Conventional T2-weighted Imaging Research Articles

Synthetic double inversion recovery imaging for rectal cancer T staging evaluation: imaging quality and added value to T2-weighted imaging

ObjectiveTo assess the image quality of synthetic double inversion recovery (SyDIR) imaging and enhance the value of T2-weighted imaging (T2WI) in evaluating T stage for rectal cancer patients.MethodsA total of 112 pathologically confirmed rectal cancer patients were retrospectively selected after undergoing MRI, including synthetic MRI. The image quality of T2WI and SyDIR imaging was compared based on signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall picture quality, presence of motion artifacts, lesion edge sharpness, and conspicuity. The concordance between MRI and pathological staging results, using T2WI alone and the combination of T2WI and SyDIR for junior and senior radiologists, was assessed using the Kappa test. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic efficacy of extramural infiltration in rectal cancer patients.ResultsNo significant differences in imaging quality were observed between conventional T2WI and SyDIR (p = 0.07–0.53). The combination of T2WI and SyDIR notably improved the staging concordance between MRI and pathology for both junior (kappa value from 0.547 to 0.780) and senior radiologists (kappa value from 0.738 to 0.834). In addition, the integration of T2WI and SyDIR increased the AUC for diagnosing extramural infiltration for both junior (from 0.842 to 0.918) and senior radiologists (from 0.917 to 0.938).ConclusionThe combination of T2WI and SyDIR increased the consistency of T staging between MRI and pathology, as well as the diagnostic performance of extramural infiltration, which would benefit treatment selection.Critical relevance statementSyDIR sequence provides additional diagnostic value for T2WI in the T staging of rectal cancer, improving the agreement of T staging between MRI and pathology, as well as the diagnostic performance of extramural infiltration.Key PointsSynthetic double inversion recovery (SyDIR) and T2WI have comparable image quality.SyDIR provides rectal cancer anatomical features for extramural infiltration detections.The combination of T2WI and SyDIR improves the accuracy of T staging in rectal cancer.Graphical

Sex and mental health are related to subcortical brain microstructure

Some mental health problems such as depression and anxiety are more common in females, while others such as autism and attention deficit/hyperactivity (AD/H) are more common in males. However, the neurobiological origins of these sex differences are poorly understood. Animal studies have shown substantial sex differences in neuronal and glial cell structure, while human brain imaging studies have shown only small differences, which largely reflect overall body and brain size. Advanced diffusion MRI techniques can be used to examine intracellular, extracellular, and free water signal contributions and provide unique insights into microscopic cellular structure. However, the extent to which sex differences exist in these metrics of subcortical gray matter structures implicated in psychiatric disorders is not known. Here, we show large sex-related differences in microstructure in subcortical regions, including the hippocampus, thalamus, and nucleus accumbens in a large sample of young adults. Unlike conventional T1-weighted structural imaging, large sex differences remained after adjustment for age and brain volume. Further, diffusion metrics in the thalamus and amygdala were associated with depression, anxiety, AD/H, and antisocial personality problems. Diffusion MRI may provide mechanistic insights into the origin of sex differences in behavior and mental health over the life course and help to bridge the gap between findings from experimental, epidemiological, and clinical mental health research.

Conventional magnetic resonance imaging key features for distinguishing pathologically confirmed corticobasal degeneration from its mimics: a retrospective analysis of the J-VAC study.

