Purpose: This study aimed to evaluate the feasibility of single-shot echo planar diffusion-weighted imaging with compressed SENSE (EPICS-DWI) for pancreas assessment by comparing with single-shot echo planar DWI with parallel imaging (PI-DWI).
Methods: This multicenter prospective study included 27 consecutive participants with untreated pancreatic ductal adenocarcinoma (PDAC) (15 men; mean age, 67 ± 10 years) who underwent pancreatic protocol MRI including both PI-DWI and EPICS-DWI. Two radiologists independently and randomly reviewed the high b-value DWI images and qualitatively assigned confidence scores for overall image quality, image noise, pancreas conspicuity, and PDAC conspicuity using a 5-point scale. One radiologist measured the PDAC-to-pancreas contrast-to-noise-ratio (CNR) on high b-value DWI images and the apparent diffusion coefficient (ADC) value of PDAC. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon signed-rank test.
Results: The confidence scores for overall image quality (P < 0.001 in both radiologists) and image noise (P < 0.001 in both radiologists) were higher in EPICS-DWI than in PI-DWI. The pancreas conspicuity was better in EPICS-DWI than in PI-DWI in one of the radiologists (P = 0.02 and 0.06). The PDAC conspicuity was comparable between PI-DWI and EPICS-DWI (P > 0.99 in both radiologists). The PDAC-to-pancreas CNR was higher in EPICS-DWI than in PI-DWI (P = 0.02), while the ADC value of PDAC in PI-DWI was not significantly different compared to that in EPICS-DWI (P = 0.48).
Conclusion: The image quality and PDAC-to-pancreas CNR was improved in EPICS-DWI compared to PI-DWI. However, the conspicuity and ADC value of PDAC were comparable between PI-DWI and EPICS-DWI.
Purpose: T2 values are hypothesized to be reduced where protein accumulates in the cerebrospinal fluid (CSF). We aimed to verify the accuracy of Carr-Purcell-Meiboom-Gil (CPMG) pulses and non-negative least squares (NNLS) analysis in visualizing protein concentrations by mapping the T2 values.
Methods: We first dissolved 1.2g of bovine serum albumin powder in 4 mL of artificial CSF to purify an albumin solution with a concentration of 4.5 mM. Artificial CSF was added thereto, and eight types of albumin solutions, with concentrations of 0.002-4.5 mM, were purified. We acquired this albumin solution with CPMG pulses and NNLS, decomposed the T2 values per pixel, and derived 25 T2 component values of 60-2000 ms. We assessed the change of T2 values by the difference in albumin concentration of a single voxel. Finally, we used the method to assess T2 values from two patients, one with a subdural hematoma and one with a suprasellar cystic tumor. T2 component values were plotted graphically, presented individually, and created in color maps.
Results: T2 component values for albumin concentrations ranging from 0.056 to 4.55 mM showed different T2 peaks, whereas, for concentrations 0.002 to 0.019 mM, the peaks were similar heights and overlapped. Peak width was similar for all concentrations. The color maps successfully reflected the changes in T2 values across both RGB color patterns. T2 components for albumin samples with 2.5 mM and 6.1 mM concentrations within a single voxel were represented separately and reflected the ratio of the two samples in nine different regions of interest within one slice. In the clinical cases, the T2 component map imaged differences in albumin concentrations, similar to those observed in the albumin samples.
Conclusion: The present method with CPMG sequences and NNLS provide adequate images to differentiate accumulating protein concentrations in the CSF, even at the level of a single pixel.
Purpose: To investigate the visibility of the lenticulostriate arteries (LSAs) in time-of-flight (TOF)-MR angiography (MRA) using compressed sensing (CS)-based deep learning (DL) image reconstruction by comparing its image quality with that obtained by the conventional CS algorithm.
Methods: Five healthy volunteers were included. High-resolution TOF-MRA images with the reduction (R)-factor of 1 were acquired as full-sampling data. Images with R-factors of 2, 4, and 6 were then reconstructed using CS-DL and conventional CS (the combination of CS and sensitivity conceding; CS-SENSE) reconstruction, respectively. In the quantitative assessment, the number of visible LSAs (identified by two radiologists), length of each depicted LSA (evaluated by one radiological technologist), and normalized mean squared error (NMSE) value were assessed. In the qualitative assessment, the overall image quality and the visibility of the peripheral LSA were visually evaluated by two radiologists.
Results: In the quantitative assessment of the DL-CS images, the number of visible LSAs was significantly higher than those obtained with CS-SENSE in the R-factors of 4 and 6 (Reader 1) and in the R-factor of 6 (Reader 2). The length of the depicted LSAs in the DL-CS images was significantly longer in the R-factor 6 compared to the CS-SENSE result. The NMSE value in CS-DL was significantly lower than in CS-SENSE for R-factors of 4 and 6. In the qualitative assessment of DL-CS images, the overall image quality was significantly higher than that obtained with CS-SENSE in the R-factors 4 and 6 (Reader 1) and in the R-factor 4 (Reader 2). The visibility of the peripheral LSA was significantly higher than that shown by CS-SENSE in all R-factors (Reader 1) and in the R-factors 2 and 4 (Reader 2).
