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Background: Early detection of nasopharyngeal carcinoma (NPC) patients who are not sensitive to neoadjuvant chemotherapy (NAC) can guard against overtreatment. This study aimed to evaluate the effectiveness of amide proton transfer (APT) imaging and diffusion-weighted imaging (DWI) in predicting the early response to NAC in patients with NPC. Methods: This prospective study enrolled fifty patients with biopsy-confirmed NPC from September 2021 to May 2023. Magnetic resonance imaging (MRI) including APT and DWI, was performed before NAC. After NAC, patients were divided into complete response (CR), partial response (PR), and stable disease (SD) and progressive disease (PD) groups based on the Response Evaluation Criteria in Solid Tumours Version 1.1. The Kruskal-Wallis H test was used for statistical analysis. The differences in APT and apparent diffusion coefficient (ADC) values among the different efficacy groups were compared, the receiver operating characteristic (ROC) curve was drawn for statistically significant parameters, and the area under the curve (AUC) was calculated. Results: Fifty patients (mean age: 47±14 years; 42 males and 8 females) were included in the final analysis (11 were in the CR group, 30 in the PR group, 9 in the SD group, and 0 in the PD group). The ADC values showed no significant differences among the different treatment response groups. The SD group showed significantly lower APTmax (P=0.025), APTskewness (P=0.025) and APT90% (P=0.001) values than the CR and PR groups. Setting APT90% =3.10% as the cut-off value, optimal diagnostic performance (AUC: 0.831; sensitivity: 0.778; specificity: 0.878) was obtained in predicting the SD group. Conclusions: APT imaging can predict the early tumour response to NAC in patients with NPC. APT imaging may be superior to DWI in predicting tumour response.
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Background: Diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (ssEPI) is a valuable tool for detecting acute brain lesions but does suffer from image distortions. Multishot echo-planar imaging (msEPI) is a technique for reducing such distortions. This study aimed to compare the image quality and diagnostic efficacy of ssEPI- and msEPI-DWI at 5.0 T for brain disease detection. Methods: This study retrospectively reviewed images of 107 consecutive patients with suspected brain diseases who underwent ssEPI- and msEPI-DWI at 5.0 T at the First Affiliated Hospital of University of Science and Technology of China from August 2023 to September 2023. Two radiologists independently graded image quality and measured the image distortion. Signal-to-noise ratio, contrast-to-noise ratio, and apparent diffusion coefficient (ADC) were calculated and compared between ssEPI- and msEPI-DWI. Image quality scores were compared using the Wilcoxon test and other continuous variables by the paired t-test. The diagnostic accuracy of ADC values in distinguishing lesions from normal-appearing tissues was measured with the area under the curve (AUC). Results: Image quality evaluation and distortion analysis revealed that msEPI-DWI significantly outperformed ssEPI-DWI (two-sided P<0.001). No significant difference was observed in signal-to-noise ratio, contrast-to-noise ratio, or ADC values between msEPI- and ssEPI-DWI (two-sided P≥0.601). The ADC values of msEPI- and ssEPI-DWI showed strong correlations for both lesions (r=0.97) and contralateral normal tissues (r=0.91) (two-sided P<0.001). Compared to those of the contralateral white matter, ADC values of low-grade gliomas (LGGs) were significantly higher [ssEPI-DWI: 1,119.9±273.1 vs. 805.1±73.9; msEPI-DWI: 1,196.2±355.6 vs. 757.3±98.0 (unit: ×10-6 mm2/s)], while the ADC values of acute cerebral infarction (ACI) lesions were significantly lower [ssEPI-DWI: 603.9±273.2 vs. 888.9±212.0; msEPI-DWI: 538.0±281.2 vs. 905.0±188.9 (unit: ×10-6 mm2/s)] (two-sided P≤0.003). The AUCs for detecting LGGs were excellent for both ssEPI-DWI [AUC =0.934; 95% confidence interval (CI): 0.84-1.00] and msEPI-DWI (AUC =0.944; 95% CI: 0.86-1.00) (two-sided P<0.001; two-sided DeLong test: P=0.833). Conclusions: As compared to ssEPI-DWI, msEPI-DWI, when performed at 5.0 T, demonstrated superior image quality and less anatomical distortion in a wide spectrum of brain diseases and showed promising diagnostic performance for LGGs and ACI. In the future, msEPI-DWI at 5.0 T could become clinically routine in the diagnosis and grading of brain disorders.