Due to the indistinguishable clinical features of corticobasal syndrome (CBS), the antemortem differentiation between corticobasal degeneration (CBD) and its mimics remains challenging. However, the utility of conventional magnetic resonance imaging (MRI) for the diagnosis of CBD has not been sufficiently evaluated. This study aimed to investigate the diagnostic performance of conventional MRI findings in differentiating pathologically confirmed CBD from its mimics. Semiquantitative visual rating scales were employed to assess the degree and distribution of atrophy and asymmetry on conventional T1-weighted and T2-weighted images. Additionally, subcortical white matter hyperintensity (SWMH) on fluid-attenuated inversion recovery images were visually evaluated. In addition to 19 patients with CBD, 16 with CBD mimics (progressive supranuclear palsy (PSP): 9, Alzheimer's disease (AD): 4, dementia with Lewy bodies (DLB): 1, frontotemporal lobar degeneration with TAR DNA-binding protein of 43kDa(FTLD-TDP): 1, and globular glial tauopathy (GGT): 1) were investigated. Compared with the CBD group, the PSP-CBS subgroup showed severe midbrain atrophy without SWMH. The non-PSP-CBS subgroup, comprising patients with AD, DLB, FTLD-TDP, and GGT, showed severe temporal atrophy with widespread asymmetry, especially in the temporal lobes. In addition to over half of the patients with CBD, two with FTLD-TDP and GGT showed SWMH, respectively. This study elucidates the distinct structural changes between the CBD and its mimics based on visual rating scales. The evaluation of atrophic distribution and SWMH may serve as imaging biomarkers of conventional MRI for detecting background pathologies.

High-resolution and highly accelerated MRI T2 mapping as a tool to characterise renal tumour subtypes and grades

BackgroundClinical imaging tools to probe aggressiveness of renal masses are lacking, and T2-weighted imaging as an integral part of magnetic resonance imaging protocol only provides qualitative information. We developed high-resolution and accelerated T2 mapping methods based on echo merging and using k-t undersampling and reduced flip angles (TEMPURA) and tested their potential to quantify differences between renal tumour subtypes and grades.MethodsTwenty-four patients with treatment-naïve renal tumours were imaged: seven renal oncocytomas (RO); one eosinophilic/oncocytic renal cell carcinoma; two chromophobe RCCs (chRCC); three papillary RCCs (pRCC); and twelve clear cell RCCs (ccRCC). Median, kurtosis, and skewness of T2 were quantified in tumours and in the normal-adjacent kidney cortex and were compared across renal tumour subtypes and between ccRCC grades.ResultsHigh-resolution TEMPURA depicted the tumour structure at improved resolution compared to conventional T2-weighted imaging. The lowest median T2 values were present in pRCC (high-resolution, 51 ms; accelerated, 45 ms), which was significantly lower than RO (high-resolution; accelerated, p = 0.012) and ccRCC (high-resolution, p = 0.019; accelerated, p = 0.008). ROs showed the lowest kurtosis (high-resolution, 3.4; accelerated, 4.0), suggestive of low intratumoural heterogeneity. Lower T2 values were observed in higher compared to lower grade ccRCCs (grades 2, 3 and 4 on high-resolution, 209 ms, 151 ms, and 106 ms; on accelerated, 172 ms, 160 ms, and 102 ms, respectively), with accelerated TEMPURA showing statistical significance in comparison (p = 0.037).ConclusionsBoth high-resolution and accelerated TEMPURA showed marked potential to quantify differences across renal tumour subtypes and between ccRCC grades.Trial registrationClinicalTrials.gov, NCT03741426. Registered on 13 November 2018.Relevance statementThe newly developed T2 mapping methods have improved resolution, shorter acquisition times, and promising quantifiable readouts to characterise incidental renal masses.Graphical

Performance of T2 mapping in the staging of Graves' ophthalmopathy based on different region of interest selection methods.

