In this study, we present images acquired by a fast-imaging method for the evaluation of endolymphatic hydrops after intravenous administration of a single dose of gadolinium-based contrast agent. We utilized the hybrid of reversed image of MR cisternography and a positive perilymph signal by heavily T2- weighted 3D-fluid attenuated inversion recovery-multiplied by T2 (HYDROPS2-Mi2) method combined with deep learning reconstruction denoising. The scan time for the fast protocol was approximately 5 mins, which is far shorter than previously reported scan times. The fast acquisition provides similar image quality and less motion artifacts compared to the longer method.
Purpose: To compare apparent diffusion coefficients (ADCs) of bone marrow on diffusion-weighted imaging (DWI) between two fat-suppression techniques, and to evaluate the association between bone-marrow ADCs and the proton density fat fraction (PDFF).
Methods: Seventy-seven patients underwent whole-body DWI with short-inversion time inversion-recovery (STIR) (DWISTIR) and/or STIR + selective water-excitation (spectral-spatial RF [SSRF]) (DWISTIR+SSRF). ADCs of lumbar vertebrae (L3 and L4) were compared between DWISTIR and DWISTIR+SSRF, and correlated with the PDFF.
Results: Lumbar ADCs obtained by DWISTIR and DWISTIR+SSRF were significantly correlated (L3: r = 0.90, P < 0.0001, L4: r = 0.90, P < 0.0001). Lumbar ADCs (× 10-6 mm2/s) obtained by DWISTIR were significantly lower than those by DWISTIR+SSRF (L3: 479 ± 137 and 490 ± 148, P < 0.05, L4: 456 ± 114 and 471 ± 118, P < 0.005). Residual fat signals were more clearly observed on DWISTIR than on DWISTIR+SSRF. The ADCs of L3 obtained by DWISTIR and DWISTIR+SSRF exhibited significant positive correlations with the PDFF (r = 0.51, P < 0.0001, and r = 0.45, P < 0.0001, respectively), and the ADCs of L4 obtained by DWISTIR and DWISTIR+SSRF exhibited significantly positive correlations with the PDFF (r = 0.40, P < 0.0005, and r = 0.40, P < 0.0005, respectively).
Conclusion: Irrespective of different fat-suppression methods, lumbar ADCs were positively correlated with the PDFF, being inconsistent with previous studies. Lumbar ADCs obtained by DWISTIR were significantly lower than those obtained by DWISTIR+SSRF, probably due to residual fat signals on DWISTIR. However, this difference (< 4%) did not explain the positive correlation between lumbar ADC and PDFF.
Purpose: To explore the feasibility of susceptibility-weighted imaging (SWI) for evaluating renal iron overload.
Methods: Twenty-eight rabbits were randomly assigned into control (n = 14) and iron (n = 14) group. In the 0th week, the study group was injected with iron dextran. Both groups underwent SWI examination at the 0th, 8th, and 12th week. The signal intensity (SI) of cortex and medulla was assessed. Angle radian value (ARV) calculated with phase image was taken as the quantitative value for cortical and medullary iron deposition. After the 12th week, the left kidneys of rabbits were removed for pathology. The difference in the ARV among three groups was analyzed using Kruskal–Wallis test. The difference of the iron content between two groups was analyzed through independent sample t-test.
Results: In the iron group: at the 12th week, eight rabbits were found to have decreased SI of only cortex, and the other six rabbits had decreased SI of cortex and medulla by the same degree; the ARV of cortex at the 8th and 12th week was significantly higher than that of the 0th week (P < 0.05); the ARV of the six rabbits’ medulla at the 12th week was significantly higher than that of the 0th week, 8th week, and the other eight rabbits at the 12th week (P < 0.05); at the 12th week, eight rabbits (iron group) were found to have many irons only deposit in the cortex, and the others were found to have many irons deposit in both cortex and medulla; the iron content of cortex and six rabbits’ medulla in the iron group was significantly higher than that of the control (P < 0.05).
Conclusion: The ARV of SWI can be used to quantitatively assess the excess iron deposition in the kidneys. Excessive iron deposition mainly occurs in the cortex or medulla and causes their SWI SI to decrease.
