Three-dimensional sectional measurement approach for serial volume changes in shoulder muscles after arthroscopic rotator cuff repair.

Purpose: This study assessed the serial volume changes in multiple shoulder muscles simultaneously following arthroscopic rotator cuff repair (ARCR) by a three-dimensional (3D) modeling-based sectional measurement. These volume changes were correlated with background preoperative factors. Methods: Four consecutive magnetic resonance imaging scans (preoperatively and postoperatively at 3, 6, and 12 months) of 33 shoulders from 31 patients who underwent arthroscopic rotator cuff repair were examined. We focused on the sectional volume differences of the supraspinatus, infraspinatus, teres minor, and subscapularis between preoperatively and 3 months postoperatively (Dif.pre.3mo) and between 3 and 12 months postoperatively (Dif.3.12mo). The correlation between volume differences and clinical/demographic parameters was determined by a multivariate analysis. Results: No statistically significant differences were observed for most serial changes in the shoulder muscle volumes. The tear-site muscles (supraspinatus and infraspinatus) showed similar tendencies for volume changes, whereas the non-tear-site muscles (teres minor and subscapularis) differed. A negative correlation was observed between Dif.pre.3mo and Dif.3.12mo for the supraspinatus, infraspinatus, and teres minor. These perioperative volume differences might correlate with tear size and symptom duration in the supraspinatus, as well as with a history of steroid injections and work and sports activity levels in the infraspinatus and teres minor. Conclusion: The serial volume changes in multiple shoulder muscles after ARCR measured using our 3D sectional approach exhibited different tendencies and clinical implications depending on the primary and non-primary site of tears. Our method may serve as a potential indicator to facilitate muscle recovery and prevent the progression of postoperative muscle atrophy.

Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.

A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m2, CKD stage G4-5); 172 with moderate renal dysfunction (30 ≤ eGFR < 60 mL/min/1.73 m2, CKD stage G3a/b); and 76 with mild renal dysfunction (eGFR ≥ 60 mL/min/1.73 m2, CKD stage G1-2) participated in this study. The model was applied to the right, left, and both kidneys, as well as to each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for the bilateral kidney models than for the unilateral kidney models. Our deep learning approach using kidney MRI can be applied to classify patients with CKD based on the severity of kidney disease.

3-Fr steerable microcatheter system via the upper limb artery in RADPLAT for right maxillary cancer.

BACKGROUND: To evaluate the efficacy of a catheter system using a 3-Fr sheath with a steerable microcatheter through right upper limb artery access for superselective intra-arterial cisplatin infusion and concomitant radiotherapy (RADPLAT) to treat right maxillary sinus squamous cell carcinoma (MS-SCC). MATERIAL AND METHODS: We retrospectively studied 46 sessions in eight patients treated between November 2020 and February 2023 using the catheter system briefly described below. A 3-Fr sheath was inserted into the distal radial, conventional radial, or brachial arteries. A coaxial catheter system with a 2.9-Fr steerable microcatheter and a 1.9-Fr microcatheter was advanced into the brachiocephalic artery. The right common carotid artery was selected by bending the tip of the steerable microcatheter. Coil embolization and intra-arterial cisplatin infusion after selecting each external carotid artery branch were achieved using this catheter system. RESULTS: Cisplatin infusion and coil embolization were successful in all sessions. Arterial occlusion at the sheath insertion sites was found in 29.4% (5/17) of the distal radial arteries and 33.3% (3/9) of the conventional radial arteries. No other major complications were observed during the procedure. CONCLUSION: Using a 3-Fr catheter system with a steerable microcatheter through right upper limb artery access is a feasible method for RADPLAT in treating right MS-SCC.

Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability.

This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models. The pointwise distance map showed anterior elevation of the trochlea, particularly at the central floor of the proximal trochlea, in the PFI models compared with the normal models. Principal component analysis examined shape variations in the PFI group, and several principal components exhibited shape variations in the trochlear floor and intercondylar width. Multivariate analysis showed that these shape components were significantly correlated with the PFI/non-PFI distinction after adjusting for age and sex. Our ML-based prediction model for PFI achieved a strong predictive performance with an accuracy of 0.909 ± 0.015, and an area under the curve of 0.939 ± 0.009 when using a support vector machine with a linear kernel. This study demonstrated that 3D MRI-based SSA can realistically visualize statistical results on surface models and may facilitate the understanding of complex shape features.