Discriminating the stage of Graves' ophthalmopathy (GO) is crucial for clinical decision. Application of conventional T2-weighted imaging in the staging is still limited. To evaluate the performance of T2 mapping based on two different regions of interest (ROIs) for staging GO. In total, 56 GO patients were retrospectively enrolled and divided into two groups according to the clinical activity score (CAS). T2 relaxation time (T2RT) of extraocular muscle (EOM) on T2 mapping based on two different ROIs (T2RTROI-1: ROIs were drawn separately in the four EOMs; T2RTROI-2: ROI was drawn in the most inflamed EOM) was measured and compared between active and inactive groups. Both T2RTROI-1 and T2RTROI-2 values in the active GO were significantly higher than those of inactive GO (P <0.001). T2RTROI-1 and T2RTROI-2 values were positively correlated with CAS (rs=0.73, 0.69; P <0.001). When the T2RTROI-1 value of 83.3 ms and T2RTROI-2 value of 106.3 ms were used as cutoff values for staging GO, respectively, the best results were obtained with areas under the curve (AUCs) of 0.822 and 0.827. There was no significant difference for AUCs between T2RTROI-1 and T2RTROI-2 (P = 0.751). Excellent and good inter-observer agreements were achieved in quantitative measurements for T2RTROI-1 and T2RTROI-2 values, respectively, with intraclass correlation coefficients of 0.954 and 0.882. The T2RT values derived from two different ROIs were useful for assessment of disease activity. Taking reproducibility and diagnostic performance into consideration, T2RTROI-1 would be an ideal image biomarker for staging GO compared to T2RTROI-2.

Use of Dixon in magnetic resonance breast contrast-enhanced T1 weighted high-resolution imaging for mastectomy patients at 3T: A prospective study in single center

BackgroundFor patients with complete breast resection, conventional contrast-enhanced T1-weighted imaging (CE-T1WI) with frequency-selective spectral attenuated inversion recovery (SPAIR) provides limited fat suppression on the postoperative side due to the uneven skin surface, inhomogeneous tissue environment, and frequency-selective feature of the SPAIR scheme, leading to difficulties in precise diagnosis. This study aimed to investigate the image quality and performance of the Dixon method compared with SPAIR in breast high-resolution CE-T1WI for mastectomy patients. Materials and methodsSixty female patients who had not performed any breast surgeries were randomly selected retrospectively as the control group. Postmastectomy female patients were enrolled to undergone high-resolution CE-T1WI with SPAIR and Dixon breast scans. Subjective scores were rated using a 5-point scale. Objective parameters, including contrast-to-noise ratio (CNR), edge sharpness, and signal uniformity were measured and calculated. The Wilcoxon rank-sum test and Kappa statistic were used. ResultsA total of 114 consecutive postmastectomy patients were included. Subjective scores of T1WI-SPAIR in the control group were all significantly better than those with SPAIR on the postoperative side of mastectomy patients (P < 0.01). Dixon outperformed SPAIR with significantly better subjective scores in regards to uniformity and degree of fat-suppression, anatomical structures depiction, lesion conspicuity, and axillary visibility (p < 0.05) in both post- and non-operative sides and bilateral axillary areas through the paired comparison. The objective parameters of Dixon were significantly better than those of SPAIR. ConclusionThe Dixon method provided better image uniformity and higher fat suppression efficiency, and showed significant advantages in delineating the anatomical structures, with better axillary and lesion visibilities, especially on the completely removed breast side.

Detection of pathological contrast enhancement with synthetic brain imaging from quantitative multiparametric MRI.

We aimed to test whether synthetic T1-weighted imaging derived from a post-contrast Quantitative Transient-state Imaging (QTI) acquisition enabled revealing pathological contrast enhancement in intracranial lesions. The analysis included 141 patients who underwent a 3 Tesla-MRI brain exam with intravenous contrast media administration, with the post-contrast acquisition protocol comprising a three-dimensional fast spoiled gradient echo (FSPGR) sequence and a QTI acquisition. Synthetic T1-weighted images were generated from QTI-derived quantitative maps of relaxation times and proton density. Two neuroradiologists assessed synthetic and conventional post-contrast T1-weighted images for the presence and pattern of pathological contrast enhancement in intracranial lesions. Enhancement volumes were quantitatively compared. Using conventional imaging as a reference, synthetic T1-weighted imaging was 93% sensitive in revealing the presence of contrast enhancing lesions. The agreement for the presence/absence of contrast enhancement was almost perfect both between readers (k = 1 for both conventional and synthetic imaging) and between sequences (k = 0.98 for both readers). In 91% of lesions, synthetic T1-weighted imaging showed the same pattern of contrast enhancement visible in conventional imaging. Differences in enhancement pattern in the remaining lesions can be due to the lower spatial resolution and the longer acquisition delay from contrast media administration of QTI compared to FSPGR. Overall, enhancement volumes appeared larger in synthetic imaging. QTI-derived post-contrast synthetic T1-weighted imaging captures pathological contrast enhancement in most intracranial enhancing lesions. Further comparative studies employing quantitative imaging with higher spatial resolution is needed to support our data and explore possible future applications in clinical trials.