Purpose: Histopathological differentiation of primary lung cancer is clinically important. We aimed to investigate whether diffusion tensor imaging (DTI) parameters of metastatic brain lesions could predict the histopathological types of the primary lung cancer.
Methods: In total, 53 patients with 98 solid metastatic brain lesions of lung cancer were included. Lung tumors were subgrouped as non-small cell carcinoma (NSCLC) (n = 34) and small cell carcinoma (SCLC) (n = 19). Apparent diffusion coefficient (ADC) and Fractional anisotropy (FA) values were calculated from solid enhanced part of the brain metastases. The association between FA and ADC values and histopathological subtype of the primary tumor was investigated.
Results: The mean ADC and FA values obtained from the solid part of the brain metastases of SCLC were significantly lower than the NSCLC metastases (P < 0.001 and P = 0.003, respectively). ROC curve analysis showed diagnostic performance for mean ADC values (AUC=0.889, P = < 0.001) and FA values (AUC = 0.677, P = 0.002). Cut-off value of > 0.909 × 10-3 mm2/s for mean ADC (Sensitivity = 80.3, Specificity = 83.8, PPV = 89.1, NPV = 72.1) and > 0.139 for FA values (Sensitivity = 80.3, Specificity = 54.1, PPV = 74.2, NPV= 62.5) revealed in differentiating NSCLC from NSCLC.
Conclusion: DTI parameters of brain metastasis can discriminate SCLC and NSCLC. ADC and FA values of metastatic brain lesions due to the lung cancer may be an important tool to differentiate histopathological subgroups. DTI may guide clinicians for the management of intracranial metastatic lesions of lung cancer.
Purpose: The purpose of the current study was to clarify the blood flow pattern in the left atrium (LA), potentially causing the formation of thrombosis after left upper lobectomy (LUL). The blood flow in the LA was evaluated and compared between LUL patients with and without thrombosis. For the evaluation, we applied highly accelerated 4D flow MRI with dual-velocity encoding (VENC) scheme, which was expected to be able to capture slow flow components in the LA accurately.
Methods: Eight volunteers and 18 patients subjected to LUL underwent dual-VENC 4D Flow MRI. Eight patients had a history of thrombosis. We measured the blood flow velocity and stasis ratio (proportion in the volume that did not exceed 10 cm/s in any cardiac phase) in the LA and left superior pulmonary vein (LSPV) stump. For visual assessment, the presence of each collision of the blood flow from pulmonary veins and vortex flow in the LA were evaluated. Each acquired value was compared between healthy participants and LUL patients, and in LUL patients with and without thrombosis.
Results: In LUL patients, blood flow velocity near the inflow part of the left superior pulmonary vein (Lt Upp) and mean velocity in the LA were lower, and stasis ratio in the LA was higher compared with healthy volunteers (Lt Upp 9.10 ± 3.09 vs.13.23 ± 14.19 cm/s, mean velocity in the LA 9.81 ± 2.49 vs. 11.40 ± 1.15 cm/s, and stasis ratio 25.28 ± 18.64 vs. 4.71 ± 3.03%, P = 0.008, 0.037, and < 0.001). There was no significant difference in any quantification values between LUL patients with and without thrombosis. For visual assessment, the thrombus formation was associated with no collision pattern (62.5% vs. 10%, P = 0.019) and not with vortex flow pattern (50% vs. 30%, P = 0.751).
Conclusion: The net blood flow velocity was not associated with the thrombus formation. In contrast, a specific blood flow pattern, the absence of blood flow collision from pulmonary veins, correlates to the thrombus formation in the LA.
Purpose: To evaluate the utility of T2-enhanced spin-echo imaging using the time-reversed gradient echo sequence (T2FFE imaging) in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI (Gd-EOB-MRI) for differentiating hemangiomas from metastatic tumors.
Methods: A total of 61 patients with 133 liver lesions, including 37 hemangiomas and 96 metastatic tumors, were scanned by Gd-EOB-MRI. Four data sets were independently analyzed by two readers: (1) 3D fat-suppressed T2-weighted imaging (FS-T2WI) alone; (2) the combination of 3D FS-T2WI and T2FFE imaging in the HBP of Gd-EOB-MRI; (3) the combination of 3D FS-T2WI, diffusion-weighted imaging (DWI) with the b-value of 1000 s/mm2 and the apparent diffusion coefficient (ADC); and (4) a dynamic study of Gd-EOB-MRI. After classifying the lesion sizes as ≤ 10 mm or > 10 mm, we conducted a receiver-operating characteristic analysis to compare diagnostic accuracies among the four data sets for differentiating hemangiomas from metastatic tumors.