Comparing 2-dimensional versus 3-dimensional MR myelography for cerebrospinal fluid leak detection.

Purpose: We compared cerebrospinal fluid (CSF) leak conspicuity and image quality as visualized using 3D versus 2D magnetic resonance (MR) myelography in patients with spinal CSF leaks. Methods: Eighteen patients underwent spinal MR imaging at 3 Tesla. Three board-certified radiologists independently evaluated CSF leak conspicuity and image quality on a 4-point scale; the latter assessed by scoring fat suppression, venous visualization, and severity of CSF flow artifacts. Additionally, the evaluators ranked the overall performances of 2D versus 3D MR myelography upon completing side-by-side comparisons of CSF leak conspicuity. Inter-reader agreement was determined using the Gwet's AC1. Results: The quality of 3D MR myelography images was significantly better than that of 2D MR myelography with respect to CSF leak conspicuity (mean scores: 3.3 vs. 1.9, p < 0.0001) and severity of CSF flow artifacts on the axial view (mean scores: 1.0 vs. 2.5, p = 0.0001). Inter-reader agreement was moderate to almost perfect for 2D MR myelography (AC1 = 0.55-1.00), and almost perfect for 3D MR myelography (AC1 = 0.85-1.00). Moreover, 3D MR myelography was judged to be superior to 2D acquisition in 78 %, 83 %, and 83 % of the samples per readers 1, 2 and 3, respectively; the inter-reader agreement was almost perfect (AC1: reader 1 vs. 2; 0.98, reader 2 vs. 3; 0.96, reader 3 vs. 1; 0.98). Conclusion: CSF leaks are more conspicuous when using 3D MR myelography than when using its 2D counterpart; therefore, the former is more reliable for identifying such leaks.

Evaluation of Uterine Carcinosarcoma and Uterine Endometrial Carcinoma Using Magnetic Resonance Imaging Findings and Texture Features.

Aim  This study aimed to evaluate the diagnostic feasibility of magnetic resonance imaging (MRI) findings and texture features (TFs) for differentiating uterine endometrial carcinoma from uterine carcinosarcoma. Methods This retrospective study included 102 patients who were histopathologically diagnosed after surgery with uterine endometrial carcinoma (n=68) or uterine carcinosarcoma (n=34) between January 2008 and December 2021. We assessed conventional MRI findings and measurements (cMRFMs) and TFs on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) map, as well as their combinations, in differentiating between uterine endometrial carcinoma and uterine carcinosarcoma. The least absolute shrinkage and selection operator (LASSO) was used to select three features with the highest absolute value of the LASSO regression coefficient for each model and construct a discriminative model. Binary logistic regression analysis was used to analyze the disease models and conduct receiver operating characteristic analyses on the cMRFMs, T2WI-TFs, ADC-TFs, and their combined model to compare the two diseases. Results A total of four models were constructed from each of the three selected features. The area under the curve (AUC) of the discriminative model using these features was 0.772, 0.878, 0.748, and 0.915 for the cMRFMs, T2WI-TFs, ADC-TFs, and a combined model of cMRFMs and TFs, respectively. The combined model showed a higher AUC than the other models, with a high diagnostic performance (AUC=0.915). Conclusion A combined model using cMRFMs and TFs might be helpful for the differential diagnosis of uterine endometrial carcinoma and uterine carcinosarcoma.

A case of ovarian endometrioid carcinoma: Atypical MR imaging.

Endometrioid carcinoma is the second most common ovarian tumor, classified as an epithelial-stromal ovarian tumor, and is usually characterized by a cystic tumor with partial solid components on magnetic resonance (MR) images. In this case report, we discuss an 81-year-old female who presented with atypical genital bleeding and distended abdomen, for which she underwent abdominal computed tomography and MR imaging. Solid endometrioid carcinoma of the ovary is very rare but was confirmed in our patient during the histological examination after surgery.

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comprised 100 participants with renal dysfunction (RD; eGFR < 45 mL/min/1.73 m2) and 70 without (non-RD; eGFR ≥ 45 mL/min/1.73 m2). The model was applied to the right, left, and both kidneys; it was first evaluated on the non-RD group data and subsequently on the combined data of the RD and non-RD groups. For bilateral kidney segmentation of the non-RD group, the best performance was obtained when using IP image, with a Dice score of 0.902 ± 0.034, average surface distance of 1.46 ± 0.75 mm, and a difference of - 27 ± 21 mL between ground-truth and automatically computed volume. Slightly worse results were obtained for the combined data of the RD and non-RD groups and for unilateral kidney segmentation, particularly when segmenting the right kidney from the OP images. Our 3D CNN-assisted automatic segmentation tools can be utilized in future studies on total kidney volume measurements and various image analyses of a large number of patients with CKD.