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.

Brain artery diameters and risk of dementia and stroke.

We tested the association of brain artery diameters with dementia and stroke risk in three distinct population-based studies using conventional T2-weighted brain magnetic resonance imaging (MRI) images. We included 8420 adults> 40 years old from three longitudinal population-based studies with brain MRI scans. We estimated and meta-analyzed the hazard ratios (HRs) of the brain and carotids and basilar diameters associated with dementia and stroke. Overall and carotid artery diameters>95th percentile increased the risk for dementia by 1.74 (95% confidence interval [CI], 1.13-2.68) and 1.48 (95% CI, 1.12-1.96) fold, respectively. For stroke, meta-analyses yielded HRs of 1.59 (95% CI, 1.04-2.42) for overall arteries and 2.11 (95% CI, 1.45-3.08) for basilar artery diameters> 95th percentile. Individuals with dilated brain arteries are at higher risk for dementia and stroke, across distinct populations. Our findings underline the potential value of T2-weighted brain MRI-based brain diameter assessment in estimating the risk of dementia and stroke.

Feasibility of deep learning-reconstructed thin-slice single-breath-hold HASTE for detecting pancreatic lesions: A comparison with two conventional T2-weighted imaging sequences

ObjectiveThe objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in comparison with two conventional T2-weighted imaging sequences: compressed-sensing HASTE (HASTECS) and BLADE. MethodsFrom March 2022 to January 2023, a total of 63 patients with suspected pancreatic-related disease underwent the HASTEDL, HASTECS, and BLADE sequences were enrolled in this retrospectively study. The acquisition time, the pancreatic lesion conspicuity (LCP), respiratory motion artifact (RMA), main pancreatic duct conspicuity (MPDC), overall image quality (OIQ), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of the pancreatic lesions were compared among the three sequences by two readers. ResultsThe acquisition time of both HASTEDL and HASTECS was 16 s, which was significantly shorter than that of 102 s for BLADE. In terms of qualitative parameters, Reader 1 and Reader 2 assigned significantly higher scores to the LCP, RMA, MPDC, and OIQ for HASTEDL compared to HASTECS and BLADE sequences; As for the quantitative parameters, the SNR values of the pancreatic head, body, tail, and lesions, the CNR of the pancreatic lesion measured by the two readers were also significantly higher for HASTEDL than for HASTECS and BLADE sequences. ConclusionsCompared to conventional T2WI sequences (HASTECS and BLADE), deep-learning reconstructed HASTE enables thin slice and single-breath-hold acquisition with clinical acceptable image quality for detection of pancreatic lesions.

Evaluation of Extra-Prostatic Extension on Deep Learning-Reconstructed High-Resolution Thin-Slice T2-Weighted Images in Patients with Prostate Cancer.