Results: The areas under the curves (AUCs) of the four data sets of two readers were: (1) ≤ 10 mm (0.85 and 0.91) and > 10 mm (0.88 and 0.97), (2) ≤ 10 mm (0.94 and 0.94) and > 10 mm (0.96 and 0.95), (3) ≤ 10 mm (0.90 and 0.87) and > 10 mm (0.89 and 0.95), and (4) ≤ 10 mm (0.62 and 0.67) and > 10 mm (0.76 and 0.71), respectively. Data sets (2) and (3) showed no significant differences in AUCs, but both showed significantly higher AUCs compared to that of (4) regardless of the lesion size (P < 0.05).
Conclusion: The combination of 3D FS-T2WI and T2FFE imaging in the HBP of Gd-EOB-MRI achieved an accuracy equivalent to that of the combination of 3D FS-T2WI, DWI, and ADC and might be helpful in differentiating hemangiomas from metastatic tumors.
Purpose: To evaluate the relationship between the size of the venous structures related to the inner ear and the degree of endolymphatic hydrops (EH).
Methods: Thirty-four patients with a suspicion of EH underwent whole brain MR imaging including the inner ear. Images were obtained pre- and post-administration, and at 4 and 24 hours after the intravenous administration of a gadolinium-based contrast agent (IV-GBCA). The cross-sectional areas (CSA) of the internal jugular vein (IJV), superior petrosal sinus (SPS), and inferior petrosal sinus (IPS) were measured on the magnetization prepared rapid acquisition of gradient echo (MPRAGE) images obtained immediately after the IV-GBCA. The grade of EH was determined on the hybrid of reversed image of positive endolymph signal and native image of positive perilymph signal (HYDROPS) images obtained at 4 hours after IV-GBCA as no, mild, and significant EH according to the previously proposed grading system for the cochlea and vestibule, respectively. The ipsilateral CSA was compared between groups with each level of EH grade. P < 0.05 was considered statistically significant.
Results: There were no statistically significant differences between EH grades for the CSA of the IJV or that of the IPS in either the cochlea or the vestibule. The CSA of the SPS in the groups with significant EH was significantly smaller than that in the group with no EH, for both the cochlea (P < 0.01) and the vestibule (P < 0.05). In an ROC analysis to predict significant EH, the cut-off CSA value in the SPS was 3.905 mm2 for the cochlea (AUC: 0.8762, 95% confidence interval [CI]: 0.7952‒0.9572) and 3.805 mm2 for the vestibule (AUC: 0.7727, 95% CI: 0.6539‒0.8916).
Conclusion: In the ears with significant EH in the cochlea or vestibule, the CSA of the ipsilateral SPS was smaller than in the ears without EH.
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.
Purpose: To assess the diagnostic performance of the tumor contact length (TCL) and apparent diffusion coefficient (ADC) for predicting extraprostatic extension (EPE) of prostate cancer with capsular abutment (CA).
Methods: Ninety-three patients with biopsy-proven prostate cancer underwent 3-Tesla MRI, including diffusion-weighted imaging (b value = 0, 2000 s/mm2) and radical prostatectomy. Two experienced radiologists, blinded to the clinicopathological data, retrospectively assessed the presence of CA on T2-weighted imaging (T2WI). TCL on T2WI and ADC values were measured on detecting CA in prostate cancer. We used the receiver operating characteristic curves to assess the diagnostic performance of TCL and ADC values for predicting EPE.
Results: CA was present in 58 prostate cancers among 93 patients. The cut-off value for TCL was 6.9 mm, which yielded an area under the curve (AUC) of 0.75. This corresponded to a sensitivity, specificity, and accuracy of 84.2%, 61.5%, and 69.0%, respectively. The cut-off value for ADC was 0.63 × 10–3 mm2/s, which yielded an AUC of 0.76. This, in turn, corresponded to a sensitivity, specificity, and accuracy of 84.2%, 59.0%, and 67.2%, respectively. The combined cut-off value of TCL and ADC yielded an AUC of 0.82. The specificity (84.6%) and accuracy (81.0%) of the combined value were superior to their individual values (P < 0.05).