Utility of contrast-enhanced 3D STIR FLAIR imaging for evaluating pituitary adenomas at 3 Tesla.

Purpose: To assess the usefulness of contrast-enhanced 3D STIR FLAIR imaging for evaluation of pituitary adenomas. Methods: Patients with pituitary adenomas underwent MR examinations including contrast-enhanced 3D STIR FLAIR and 2D T1-weighted (T1W) imaging. We subjectively compared the two techniques in terms of 10 categories. In addition, images were rated by side-by-side comparisons into three outcomes: 3D STIR FLAIR imaging superior, equal, or 2D T1W imaging superior. Additionally, the added value of 3D STIR FLAIR imaging for adenoma detection over conventional MR imaging was assessed. Results: Twenty-one patients were included in this study. 3D STIR FLAIR imaging offered significantly better images than 2D T1W imaging in terms of three categories, including overall visualization of the cranial nerves in the cavernous sinus (mean 4.0 vs. 2.8, p < 0.0001), visualization of the optic nerves and chiasm (mean 4.0 vs. 2.6, p < 0.0001), and severity of susceptibility artifacts (mean 0.0 vs. 0.4, p = 0.004). In the side-by-side comparison, 3D STIR FLAIR imaging was judged to be significantly superior to 2D T1W imaging for overall lesion conspicuity (62% vs. 19%, p = 0.049) and border between the adenoma and the pituitary gland (67% vs. 19%, p = 0.031). The addition of 3D STIR FLAIR imaging significantly improved the adenoma detection of conventional MR imaging. Conclusion: 3D STIR FLAIR imaging improved overall lesion conspicuity compared to 2D T1W imaging. We suggest that 3D STIR FLAIR imaging is recommended as a supplemental technique when pituitary adenomas are invisible or equivocal on conventional imaging.

Motion-robust MR imaging of the shoulder using compressed SENSE MultiVane.

Purpose: Motion artifacts caused by breathing or involuntary motion of patients, which may lead to reduced image quality and a loss of diagnostic information, are a major problem in shoulder magnetic resonance imaging (MRI). The MultiVane (MV) technique decreases motion artifacts; however, it tends to prolong the acquisition time. As a parallel imaging technique, SENSitivity Encoding (SENSE) can be combined with the compressed sensing method to produce compressed SENSE (C-SENSE), resulting in a markedly reduced acquisition time. This study aimed to evaluate the use of C-SENSE MV for MRI of the shoulder joint. Methods: Thirty-one patients who were scheduled to undergo MRI of the shoulder were included. This prospective study was approved by our institution's medical ethics committee, and written informed consent was obtained from all 31 patients. Two sets of oblique coronal images derived from the standard protocol were acquired without (standard) or with C-SENSE MV: proton-density weighted imaging (PDWI), PDWI with C-SENSE MV, T2-weighted imaging (T2WI) with fat suppression (fs), and T2WI fs with C-SENSE MV. Two radiologists graded motion artifacts and the detectability of anatomical shoulder structures on a 4-point scale (3, no artifacts/excellent delineation; 0, severe artifacts/difficulty with delineation). The Wilcoxon signed-rank test was used to compare the data for the standard and C-SENSE MV images. Results: Motion artifacts were significantly reduced on the C-SENSE MV images (p < 0.001). Regarding the detectability of anatomical structures, the ratings for the C-SENSE MV sequences were significantly better (p < 0.001).In conclusion, in shoulder MRI the newly developed C-SENSE MV technique reduces motion artifacts and increases the detectability of anatomical structures compared with standard sequences.

The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model.