The aim of this study was to compare diagnostic performance for extra-prostatic extension (EPE) and image quality among three image datasets: conventional T2-weighted images (T2WIconv, slice thickness, 3 mm) and high-resolution thin-slice T2WI (T2WIHR, 2 mm), with and without deep learning reconstruction (DLR) in patients with prostatic cancer (PCa). A total of 88 consecutive patients (28 EPE-positive and 60 negative) diagnosed with PCa via radical prostatectomy who had undergone 3T-MRI were included. Two independent reviewers performed a crossover review in three sessions, in which each reviewer recorded five-point confidence scores for the presence of EPE and image quality using a five-point Likert scale. Pathologic topographic maps served as the reference standard. For both reviewers, T2WIconv showed better diagnostic performance than T2WIHR with and without DLR (AUCs, in order, for reviewer 1, 0.883, 0.806, and 0.772, p = 0.0006; for reviewer 2, 0.803, 0.762, and 0.745, p = 0.022). The image quality was also the best in T2WIconv, followed by T2WIHR with DLR and T2WIHR without DLR for both reviewers (median, in order, 3, 4, and 5, p < 0.0001). In conclusion, T2WIconv was optimal in regard to image quality and diagnostic performance for the evaluation of EPE in patients with PCa.

Feasibility study on the clinical application of CT-based synthetic brain T1-weighted MRI: comparison with conventional T1-weighted MRI.

This study aimed to examine the equivalence of computed tomography (CT)-based synthetic T1-weighted imaging (T1WI) to conventional T1WI for the quantitative assessment of brain morphology. This prospective study examined 35 adult patients undergoing brain magnetic resonance imaging (MRI) and CT scans. An image synthesis method based on a deep learning model was used to generate synthetic T1WI (sT1WI) from CT data. Two senior radiologists used sT1WI and conventional T1WI on separate occasions to independently measure clinically relevant brain morphological parameters. The reliability and consistency between conventional and synthetic T1WI were assessed using statistical consistency checks, comprising intra-reader, inter-reader, and inter-method agreement. The intra-reader, inter-reader, and inter-method reliability and variability mostly exhibited the desired performance, except for several poor agreements due to measurement differences between the radiologists. All the measurements of sT1WI were equivalent to that of T1WI at 5% equivalent intervals. This study demonstrated the equivalence of CT-based sT1WI to conventional T1WI for quantitatively assessing brain morphology, thereby providing more information on imaging diagnosis with a single CT scan. Real-time synthesis of MR images from CT scans reduces the time required to acquire MR signals, improving the efficiency of the treatment planning system and providing benefits in the clinical diagnosis of patients with contraindications such as presence of metal implants or claustrophobia. • Deep learning-based image synthesis methods generate synthetic T1-weighted imaging from CT scans. • The equivalence of synthetic T1-weighted imaging and conventional MRI for quantitative brain assessment was investigated. • Synthetic T1-weighted imaging can provide more information per scan and be used in preoperative diagnosis and radiotherapy.

Precision in Practice: A Cross-sectional Study Involving MRI T2 Dixon and Conventional Sequence in Detecting Focal Multiple Myeloma Lesions

