies, image quality and visibility of anatomical landmarks using a 5-point Likert scale. Moreover, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. ResultsCompared to CT, all acute fractures (n = 23) and osseous pathologies were detected accurately on the CS only and CS DL images with almost perfect agreement between the CS DL and CS only images (κ 0.95 (95 %confidence interval 0.82–1.00). Image quality as well as the visibility of the fracture lines, bone fragments and glenoid borders were overall rated significantly higher for the CS DL reconstructions than the CS only images (CS DL range 3.7–4.9 and CS only range 3.2–3.8, P = 0.01–0.04). Significantly higher SNR and CNR values were observed for the CS DL reconstructions (P = 0.02–0.03). ConclusionEvaluation of traumatic shoulder pathologies is feasible using a DL-based algorithm for reconstruction of high-resolution CT-like MR imaging.

Detection of Brain Metastases by Contrast-Enhanced MRI: Comparison of Gadopiclenol and Gadobenate in a Mouse Model.

The aim of this study was to evaluate the capacity of gadopiclenol, a high-relaxivity gadolinium-based contrast agent to detect brain metastases in mice as a function of dose (0.08 mmol/kg or 0.1 mmol/kg) compared with gadobenate at 0.1 mmol/kg. Brain metastases were induced by ultrasound-guided intracardiac implantation of 1.10 5 MDA-MB-231Br cells in the left ventricle of 18 anesthetized Balb/c Nude nu/nu female mice. At day 28 ± 3 after cell injection, each mouse received 2 crossover intravenous injections at 24-hour intervals, randomly selected from 2 doses of gadopiclenol (0.08 mmol/kg or 0.1 mmol/kg) and gadobenate (0.1 mmol/kg) with n = 6 mice/group (3 groups). Brain magnetic resonance imaging sessions were performed at 4 weeks on a 2.35 T magnet with a 3-dimensional T1-weighted high-resolution gradient echo sequence, before and after each injection. Images were blindly and randomly analyzed to detect enhancing lesions. Contrast-to-noise ratio between the metastases and the surrounding healthy parenchyma was calculated, based on region-of-interest signal measurements. In 2 animals per group, an early time point was added to the protocol (day 22 ± 3) to evaluate the sensitivity of detection as a function of time. After the last imaging session, the presence and location of whole-brain metastases were confirmed by histology in 4 mice. After gadopiclenol, approximately twice as many metastases were detected compared with gadobenate, regardless of the dose. Contrast-to-noise ratios of the detected metastases were 2.3 and 3.3 times higher with gadopiclenol at 0.08 mmol/kg and 0.1 mmol/kg, respectively, compared with gadobenate at 0.1 mmol/kg ( P < 0.0001). Gadopiclenol at the dose of 0.1 mmol/kg resulted in a 1.4-fold higher contrast compared with gadopiclenol at 0.08 mmol/kg ( P < 0.02). In a subset of mice that were imaged 1 week earlier, 2 metastases were detected with gadopiclenol and not with gadobenate. The high-relaxivity macrocyclic gadolinium-based contrast agent gadopiclenol allowed higher diagnostic performance for detecting brain enhancing metastases in terms of contrast-to-noise ratio and number of detected metastases compared with gadobenate, at both equal (0.1 mmol/kg) dose and 20% lower Gd dose (0.08 mmol/kg). Tumor detection was higher after gadopiclenol at the dose of 0.1 mmol/kg compared with 0.08 mmol/kg.