Conclusion: CS-DL reconstruction demonstrated preserved image quality for the depiction of LSAs compared to the conventional CS-SENSE when the R-factor is elevated.
Purpose: The ocular and brain glymphatic systems may share common physiological pathways. We hypothesized that the anteroposterior movement of gadolinium-based contrast agent (GBCA) that has leaked into the vitreous could serve as a biomarker for brain glymphatic function. This study aimed to retrospectively investigate the association between the intravitreal GBCA distribution on MRI and recently proposed imaging markers of impaired brain waste clearance.
Methods: We analyzed 156 eyes from 78 adult participants who underwent 3T MRI 4 hr after standard-dose GBCA administration. On 3D-real IR images, we calculated a "contrast shift index" (the signal difference between anterior and posterior vitreous volumes of interest: VOIa-VOIp) to quantify the anteroposterior GBCA distribution. The primary outcome was a composite endpoint of positivity for either putative meningeal lymphatics at the posterior sigmoid sinus (PML-PSS) or enhanced basal ganglia perivascular spaces (PVS-BG). Multivariable logistic regression with cluster-robust inference was used to assess predictors, including the contrast shift index, mean vitreous contrast distribution, age, sex, and axial length of the eye.
Results: A positive contrast shift index, indicating preferential anterior GBCA distribution, was significantly and independently associated with the composite outcome of impaired brain clearance (P = 0.006). Age (P <0.001) and male sex (P = 0.009) were also independent predictors. A predictive model incorporating these factors demonstrated high discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.872. Axial length of the eye and mean vitreous contrast distribution were not significant independent predictors.
Conclusion: The anteroposterior distribution of GBCA in the vitreous is a novel, non-invasive imaging biomarker associated with impaired brain clearance function. This "contrast shift index" may reflect systemic glymphatic dysregulation common to both the eye and brain, offering a new avenue for assessing neurodegenerative risk.
Purpose: To evaluate the clinical value of early renal changes in type 2 diabetes mellitus (T2DM) using multiparameter MRI.
Methods: The study included 41 diabetics (normoalbuminuria: n = 23; microalbuminuria: n = 18) and 30 healthy controls. All subjects underwent intravoxel incoherent motion diffusion-weighted imaging (IVIM), blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) examinations. One-way analysis of variance was used to compare MRI parameters among the three groups. Pearson correlation analysis was used to evaluate the relationship between MRI parameters and estimated glomerular filtration rate (eGFR) and albumin-creatinine ratio (ACR). Receiver operating characteristic analysis was performed to assess the diagnostic performance.
Results: There were statistical differences in cortical D, D*, f, renal blood flow (RBF) and medulla D, D*, f, R2* among the three groups (P < 0.05). The cortical or medullary D, cortical f, and RBF were significantly positively correlated with eGFR (all P < 0.01). The cortical or medullary D, D*, f, cortical RBF were negatively correlated with ACR (all P < 0.05).To evaluate early kidney changes and degree of diabetes, cortical combined D and RBF (AUC [area under the curve] = 0.796 and 0.947, respectively) was better than single D or RBF (all P > 0.05); medullary combined D and R2* (AUC = 0.899 and 0.923, respectively) was better than single D or R2* (all P > 0.05), except single D (P = 0.005) in differentiating normoalbuminuria group from control group.
Conclusion: The early changes of renal diffusion and perfusion, oxygenation level, and blood flow in T2DM could be evaluated noninvasively and quantitatively using IVIM, BOLD and ASL. Renal medullary combined IVIM-derived D and BOLD-derived R2* and cortical combined IVIM-derived D and ASL-derived RBF were better for evaluating early renal changes in T2DM.
Purpose: This study aimed to compare MRI findings among benign, borderline, and malignant ovarian seromucinous neoplasms.
Methods: We retrospectively analyzed MRI data from 24 patients with ovarian seromucinous neoplasms-seven benign, thirteen borderline, and six malignant. The parameters evaluated included age, tumour size, morphology, number, height, apparent diffusion coefficient (ADC) values, T2 ratios, time-intensity curve (TIC) descriptors, and TIC patterns of the mural nodules. Additionally, we examined the T2 and T1 ratios of the cyst contents, tumour markers, and the presence of endometriosis. We used statistical tests, including the Kruskal-Wallis and Fisher-Freeman-Halton exact tests, to compare these parameters among the three aforementioned groups.
Results: The cases showed papillary architecture with internal branching in 57% of benign, 92% of borderline, and 17% of malignant cases. Three or fewer mural nodules were seen in 57% of benign, 8% of borderline, and 17% of malignant cases. Compared to benign and borderline tumours, mural nodules of malignant neoplasms had significantly increased height (P = 0.015 and 0.011, respectively), lower means ADC values (P = 0.003 and 0.035, respectively). The mural nodules in malignant cases also demonstrated significantly lower T2 ratios than those in the benign cases (P = 0.045). Most neoplasms displayed an intermediate-risk TIC pattern, including 80% benign, 83% borderline, and 60% malignant neoplasms, and no significant differences were observed.