Introduction: Multiple Myeloma (MM) represents a malignant proliferation of plasma cells derived from a single clone. Imaging of the skeleton beyond symptomatic areas is useful for myeloma staging and subsequent follow-up for treatment response and disease relapse. Despite research comparing the Dixon sequence to conventional sequences in a variety of musculoskeletal disorders, there is a lack of studies regarding the Dixon sequence’s application in MM. Aim: To compare the contrast of MM focal lesions in all four T2- weighted Dixon and Conventional T1-weighted spin-echo and Short Tau Inversion Recovery (STIR) images. Materials and Methods: This cross-sectional study was conducted in the Department of Radiology at Kovai Medical Centre and Hospitals (KMCH), Coimbatore, Tamil Nadu, India. All newly diagnosed and known cases of MM, either biopsyproven or strongly suspected based on other diagnostic testing conforming to International Myeloma Working Group (IMWG) criteria from December 2020 to July 2022, were included in the study. A total of 43 patients with 142 focal MM lesions were included. Contrast between focal MM lesions and surrounding bone marrow was calculated on T1-weighted spin-echo, STIR, and T2-weighted Dixon (all four) images. Statistical analysis was done using repeated measures of Analysis of Variance (ANOVA) with Bonferroni correction to control the type I error on multiple comparisons to find the significant difference between multivariate analyses. A probability value of 0.05 was considered a significant level for all statistical tools. Results: The study population consisted of 21 men and 22 women with a mean age of 65.3±8.6 years {Mean±Standard Deviation (SD)}. Contrast values in all four T2 Dixon images, STIR, and T1-weighted images were as follows: T2 Dixon Fat-only (FO) images (0.86.±0.09) (SD); range: (0.46-0.99), T2-weighted Dixon Water-only (WO) images (0.54±0.14) (SD); range: (0.14-0.82), T2 Dixon In-phase (IP) images (0.20±0.13) (SD); range: (0.02-0.41), T2-weighted Dixon Out-phase (OP) images (0.53±0.19) (SD); range: (0.12-0.87), STIR images (0.47±0.12) (SD); range: (0.12-0.73), and T1 images (0.23±0.12) (SD); range: (0.01-0.55). The mean contrast was highest on T2 Dixon fat-only images (p&lt;0.0005) compared to T1 images, with the lowest contrast seen in IP images and intermediate values in OP images. Conclusion: In conclusion, fat-only images of the T2 multipoint Dixon sequence provide significant contrast compared to conventional T1-weighted imaging. Dixon water-only images provide fat suppression that is not inferior to STIR images. While Dixon techniques in the diagnosis of MM did not significantly differ from the conventional sequence, Dixon stands out from conventional sequences when considering the study duration and contrast between the lesion and normal bone marrow.

Differentiation of bone metastases from benign red marrow depositions: utilizing qualitative and quantitative analysis of conventional T1-weighted imaging and fat-suppressed T2-weighted imaging.

To distinguish bone metastases (BMs) from benign red marrow depositions (BRMs) by qualitative and quantitative analyses of T1-weighted imaging and fat-suppressed T2-weighted imaging (T2 FS). For 75 lesions including 38 BMs and 37 BRMs, tworadiologists independently evaluated magnetic resonance images by qualitative (signal intensity [SI] of lesions compared to that of normal muscle [NM] or normal bone marrow [NBM]) and quantitative (parameters of the region of interests in the lesions, including T1 ratio [T1 SI ratio of lesion and NM], T2FMu ratio [T2 FS SI ratio of lesion and NM], and T2FMa ratio [T2 FS SI ratio of lesion and NBM]) analyses. Hyperintensity relative to NM or NBM on T2 FS was more frequent in BMs than in BRMs (100% vs 59.5%-78.4%, respectively; P ≤ 0.001) but also was present in more than half of BRMs. All quantitative parameters showed a significant difference between BMs and BRMs (T1 ratio, 1.075 vs 1.227 [P = 0.002]; T2FMu ratio, 2.094 vs 1.282 [P < 0.001]; T2FMa ratio, 3.232 vs 1.810 [P < 0.001]). The receiver operating characteristics areas under the curves of T2FMu and T2FMa ratios were clinically useful (0.781 and 0.841, respectively) and did not demonstrate statistically significant differences. The quantitative analysis of T2 FS facilitates distinguishing between BMs and BRMs, regardless of whether the reference was NM or NBM. Quantitative parameters derived from T2 FS facilitate differentiation of BMs BRMs without additional scans. The role of NBM as an internal standard for T2 FS to differentiate between BMs and BRMs is similar to that of NM.

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.

Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging.

Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging. A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify the outcome of TBI. We developed three models based on DTI, NODDI, and T1-weighted imaging, and we compared the accuracy results across different models. Compared with the conventional T1-weighted imaging-based classification with an accuracy of 51.7-56.8%, our machine learning-based models achieved significantly better results with DTI-based models at 58.7-73.0% accuracy and NODDI with an accuracy of 64.0-72.3%. The machine learning-based feature selection and classification algorithm based on hybrid diffusion features significantly outperform conventional T1-weighted imaging. The results suggest that advanced algorithms can be developed for inferring symptoms of chronic brain injury using feature selection and diffusion-weighted imaging.