We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images, apparent diffusion coefficient (ADC) maps, and T2* maps. The patients were divided into severe, moderate, and control groups based on eGFR borderlines of 30 and 60 mL/min/1.73 m2. After extracting 93 texture features (TFs), dimension reduction was performed using inter-observer reproducibility analysis and sequential feature selection (SFS) algorithm. Models were created using linear discriminant analysis (LDA); support vector machine (SVM) with linear, rbf, and sigmoid kernels; decision tree (DT); and random forest (RF) classifiers, with synthetic minority oversampling technique (SMOTE). Models underwent 100-time repeat nested cross-validation. Overall performances of our classification models were modest, and TA based on T1-weighted IP/OP/WO images provided better performance than those based on ADC and T2* maps. The most favorable result was observed in the T1-weighted WO image using RF classifier and the combination model was derived from all T1-weighted images using SVM classifier with rbf kernel. Among the selected TFs, total energy and energy had weak correlations with eGFR.

Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors.

OBJECTIVE: To evaluate the diagnostic utility of conventional magnetic resonance imaging (MRI)-based characteristics and a texture analysis (TA) for discriminating between ovarian thecoma-fibroma groups (OTFGs) and ovarian granulosa cell tumors (OGCTs). METHODS: This retrospective multicenter study enrolled 52 patients with 32 OGCTs and 21 OTFGs, which were dissected and pathologically diagnosed between January 2008 and December 2019. MRI-based features (MBFs) and texture features (TFs) were evaluated and compared between OTFGs and OGCTs. A least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select features and construct the discriminating model. ROC analyses were conducted on MBFs, TFs, and their combination to discriminate between the two diseases. RESULTS: We selected 3 features with the highest absolute value of the LASSO regression coefficient for each model: the apparent diffusion coefficient (ADC), peripheral cystic area, and contrast enhancement in the venous phase (VCE) for the MRI-based model; the 10th percentile, difference variance, and maximal correlation coefficient for the TA-based model; and ADC, VCE, and the difference variance for the combination model. The areas under the curves of the constructed models were 0.938, 0.817, and 0.941, respectively. The diagnostic performance of the MRI-based and combination models was similar (p = 0.38), but significantly better than that of the TA-based model (p < 0.05). CONCLUSIONS: The conventional MRI-based analysis has potential as a method to differentiate OTFGs from OGCTs. TA did not appear to be of any additional benefit. Further studies are needed on the use of these methods for a preoperative differential diagnosis of these two diseases.

Framework for estimating renal function using magnetic resonance imaging.

Purpose: Nephrologists have empirically predicted renal function from renal morphology. In diagnosing a case of renal dysfunction of unknown course, acute kidney injury and chronic kidney disease are diagnosed from blood tests and an imaging study including magnetic resonance imaging (MRI), and an examination/treatment policy is determined. A framework for the estimation of renal function from water images obtained using the Dixon method is proposed to provide information that helps clinicians reach a diagnosis by accurately estimating renal function on the basis of renal MRI. Approach: The proposed framework consists of four steps. First, the kidney area is extracted by MRI using the Dixon method with a U-net by deep learning. Second, the extracted renal region is registered with the target mask. Third, the kidney features are calculated based on the target mask classification information created by a specialist. Fourth, the estimated glomerular filtration rate (eGFR) representing the renal function is estimated using a regression support vector machine from the calculated features. Results: For the accuracy evaluation, we conducted an experiment to estimate the eGFR when MRI was performed and the eGFR slope, which is the annual rate of decline in eGFR. When the accuracy was evaluated for 165 subjects, the eGFR was estimated to have a root mean square error (RMSE) of 11.99 and a correlation coefficient of 0.83. Moreover, the eGFR slope was estimated to have an RMSE of 4.8 and a correlation coefficient of 0.5. Conclusions: Therefore, the proposed method shows the possibility of estimating the prognosis of renal function based on water images obtained by the Dixon method.

Contrast Enhancement of the Normal Infundibular Recess Using Heavily T2-weighted 3D FLAIR.