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Background: Kirsten rat sarcoma (KRAS) mutation drives resistance to anti-epidermal growth factor receptor (anti-EGFR)-targeted therapies in rectal cancer. Amide proton transfer-weighted magnetic resonance imaging (APTw MRI) might be a supplement to the evaluation of KRAS mutation because the APTw value can reflect mobile cellular protein content in vivo. This study aimed to determine whether APTw MRI could predict KRAS mutation in rectal cancer and compare this technique with diffusion-weighted imaging (DWI). Methods: This retrospective study reviewed 153 consecutive patients with rectal cancer from April 2019 to June 2021 in our hospital. Among them, a total of 55 patients who did not undergo neoadjuvant chemoradiotherapy and underwent preoperative APTw MRI, DWI, and postoperative KRAS tests were included in this study. In two-dimensional APTw images, two radiologists manually delineated three regions of interest (ROIs) along tumor contour in the largest slice and the adjacent two slices of tumor respectively. The mean APTw value within a ROI was calculated, and the values of three ROIs were averaged for each patient. In consecutive DWI images, two radiologists depicted the ROIs of the whole lesion, and the mean apparent diffusion coefficient (ADC) was generated. The intraclass correlation coefficient (ICC), Shapiro-Wilk test and Student's t-test were used for statistical analyses. Receiver operating characteristic (ROC) curves were constructed for APTw and ADC values respectively, and the area under the curve (AUC) was used to evaluate the diagnostic performance for the prediction of KRAS mutation. Results: Among these 55 patients, KRAS mutation occurred in 21 patients. The ICCs of two independent raters for APTw and ADC values were 0.937 [95% confidence interval (CI), 0.914-0.953] and 0.976 (95% CI, 0.959-0.986), respectively. ADC values did not show a statistically significant difference between the KRAS-mutant group and the wild type (WT) group (P=0.733). KRAS-mutant tumors exhibited a higher APTw value than WT tumors in patients with rectal non-mucinous adenocarcinoma (3.324%±0.685% vs. 2.230%±0.833%, P<0.001). The AUC of the APTw value was 0.827 (95% CI, 0.701-0.916), with a cutoff value of 2.4% (sensitivity, 95.2%; specificity, 55.9%). Conclusions: DWI cannot differentiate mutant KRAS genes from WT genes in patients with rectal cancer, but APTw MRI has potential for evaluating KRAS mutation in rectal cancer. The APTw value had moderate diagnostic performance in the prediction of KRAS mutation with a high sensitivity but a low specificity. APTw MRI might be a promising supplement to KRAS genomic analysis in rectal cancer patients.
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Background Prostate disorders, including benign enlargement and malignancy, are commonly evaluated through imaging techniques. Historically, transrectal ultrasound (TRUS) has been used for prostate imaging and biopsy. However, multiparametric MRI (mpMRI), which integrates structural and functional imaging methods, offers enhanced diagnostic capabilities. This study evaluates the effectiveness of mpMRI, including its grading via Prostate Imaging - Reporting and Data System (PI-RADS) or Likert scoring, in distinguishing between benign and malignant prostatic conditions and compares these findings with TRUS outcomes. Methodology This prospective study enrolled 30 male patients aged 45 to 75 years (mean age 60 years), selected based on prostatic abnormalities, elevated prostate-specific antigen (PSA) levels (>4 ng/dL), or palpable nodules detected via digital rectal examination. MRI, including PI-RADS or Likert scoring, was utilized to assess prostatic lesions, and results were compared with histopathological data obtained from TRUS-guided biopsies. Results Among the 30 patients, common symptoms included urinary retention (60%) and painful urination (53.3%). Malignant tumors were diagnosed in 12 patients (40%). MRI identified eight cases with enlarged transitional zones and irregular signals in peripheral zones (benign prostatic hyperplasia with tumor) and four cases with irregular signals in both zones (sarcoma). Concordance between MRI T2-weighted (T2W) observations and biopsy results showed 60% malignancy detection. Sensitivity assessments revealed MRI detected 15 true-positives (50%), TRUS detected six true positives (20%), and multivoxel spectroscopic analysis (MVS) identified 14 true-positives (46.7%). PI-RADS or Likert scoring of mpMRI was correlated with TRUS outcomes, highlighting its enhanced diagnostic accuracy compared to TRUS alone. Conclusion While TRUS remains a standard diagnostic tool, it is limited by significant sampling errors and complications. The integration of mpMRI, with its grading system, significantly improves diagnostic accuracy and treatment planning. Although mpMRI alone has limitations, its combination with contrast-enhanced MRI, diffusion-weighted imaging, and MR spectroscopy offers a comprehensive approach to enhanced prostate cancer detection.