Conclusion: Most benign and borderline tumours exhibited a papillary architecture with an internal branching pattern, whereas this feature was less common in malignant neoplasms. Additionally, benign tumours had fewer mural nodules compared to borderline tumours. Malignant neoplasms were characterized by mural nodules with increased height and lower ADC values than those in benign and borderline tumours. Interestingly, all three groups predominantly exhibited an intermediate-risk TIC pattern, emphasizing the complexity of diagnosing seromucinous neoplasms using MRI.
Purpose: To assess right heart diastolic energy loss (EL) as a cardiac workload and evaluate its association with major cardiac events (MACE) in adult patients with pulmonary atresia with an intact ventricular septum (PAIVS).
Methods: We retrospectively enrolled and compared 30 consecutive adult patients (18 with PAIVS and 12 with pulmonary stenosis [PS] as controls) who underwent right ventricular (RV) outflow tract reconstruction and 4D flow MRI. EL, conventional parameters on MRI, and the severity of tricuspid regurgitation (TR) on echocardiography were assessed. We also evaluated the association between MACE including arrhythmias, heart failure, surgical intervention, and imaging parameters in adults with PAIVS.
Results: Patients with PAIVS were younger, had a higher diastolic EL/cardiac output (CO) ratio, and had a more significant TR than those with PS (controls). However, RV volume, ejection fraction (EF), and pulmonary regurgitation (PR) severity did not differ between the two groups. Higher RV end-diastolic pressure (EDP) and lower cardiac index (CI) correlated with the diastolic EL/CO in patients with PAIVS. Univariate logistic analysis demonstrated that older age and a higher diastolic EL/CO ratio were important factors for MACE in adults with PAIVS (P = 0.048, 0.049).
Conclusion: A higher diastolic EL/CO ratio was associated with a higher RV EDP and lower CI. A high diastolic EL/CO ratio is also associated with MACE in adults with PAIVS. Even in adults with normal RV volume and EF, the right heart EL was elevated, suggesting an excessive right-sided cardiac workload that integrated both afterload and preload beyond the RV size in adult patients with PAIVS.
Purpose: To assess the utility of apparent diffusion coefficient maps (ADC) for diagnosing myometrial invasion (MI) in endometrial cancer (EC).
Methods: This retrospective study included 164 patients (mean age, 56 years; range, 25-89 years) who underwent preoperative MRI for EC with <1/2 MI or no MI between April 2016 and July 2023. Five sequences were evaluated: T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), ADC, dynamic contrast-enhanced T1-weighted imaging (DCE-T1WI), and contrast-enhanced T1WI (CE-T1WI). Three experienced radiologists independently assessed the sequences for MI. For ADC, MI was determined if the endometrial-myometrial junction-tumor boundary had disappeared. Additionally, the assessment of MI was performed using the combination of T2WI, DWI, and ADC, as well as T2WI, DCE-T1WI, and CE-T1WI. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for the presence of MI were calculated and compared between the sequences and combinations. Inter-reader agreement was assessed using kappa (κ) statistics.
Results: The sensitivity of ADC was significantly higher than T2WI (P < 0.001) and DCE-T1WI (P = 0.018) for one reader and significantly higher than CE-T1WI (P = 0.045 and 0.043) for two readers. The specificity of ADC was significantly lower than T2WI (P = 0.015 and < 0.001) and CE-T1WI (P = 0.031 and 0.01) for two readers and significantly lower than DCE-T1WI (P = 0.031) for one reader. The AUC of ADC was significantly higher than T2WI (P = 0.048) and DCE-T1WI (P = 0.049) for one reader. The combination including ADC showed higher positive predictive value for all three readers compared to any sequence or combination including contrast enhancement. Additionally, ADC demonstrated the highest agreement rates.
Conclusion: ADC had high sensitivity for MI and the highest agreement rate among all sequences. Thus, this sequence, combined with other sequences, can be crucial for a comprehensive evaluation of MI.
Purpose: To develop a new method to generate synthetic MR spectroscopic imaging (MRSI) data for training machine learning models.
Methods: This study targeted routine MRI examination protocols with single voxel spectroscopy (SVS). A novel model derived from pix2pix generative adversarial networks was proposed to generate synthetic MRSI data using MRI and SVS data as inputs. T1- and T2-weighted, SVS, and reference MRSI data were acquired from healthy brains with clinically available sequences. The proposed model was trained to generate synthetic MRSI data. Quantitative evaluation involved the calculation of the mean squared error (MSE) against the reference and metabolite ratio value. The effect of the location of and the number of the SVS data on the quality of the synthetic MRSI data was investigated using the MSE.
Results: The synthetic MRSI data generated from the proposed model were visually closer to the reference. The 95% confidence interval (CI) of the metabolite ratio value of synthetic MRSI data overlapped with the reference for seven of eight metabolite ratios. The MSEs tended to be lower in the same location than in different locations. The MSEs among groups of numbers of SVS data were not significantly different.
Conclusion: A new method was developed to generate MRSI data by integrating MRI and SVS data. Our method can potentially increase the volume of MRSI data training for other machine learning models by adding SVS acquisition to routine MRI examinations.
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