PURPOSE: The purpose of the present study was to evaluate contrast enhancement of the infundibular recess in the normal state using heavily T2-weighted 3D fluid-attenuated inversion recovery (FLAIR) (HT2-FLAIR). METHODS: Twenty-six patients were retrospectively recruited. We subjectively assessed overall contrast enhancement of the infundibular recess between postcontrast, 4-hour (4-h) delayed postcontrast, and precontrast HT2-FLAIR images. We also objectively conducted chronological and spatial comparisons by measuring the signal intensity (SI) ratio (SIR). Chronological comparisons were performed by comparing SI of the infundibular recess/SI of the midbrain (SIRIR-MB). Spatial comparisons were conducted by comparing SI on postcontrast HT2-FLAIR/SI on precontrast HT2-FLAIR (SIRPost-Pre) of the infundibular recess with that of other cerebrospinal fluid (CSF) spaces, including the superior part of the third ventricle, lateral ventricles, fourth ventricle, and interpeduncular cistern. RESULTS: In the subjective analysis, all cases showed contrast enhancement of the infundibular recess on both postcontrast and 4-h delayed postcontrast HT2-FLAIR, and showed weaker contrast enhancement of the infundibular recess on 4-h delayed postcontrast HT2-FLAIR than on postcontrast HT2-FLAIR. In the objective analysis, SIRIR-MB was the highest on postcontrast images, followed by 4-h delayed postcontrast images. SIRPost-Pre was significantly higher in the infundibular recess than in the other CSF spaces. CONCLUSION: The present results demonstrated that the infundibular recess was enhanced on HT2-FLAIR after an intravenous gadolinium injection. The infundibular recess may be a potential source of the leakage of intravenously administered gadolinium into the CSF.

Utility of magnetic resonance imaging for differentiating malignant mesenchymal tumors of the uterus from T2-weighted hyperintense leiomyomas.

PURPOSE: To generate a new discrimination method to distinguish between malignant mesenchymal tumors of the uterus and T2-weighted hyperintense leiomyoma based on magnetic resonance imaging findings and clinical features. MATERIALS AND METHODS: Data from 32 tumors of 32 patients with malignant mesenchymal tumors of the uterus and from 34 tumors of 30 patients with T2-weighted hyperintense leiomyoma were analyzed. Clinical parameters, qualitative magnetic resonance imaging features, including computed diffusion-weighted imaging, and quantitative characteristics of magnetic resonance imaging of these two tumor types were compared. Predictive values for malignant mesenchymal tumors of the uterus were calculated using variant discriminant analysis. RESULTS: The T1 bright area on qualitative assessment and mean apparent diffusion coefficient value on quantitative assessment yielded the most independent magnetic resonance imaging differentiators of malignant mesenchymal tumors of the uterus and T2-weighted hyperintense leiomyoma. The classification accuracy of the variant discriminant analysis based on three selected findings, i.e., a T1 bright area, computed diffusion-weighted imaging with a b-value of 2000s/mm2 (cDWI2000), and T2-hypointense bands, was 84.8% (56/66), indicating high accuracy. CONCLUSIONS: Variant discriminant analysis using the T1 bright area, cDWI2000, and T2-hypointense bands yielded high accuracy for differentiating between malignant mesenchymal tumors of the uterus and T2-weighted hyperintense leiomyoma.

Comparison of multiparametric magnetic resonance imaging sequences with laboratory parameters for prognosticating renal function in chronic kidney disease.

Magnetic resonance imaging (MRI) is playing an increasingly important role in evaluating chronic kidney disease (CKD). It has the potential to be used not only for evaluation of physiological and pathological states, but also for prediction of disease course. Although different MRI sequences have been employed in renal disease, there are few studies that have compared the different sequences. We compared several multiparametric MRI sequences, and compared their results with the estimated glomerular filtration rate. Principal component analysis showed a similarity between T1 values and tissue perfusion (arterial spin labelling), and between fractional anisotropy (diffusion tensor imaging) and apparent diffusion coefficient values (diffusion-weighted imaging). In multiple regression analysis, only T2* values, derived from the blood oxygenation level-dependent (BOLD) MRI sequence, were associated with estimated glomerular filtration rate slope after adjusting for degree of proteinuria, a classic prognostic factor for CKD. In receiver operating characteristic curve analysis, T2* values were a good predictor of rapid deterioration, regardless of the degree of proteinuria. This suggests further study of the use of BOLD-derived T2* values in the workup of CKD, especially to predict the disease course.

Signal and morphological changes in the endolymph of patients with vestibular schwannoma on non-contrast 3D FLAIR at 3 Tesla.