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Diffusion-weighted imaging (DWI) is a technique used to probe the random microscopic motion of water protons in living tissue, represented by a parameter measurement of apparent diffusion coefficient (ADC) values. This study aimed to measure the ADC values of various fetal organs and placenta using 3T at various gestational ages. This was a prospective observational study. A total of 103 singleton pregnancies from 20 to 38 weeks of gestational age were included. Diffusion-weighted imaging was performed in the axial plane from the fetal head to the trunk with the following parameters: TR: 2000-2500 ms; TE: 88 ms; FOV: 250 mm; 256 matrix; slice thickness: 4 mm with a 0 mm gap; acquisition time: 1 min, 18 s. Diffusion gradient values were b = 0 and b = 700 s/mm2. ADC was measured in fetal brain regions (frontal white matter, occipital white matter, centrum semiovale, pons, thalamus, cerebellum, and fetal organs (lungs, kidney, and placenta). ANOVA was used to calculate the mean ADC values. Karl Pearson's coefficient of correlation was used to evaluate the correlation between ADC values and increasing gestational age. The mean ADC values of brain regions were: frontal white matter (1.64 ± 0.08 × 10- 3 mm2 /s, F-39.10,p-<0.001), occipital white matter (1.64 ± 0.06 × 10- 3 mm2/s, F-26.14, p-<0.001), centrum semiovale (1.62 ± 0.03 × 10- 3 mm2/s, F-49.88,p-<0.001, pons (1.23 ± 0.09 × 10- 3 mm2/s F-9.14,p-<0.001) ), Thalamus (1.21 ± 0.07 × 10- 3 mm2/s, F-13.54,p-<0.001) and cerebellum (1.36 ± 0.10 × 10- 3 mm2 /s, F-4.19,p-<0.001). The mean ADC values of fetal organs were lung (1.92 ± 0.15 × 10- 3 mm2 /s, F-28.24, p-<0.001), kidney (1.34 ± 0.11 × 10- 3 mm2 /s, F-1.05, p- 0.37) and placenta (1.94 ± 0.11 × 10- 3 mm2 /s, F-160.33, p-<0.001). White-matter regions showed a significant positive correlation with increasing gestational age. Statistically, a negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney. This will be one of the first few studies to provide the ADC values of the fetal brain and fetal organs using 3T MRI. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially lead to a biomarker for predicting the functionality of the fetal organs in abnormalities.
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Imagen de Difusión por Resonancia Magnética , Feto , Edad Gestacional , Placenta , Humanos , Femenino , Embarazo , Placenta/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética/métodos , Adulto , Feto/diagnóstico por imagen , Estudios Prospectivos , Encéfalo/diagnóstico por imagen , Encéfalo/embriología , Riñón/diagnóstico por imagen , Riñón/embriología , Pulmón/diagnóstico por imagen , Pulmón/embriologíaRESUMEN
Background: In liver diffusion-weighted imaging (DWI), single-shot echo-planar imaging (SS-EPI) sequences are susceptible to motion artifacts, resulting in image blurring and decreased lesion detection rates. This study aimed to develop and optimize a motion-corrected (MOCO) technique for liver DWI at 3 Tesla (3T). The technique incorporates motion correction, complex averaging, and a combination of a reparametrized sinc fatsat pulse with an optimized water excitation pulse. Methods: This prospective cross-sectional study performed at Fujian Medical University Union Hospital included 42 healthy volunteers who underwent four SS-EPI DWI sequences on a 3T magnetic resonance imaging (MRI) system between January 2023 and March 2023. The sequences included a navigator-triggered (NT) MOCO-DWI, two free-breathing (FB) MOCO-DWI, and an FB conventional DWI (FB cDWI) sequence. Motion correction and complex averaging were performed for both MOCO-DWI sequences, and fat suppression was achieved using either a sinc fatsat pulse with optimized water excitation or a conventional spectral attenuated inversion recovery (SPAIR) pulse. Liver signal-to-noise ratio (SNR) was measured at b=1,000 s/mm2. Qualitative parameters were independently evaluated by three radiologists using 5-point Likert scales. Quantitative parameters were assessed using the Kolmogorov-Smirnov test, and variance homogeneity was assessed using Levene's test. Regarding the qualitative analysis, the Friedman test was used to compare subjective scores among the four techniques. Results: The SNRs of the liver were significantly higher with FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). In the superior-inferior direction, the SNRs of the inferior level of the liver were higher than those of the superior level in NT MOCO-DWI. The qualitative results showed significantly higher ratings for NT MOCO-DWI and FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). Regarding the apparent diffusion coefficient (ADC) quantification, the ADC values of the left lobe were higher than those of the right lobe in all four techniques. Conclusions: The proposed EPI DWI technique, incorporating motion correction, complex averaging, and a modified fat suppression scheme using spectral fat saturation and binomial water excitation, was found to be clinically feasible for liver MRI. The FB MOCO-DWI sequence, with its superior SNR and excellent image quality, is recommended for liver DW imaging at 3T in clinical routine.