Potential clinical feasibility of synthetic MRI in bladder tumors: a comparative study with conventional MRI.

Synthetic magnetic resonance imaging (MRI) can provide quantitative information about inherent tissue properties and synthesize tailored contrast-weighted images simultaneously in a single scan. This study aimed to investigate the clinical feasibility of synthetic MRI in bladder tumors. A total of 47 patients (37 males; mean age: 66±10 years old) with postoperative pathology-confirmed papillary urothelial neoplasms of the bladder were enrolled in this retrospective study. A 2-dimensional (2D) multi-dynamic multi-echo pulse sequence was performed for synthetic MRI at 3T. The overall image quality, lesion conspicuity, contrast resolution, resolution of subtle anatomic structures, motion artifact, blurring, and graininess of images were subjectively evaluated by 2 radiologists independently using a 5-point Likert scale for qualitative analysis. The signal intensity ratio (SIR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for quantitative analysis. Linear weighted Kappa, Wilcoxon's signed-rank test, and the Mann-Whitney U-test were used for statistical analysis. The interobserver consistency was excellent (κ values: 0.607-1). Synthetic T1-weighted (syn-T1w) and synthetic T2-weighted (syn-T2w) images obtained scores of 4 in most subjective terms, which were relatively smaller than those of conventional images. The SIR and SNR of syn-T1w were significantly higher than those of con-T1w images (SIR 2.37±0.86 vs. 1.47±0.20, P<0.001; SNR 21.83±9.43 vs. 14.81±3.30, P<0.001). No difference was found in SIR between syn-T2w and conventional T2-weighted (con-T2w) images, whereas the SNR of the syn-T2w was significantly lower (8.79±4.06 vs. 26.49±6.80, P<0.001). Additionally, the CNR of synthetic images was significantly lower than that of conventional images (T1w 1.41±0.72 vs. 2.68±1.04; T2w 1.40±0.87 vs. 4.03±1.55, all P<0.001). Synthetic MRI generates morphologic magnetic resonance (MR) images with diagnostically acceptable image quality in bladder tumors, especially T1-weighted images with high image contrast of tumors relative to urine. Further technological improvements are needed for synthetic MRI to reduce noise. Combined with T1, T2, and proton density (PD) quantitative data, synthetic MRI has potential for clinical application in bladder tumors.

Contrast Enhanced Magnetic Resonance Imaging of Amyloid-β Plaques in a Murine Alzheimer's Disease Model.

Early detection of amyloid-β (Aβ) aggregates is a critical step to improve the treatment of Alzheimer's disease (AD) because neuronal damage by the Aβ aggregates occurs before clinical symptoms are apparent. We have previously shown that luminescent conjugated oligothiophenes (LCOs), which are highly specific towards protein aggregates of Aβ, can be used to fluorescently label amyloid plaque in living rodents. We hypothesize that the LCO can be used to target gadolinium to the amyloid plaque and hence make the plaque detectable by T1-weighted magnetic resonance imaging (MRI). A novel LCO-gadolinium construct was synthesized to selectively bind to Aβ plaques and give contrast in conventional T1-weighted MR images after intravenous injection in Tg-APPSwe mice. We found that mice with high plaque-burden could be identified using the LCO-Gd constructs by conventional MRI. Our study shows that MR imaging of amyloid plaques is challenging but feasible, and hence contrast-mediated MR imaging could be a valuable tool for early AD detection.

Combining in vivo proton exchange rate (k ex) MRI with quantitative susceptibility mapping to further stratify the gadolinium-negative multiple sclerosis lesions.