BACKGROUND: Non-contrast FLAIR revealed increased signal within the inner ear in patients with vestibular schwannoma, which is generally assumed to occur in the perilymph; however, the majority of previous studies did not differentiate between the endolymph and perilymph. Therefore, endolymph signal changes have not yet been investigated in detail. The purpose of the present study was three-fold: (1) to assess perilymph signal changes in patients with vestibular schwannoma on heavily T2-weighted (T2W) 3D FLAIR, also termed positive perilymphatic images (PPI), (2) to evaluate signal and morphological changes in the endolymph on PPI, and (3) to establish whether vertigo correlates with the signal intensity ratios (SIR) of the vestibular perilymph or vestibular endolymphatic hydrops. METHODS: Forty-two patients with unilateral vestibular schwannoma were retrospectively recruited. We semi-quantitatively and qualitatively evaluated the perilymph signal intensity on the affected and unaffected sides. We also quantitatively examined the signal intensity of the vestibular perilymph and assessed the relationship between vertigo and the SIR of the vestibular perilymph on the affected side. We semi-quantitatively or qualitatively evaluated the endolymph, and investigated whether vestibular hydrops correlated with vertigo. RESULTS: The perilymph on the affected side showed abnormal signal more frequently (signal intensity grade: overall mean 1.45 vs. 0.02; comparison of signal intensity: overall mean 36 vs. 0 cases) and in more parts (the entire inner ear vs. the basal turn of the cochlea and vestibule) than that on the unaffected side. No significant difference was observed in the SIR of the vestibular perilymph with and without vertigo (5.54 vs. 5.51, p = 0.18). The endolymph of the vestibule and semicircular canals showed the following characteristic features: no visualization (n = 4), signal change (n = 1), or vestibular hydrops (n = 10). A correlation was not observed between vestibular hydrops and vertigo (p = 1.000). CONCLUSIONS: PPI may provide useful information on signal and morphological changes in the endolymph of patients with vestibular schwannoma. Further research is warranted to clarify the relationship between vertigo and the MR features of the inner ear.

Application of Magnetic Resonance Imaging in the Evaluation of Nutritional Status: A Literature Review with Focus on Dialysis Patients.

Magnetic resonance imaging (MRI) is indispensable in clinical medicine for the morphological and tomographic evaluation of many parenchymal organs. With varied imaging methods, diverse biological information, such as the perfusion volume and measurements of metabolic products, can be obtained. In addition to conventional MRI for morphological assessment, diffusion-weighted MRI/diffusion tensor imaging is used to evaluate white matter structures in the brain; arterial spin labeling is used for cerebral blood flow evaluation; magnetic resonance elastography for fatty liver and cirrhosis evaluation; magnetic resonance spectroscopy for evaluation of metabolites in specific regions of the brain; and blood oxygenation level-dependent imaging for neurological exploration of eating behavior, obesity, and food perception. This range of applications will continue to expand in the future. Nutritional science is a multidisciplinary and all-inclusive field of research; therefore, there are many different applications of MRI. We present a literature review of MRI techniques that can be used to evaluate the nutritional status, particularly in patients on dialysis. We used MEDLINE as the information source, conducted a keyword search in PubMed, and found that, as a nutritional evaluation method, MRI has been used frequently to comprehensively and quantitatively evaluate muscle mass for the determination of body composition.

Intravenous enhanced 3D FLAIR imaging to identify CSF leaks in spontaneous intracranial hypotension: Comparison with MR myelography.

PURPOSE: To evaluate the clinical utility of intravenous gadolinium-enhanced heavily T2-weighted 3D fluid-attenuated inversion recovery (HT2-FLAIR) imaging for identifying spinal cerebrospinal fluid (CSF) leaks in patients with spontaneous intracranial hypotension (SIH). METHODS: Patients with SIH underwent MR myelography and post-contrast HT2-FLAIR imaging after an intravenous gadolinium injection. Two types of CSF leaks (epidural fluid collection and CSF leaks around the nerve root sleeve) at each vertebral level were compared between the 2 sequences. The total numbers of CSF leaks and vertebral levels involved were recorded for the whole spine. The sequence that was superior for the overall visualization of epidural and paraspinal fluid collection was then selected. RESULTS: Nine patients with SIH were included in the present study. HT2-FLAIR imaging was equivalent or superior to MR myelography at each level for detecting the 2 types of CSF leaks. In the 2 types of CSF leaks, the total numbers of CSF leaks and levels involved were higher on HT2-FLAIR images than on MR myelography, while no significant difference was observed for CSF leaks around the nerve root sleeve. In all 9 patients, HT2-FLAIR imaging was superior to MR myelography for the overall visualization of epidural and paraspinal fluid collection. CONCLUSION: Intravenous gadolinium-enhanced HT2-FLAIR imaging was superior to MR myelography for the visualization of CSF leaks in patients with SIH. This method can be useful for identifying spinal CSF leaks.