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Background: Simultaneous multislice (SMS) technology improves acquisition efficiency of diffusion-weighted imaging (DWI). This study aimed to evaluate the performance of SMS-DWI in image quality and apparent diffusion coefficient (ADC) measurements for focal liver lesions (FLLs) as compared with that of conventional DWI (CON-DWI). Methods: The institutional ethics committee of West China Hospital, Sichuan University approved this single-center, prospective study conducted from February 2021 to March 2022. Free-breathing SMS-DWI and CON-DWI examinations were acquired on a 3-T scanner with b-values of 50, 400, and 800 s/mm2. Qualitative image quality and quantitative measurements of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC were compared between SMS-DWI and CON-DWI. The ADC values for FLLs were further compared between SMS-DWI and CON-DWI in different patient subgroups. The intra- and interreader agreements were assessed. Significance was set at P<0.05. Results: This study included 116 patients (96 males, 20 females; mean age 52.0±10.7 years) with 119 FLLs. No significant differences were observed between SMS-DWI and CON-DWI regarding overall image quality in any b-value DWIs, and there were also no differences observed between SMS-DWI and CON-DWI (b=800 s/mm2) for either SNR or CNR (both P values >0.05). ADC values obtained from CON-DWI were higher than those from SMS-DWI in all FLLs [(1.31±0.47)×10-3 vs. (1.26±0.46)×10-3 mm2/s; P=0.004], and similar findings were observed across the different patient subgroups. The consistency analysis showed intrareader intraclass correlation coefficient (ICC) values of 0.792-0.944 and interreader ICC values of 0.758-0.861 for quantitative measurements (SNR, CNR, and ADC) and kappa values of 0.609-0.878 for qualitative image quality. Conclusions: SMS-DWI achieved a 37% reduction in scan time compared to CON-DWI while maintaining comparable overall image quality. Notably, the ADC values for FLLs were observed to be quantitatively lower with SMS-DWI.
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Background: Single diffusion encoding is a widely used, noninvasive technique for probing the tissue microstructure in breast tumors. However, it does not provide detailed information about the microenvironmental complexity. This study investigated the clinical utility of tensor-valued diffusion encoding for evaluating microstructural changes in breast cancer after neoadjuvant chemotherapy (NAC). Methods: We retrospectively included patients underwent chemotherapy for histologically proven invasive breast cancer between July 2020 and June 2023 and monitored the tumor response with breast magnetic resonance imaging (MRI), including tensor-valued diffusion encoding. We reviewed pre- and post-NAC MRIs regarding chemotherapy in 23 breast cancers. Q-space trajectory imaging (QTI) parameters were estimated at each time-point, and were compared with histopathological parameters. Results: The mean total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), and microscopic fractional anisotropy (µFA) were significantly decreased on post-NAC MRI compared with pre-NAC MRI, with the large effect size (ES) in MKA and µFA (0.81±0.41 vs. 0.99±0.33, ES: 0.48, P=0.03; 0.48±0.30 vs. 0.73±0.27, ES: 0.88, P<0.001; 0.58±0.14 vs. 0.68±0.11, ES: 0.79, P=0.003; respectively). Regarding prognostic factors, tumors with high Ki-67 expression showed significantly lower pre-NAC mean diffusivity (MD) and higher pre-NAC µFA compared to tumors with low Ki-67 expression (0.98±0.09 vs. 1.25±0.20, P=0.002; and 0.72±0.07 vs. 0.57±0.10, P=0.005; respectively). And negative progesterone receptor (PR) group revealed significantly lower MKT, MKA, and isotropic mean kurtosis than positive PR group on the post-NAC MRI (0.60±0.31 vs. 1.03±0.40, P=0.008; 0.36±0.21 vs. 0.61±0.33, P=0.04; and 0.23±0.17 vs. 0.42±0.25, P=0.046; respectively). Conclusions: QTI parameters reflected the microstructural changes in breast cancer treated with NAC and can be used as noninvasive imaging biomarkers correlated with prognostic factors.