Conventional gadolinium (Gd)-enhanced MRI is currently used for stratifying the lesion activity of multiple sclerosis (MS) despite limited correlation with disability and disease activity. The stratification of MS lesion activity needs further improvement to better support clinics. To investigate if the novel proton exchange rate (k ex ) MRI combined with quantitative susceptibility mapping (QSM) may help to further stratify non-enhanced (Gd-negative) MS lesions. From December 2017 to December 2020, clinically diagnosed relapsing-remitting MS patients who underwent MRI were consecutively enrolled in this IRB-approved retrospective study. The customized MRI protocol covered conventional T2-weighted, T2-fluid-attenuated-inversion-recovery, pre- and post-contrast T1-weighted imaging, and quantitative sequences, including k ex MRI based on direct-saturation removed omega plots and QSM. Each MS lesion was evaluated based on its Gd-enhancement as well as its susceptibility and k ex elevation compared to the normal appearing white matter. The difference and correlation concerning lesion characteristics and imaging contrasts were analyzed using the Mann-Whitney U test or Kruskal-Wallis test, and Spearman rank analysis with p < 0.05 considered significant. A total of 322 MS lesions from 30 patients were identified with 153 Gd-enhanced and 169 non-enhanced lesions. We found that the k ex elevation of all lesions significantly correlated with their susceptibility elevation (r = 0.30, p < 0.001). Within the 153 MS lesions with Gd-enhancement, ring-enhanced lesions showed higher k ex elevation than the nodular-enhanced ones' (p < 0.001). Similarly, lesions with ring-hyperintensity in QSM also had higher k ex elevation than the lesions with nodular-QSM-hyperintensity (p < 0.001). Of the 169 Gd-negative lesions, three radiological patterns were recognized according to lesion manifestations on the k ex map and QSM images: Pattern I (k ex + and QSM+, n = 114, 67.5%), Pattern II (only k ex + or QSM+, n = 47, 27.8%) and Pattern III (k ex - and QSM-, n = 8, 4.7%). Compared to Pattern II and III, Pattern I had higher k ex (p < 0.001) and susceptibility (p < 0.05) elevation. The percentage of Pattern I of each subject was negatively correlated with the disease duration (r = -0.45, p = 0.015). As a potential imaging biomarker for inflammation due to oxidative stress, in vivo k ex MRI combined with QSM is promising in extending the clinical classification of MS lesions beyond conventional Gd-enhanced MRI.

MRI detection of brain gadolinium retention in multiple sclerosis: Magnetization transfer vs. T1-weighted imaging.

Evidence of brain gadolinium retention has affected gadolinium-based contrast agent usage. It is, however, unclear to what extent macrocyclic agents are retained and whether their in vivo detection may necessitate nonconventional MRI. Magnetization transfer (MT) could prove suitable to detect gadolinium-related signal changes since dechelated gadolinium ions bind to macromolecules. Therefore, this study aimed to investigate associations of prior gadolinium administrations with MT and T1 signal abnormalities. A cohort of 23 persons with multiple sclerosis (MS) (18 females, 5 males, 57±8.0years) with multiple past gadolinium administrations (median 6, range 3-12) and 23 age- and sex-matched healthy controls underwent 1.5 Tesla MRI with MT, T1-weighted 2-dimensional spin echo, and T1-weighted 3-dimensional gradient echo. The signal intensity index was assessed by MRI in gadolinium retention predilection sites. There were dose-dependent associations of the globus pallidus signal on gradient echo (r=.55, p<.001) and spin echo (r=.38, p=.013) T1-weighted imaging, but not on MT. Relative to controls, MS patients had higher signal intensity index in the dentate nucleus on T1-weighted gradient echo (1.037±0.040 vs. 1.016±0.023, p=.04) with a similar trend in the globus pallidus on T1-weighted spin echo (1.091±0.034 vs. 1.076±0.014, p=.06). MT detected no group differences. Conventional T1-weighted imaging provided dose-dependent associations with gadolinium administrations in MS, while these could not be detected with 2-dimensional MT. Future studies could explore newer MT techniques like 3D and inhomogenous MT. Notably, these associations were identified with conventional MRI even though most patients had not received gadolinium administrations in the preceding 9years, suggestive of long-term retention.