Conclusion: A combination of TCL and ADC values provided high specificity and accuracy for detecting EPE of prostatic cancer with CA.
Purpose: We evaluated the diagnostic performance of the texture features of dynamic contrast-enhanced (DCE) MRI for breast cancer diagnosis in which the discriminator was optimized, so that the specificity was maximized via the restriction of the negative predictive value (NPV) to greater than 98%.
Methods: Histologically proven benign and malignant mass lesions of DCE MRI were enrolled retrospectively. Training and testing sets consist of 166 masses (49 benign, 117 malignant) and 50 masses (15 benign, 35 malignant), respectively. Lesions were classified via MRI review by a radiologist into 4 shape types: smooth (S-type, 34 masses in training set and 8 masses in testing set), irregular without rim-enhancement (I-type, 60 in training and 14 in testing), irregular with rim-enhancement (R-type, 56 in training and 22 in testing), and spicula (16 in training and 6 in testing). Spicula were immediately classified as malignant. For the remaining masses, 298 texture features were calculated using a parametric map of DCE MRI in 3D mass regions. Masses were classified into malignant or benign using two thresholds on a feature pair. On the training set, several feature pairs and their thresholds were selected and optimized for each mass shape type to maximize specificity with the restriction of NPV > 98%. NPV and specificity were computed using the testing set by comparison with histopathologic results and averaged on the selected feature pairs.
Results: In the training set, 27, 12, and 15 texture feature pairs are selected for S-type, I-type, and R-type masses, respectively, and thresholds are determined. In the testing set, average NPV and specificity using the selected texture features were 99.0% and 45.2%, respectively, compared to the NPV (85.7%) and specificity (40.0%) in visually assessed MRI category-based diagnosis.
Conclusion: We, therefore, suggest that the NPV of our texture-based features method described performs similarly to or greater than the NPV of the MRI category-based diagnosis.
Purpose: This study proposes and assesses a new diffusion MRI (dMRI) technique to solve problems related to the quantification of parameter maps (apparent diffusion coefficient [ADC] or mean diffusivity [MD], fractional anisotropy [FA]) and misdrawing of fiber tractography (FT) due to cerebrospinal fluid (CSF)-partial volume effects (PVEs) for brain tissues by combining with the T2-based water suppression (T2wsup) technique.
Methods: T2wsup–diffusion-weighted imaging (DWI) images were obtained by subtracting those images from the acquired multi-b value (b) DWI images after correcting the signal intensities of multiecho time (TE) images using long TE water signal-dominant images. Quantitative parameter maps and FT were obtained from minimum data points and were compared with those using the standard (without wsup) DWI method, and partly compared with those obtained using other alternative DWI methods of applying fluid attenuation inversion recovery (FLAIR), non-b-zero (NBZ) by theoretical or noise-added simulation and MR images.
Results: In the T2wsup-dMRI method, the hyperintense artifacts due to CSF-PVEs in MRI data were dramatically suppressed even at lower b (≲ 500 s/mm2) while keeping the tissue SNR. The quantitative parameter map values became precisely close to the pure tissue values precisely even in water (CSF) PVE voxels in healthy brain tissues (T2 ≲ 100 ms). Furthermore, the fiber tracts were correctly connected, particularly at the fornix in closest contact to the CSF.
Conclusion: Solving the problem of CSF-PVE in the current dMRI technique using our proposed T2wsup-dMRI technique is easy, with higher SNR than those obtained with FLAIR or NBZ methods when applying to healthy brain tissues. The proposed T2wsup–dMRI could be useful in clinical settings, although further optimization of the pulse sequence and processing techniques and clinical assessments are required, particularly for long T2 lesions.
The volumes of intracranial tissues of 40 healthy volunteers acquired from 0.3- and 3-T scanners were compared using intraclass correlation coefficients, correlation analyses, and Bland-Altman analyses. We found high intraclass correlation coefficients, high Pearson’s correlation coefficients, and low percentage biases in all tissues and most of the brain regions, although small differences were observed in some areas. These findings may support the validity of brain volumetry with low-field magnetic resonance imaging.