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Purpose: Sex-based differences in lumbar spine's fat content in adults are minimal, but significant variations exist in diffusion-weighted imaging (DWI) signal characteristics. This study aimed to investigate fat content's impact on DWI performance in lumbar spine and potential sex differences. Methods: A retrospective analysis was conducted on upper abdominal MRI examinations in asymptomatic adult. The lumbar 1 vertebral apparent diffusion coefficient (ADC) values and fat fraction were measured. Using DWI images (b = 800â¯s/mm2), the lumbar 1 vertebral signal was categorized into high and iso-low signal groups. A univariate and multivariate analysis was conducted to investigate the influence of fat fraction on DWI performance. Finally, the participants were divided into three groups to analyze sex differences in the effect of fat content on DWI performance. Results: 202 subjects, 99 men were included. Fat content significantly influenced lumbar spine DWI signal in both sexes (p < 0.05). The effect on ADC values was significant only in women (p < 0.001). Women demonstrated a significantly higher proportion of high DWI signal than men in the low (p = 0.002) and middle (p = 0.012) fat content groups. Additionally, women had higher ADC values in the low fat group (p = 0.004) but lower values in the high fat group (p = 0.004). Conclusion: Fat content significantly impacts the DWI signal of lumbar spine, with a slight sex difference observed. These sex differences suggest that DWI signals may provide valuable information about the bone marrow beyond fat content.
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Conventional diffusion-weighted imaging (DWI) sequences employing a spin echo or stimulated echo sensitize diffusion with a specific b-value at a fixed diffusion direction and diffusion time (Δ). To compute apparent diffusion coefficient (ADC) and other diffusion parameters, the sequence needs to be repeated multiple times by varying the b-value and/or gradient direction. In this study, we developed a single-shot multi-b-value (SSMb) diffusion MRI technique, which combines a spin echo and a train of stimulated echoes produced with variable flip angles. The method involves a pair of 90° radio frequency (RF) pulses that straddle a diffusion gradient lobe (GD), to rephase the magnetization in the transverse plane, producing a diffusion-weighted spin echo acquired by the first echo-planar imaging (EPI) readout train. The magnetization stored along the longitudinal axis is successively re-excited by a series of n variable-flip-angle pulses, each followed by a diffusion gradient lobe GD and a subsequent EPI readout train to sample n stimulated-echo signals. As such, (n + 1) diffusion-weighted images, each with a distinct b-value, are acquired in a single shot. The SSMb sequence was demonstrated on a diffusion phantom and healthy human brain to produce diffusion-weighted images, which were quantitative analyzed using a mono-exponential model. In the phantom experiment, SSMb provided similar ADC values to those from a commercial spin-echo EPI (SE-EPI) sequence (r = 0.999). In the human brain experiment, SSMb enabled a fourfold scan time reduction and yielded slightly lower ADC values (0.83 ± 0.26 µm2/ms) than SE-EPI (0.88 ± 0.29 µm2/ms) in all voxels excluding cerebrospinal fluid, likely due to the influence of varying diffusion times. The feasibility of using SSMb to acquire multiple images in a single shot for intravoxel incoherent motion (IVIM) analysis was also demonstrated. In conclusion, despite a relatively low signal-to-noise ratio, the proposed SSMb technique can substantially increase the data acquisition efficiency in DWI studies.
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Background: Preoperative grading gliomas is essential for therapeutic clinical decision-making. Current non-invasive imaging modality for glioma grading were primarily focused on magnetic resonance imaging (MRI) or positron emission tomography (PET) of the tumor region. However, these methods overlook the peritumoral region (PTR) of tumor and cannot take full advantage of the biological information derived from hybrid-imaging. Therefore, we aimed to combine multiparameter from hybrid 18F-fluorodeoxyglucose (18F-FDG) PET/MRI of the solid component and PTR were combined for differentiating high-grade glioma (HGG) from low-grade glioma (LGG). Methods: A total of 76 patients with pathologically confirmed glioma (41 HGG and 35 LGG) who underwent simultaneous 18F-FDG PET, arterial spin labelling (ASL), and diffusion-weighted imaging (DWI) with hybrid PET/MRI were retrospectively enrolled. The relative maximum standardized uptake value (rSUVmax), relative cerebral blood flow (rCBF), and relative minimum apparent diffusion coefficient (rADCmin) for the solid component and PTR at different distances outside tumoral border were compared. Receiver operating characteristic (ROC) curves were applied to assess the grading performance. A nomogram for HGG prediction was constructed. Results: HGGs displayed higher rSUVmax and rCBF but lower rADCmin in the solid component and 5 mm-adjacent PTR, lower rADCmin in 10 mm-adjacent PTR, and higher rCBF in 15- and 20-mm-adjacent PTR. rSUVmax in solid component performed best [area under the curve (AUC) =0.865] as a single parameter for grading. Combination of rSUVmax in the solid component and adjacent 20 mm performed better (AUC =0.881). Integration of all 3 indicators in the solid component and adjacent 20 mm performed the best (AUC =0.928). The nomogram including rSUVmax, rCBF, and rADCmin in the solid component and 5-mm-adjacent PTR predicted HGG with a concordance index (C-index) of 0.906. Conclusions: Multiparametric 18F-FDG PET/MRI from the solid component and PTR performed excellently in differentiating HGGs from LGGs. It can be used as a non-invasive and effective tool for preoperative grade stratification of patients with glioma, and can be considered in clinical practice.
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Sporadic Creutzfeldt-Jakob disease (sCJD) is a rare and fatal neurodegenerative disorder belonging to a group of diseases known as prion disease. Characterized by the formation of abnormal prion proteins in the brain, these conditions lead to tissue damage and vacuolation, giving the brain a sponge-like appearance. sCJD represents the most prevalent form of CJD, accounting for roughly 85% of all CJD cases. We report a case with unusual clinical manifestations. The patient experienced progressive neurological symptoms and MRI progression.
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INTRODUCTION: Diffusion-weighted imaging (DWI) with radial acquisition regime (RADAR; RADAR-DWI) is a fast spin echo (FSE)-based DWI imaging technique that is known to be robust to magnetic susceptibility artifacts and distortions as compared with echo planar imaging DWI (EPI-DWI). Several reports have suggested that the apparent diffusion coefficient (ADC) values obtained with FSE-based DWI are different from those obtained with EPI-DWI. The purpose of this study was to create phantoms that mimic the T2 and ADC values of various tissues and to demonstrate the ADC values obtained with RADAR-DWI and EPI-DWI in low-field magnetic resonance imaging (MRI) systems. METHODS: Several phantoms were created using sucrose and manganese (II) chloride tetrahydrate mimicking various tissues. RADAR-DWI and EPI-DWI were used to scan the phantoms, and the obtained ADC values were compared. RESULTS: The ADC values obtained with RADAR-DWI were significantly higher than those obtained with EPI-DWI for all phantoms (P < 0.05). The ADC values obtained by RADAR-DWI ranged from 0.70 ± 0.01 to 1.21 ± 0.02 ( × 10-3mm2s-1). Meanwhile, the ADC values obtained with EPI-DWI ranged from 0.59 ± 0.01 to 1.08 ± 0.05 ( × 10-3mm2s-1). CONCLUSIONS: We created phantoms mimicking T2 and ADC values of various tissues and demonstrated the differences in ADC values obtained with RADAR-DWI and EPI-DWI using low-field MRI systems. IMPLICATIONS FOR PRACTICE: ADC values obtained by RADAR-DWI are significantly higher than those obtained by EPI-DWI, with different cutoff values for various tumor malignancies between them.
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Imagen de Difusión por Resonancia Magnética , Imagen Eco-Planar , Fantasmas de Imagen , Imagen Eco-Planar/métodos , Imagen de Difusión por Resonancia Magnética/métodos , HumanosRESUMEN
Background: An accurate and noninvasive method to determine the preoperative clear-cell renal cell carcinoma (ccRCC) pathological grade is of great significance for surgical program selection and prognosis assessment. Previous studies have shown that diffusion-weighted imaging (DWI) has moderate value in grading ccRCC. But DWI cannot reflect the diffusion of tissue accurately because it is calculated using a monoexponential model. Intravoxel incoherent motion (IVIM) is the biexponential model of DWI. Only a few studies have examined the value of IVIM in grading ccRCC yet with inconsistent results. This study aimed to compare the value of DWI and IVIM in grading ccRCC. Methods: In this study, 96 patients with pathologically confirmed ccRCC were evaluated by DWI and IVIM on a 3-T scanner. According to the World Health Organization/International Society of Urological Pathology (WHO/ISUP) classification system, these patients were divided into two groups: low-grade (grade I and II) and high-grade (grade III and IV) ccRCC. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction of pseudodiffusion (f) values were calculated. The Mann-Whitney test, receiver-operating characteristic (ROC) analysis, and the Delong test were used for statistical evaluations. Results: (I) According to the WHO/ISUP nuclear grading system, 96 patients were divided into low-grade (grade I and II, 45 patients) and high-grade (grade III and IV, 51 patients) groups. (II) Compared with patients of low-grade ccRCC, the ADC and D values of those with high-grade ccRCC decreased while the D* and f values increased (P<0.05). (III) The cutoff value of the ADC, D, D*, and f in distinguishing low-grade from high-grade ccRCC was 1.50×10-3 mm2/s, 1.12×10-3 mm2/s, and 33.19×10-3 mm2/s, 0.31, respectively; the area under the curve (AUC) for the ADC, D, D*, and f values was 0.871, 0.942, 0.621, and 0.894, respectively, with the AUC of the D value being the highest; the sensitivity for the ADC, D, D*, and f values was 94.12%, 92.16%, 47.06%, and 92.16%, respectively; and the specificity for the ADC, D, D*, and f values was 66.67%, 91.11%, 77.78%, and 73.33%, respectively. (IV) Based on the Delong test, AUCD was significantly higher than AUCADC (P=0.02) and AUCD* (P<0.001), but there was no significant difference between AUCD and AUC f (P=0.18). Conclusions: Compared with the monoexponential model DWI, the biexponential model IVIM was more accurate in grading ccRCC.
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Background: The noninvasive prediction of sentinel lymph node (SLN) metastasis using quantitative magnetic resonance imaging (MRI), particularly with synthetic MRI (syMRI), is an emerging field. This study aimed to explore the potential added benefits of syMRI over conventional MRI and diffusion-weighted imaging (DWI) in predicting metastases in SLNs. Methods: This retrospective study consecutively enrolled 101 patients who were diagnosed with breast cancer (BC) and underwent SLN biopsy from December 2022 to October 2023 at the Affiliated Hospital of Jiangnan University. These patients underwent preoperative MRI including conventional MRI, DWI, and syMRI and were categorized into two groups according to the postoperative pathological results: those with and without metastatic SLNs. MRI morphological features, DWI, and syMRI-derived quantitative parameters of breast tumors were statistically compared between these two groups. Binary logistic regression was used to separately develop predictive models for determining the presence of SLN involvement, with variables that exhibited significant differences being incorporated. The performance of each model was evaluated through receiver operating characteristic (ROC) curve analysis, including the area under the curve (AUC), sensitivity, and specificity. Results: Compared to the group of 54 patients with BC but no metastatic SLNs, the group of 47 patients with BC and metastatic SLNs had a significantly larger maximum axis diameter [metastatic SLNs: median 2.40 cm, interquartile range (IQR) 1.50-3.00 cm; no metastatic SLNs: median 1.80 cm, IQR 1.37-2.50 cm; P=0.03], a higher proton density (PD) (78.44±11.92 vs. 69.20±10.63 pu; P<0.001), and a lower apparent diffusion coefficient (ADC) (metastatic SLNs: median 0.91×10-3 mm2/s, IQR 0.79-1.01 mm2/s; no metastatic SLNs: median 1.02×10-3 mm2/s, IQR 0.92-1.12 mm2/s; P=0.001). Moreover, the prediction model with maximum axis diameter and ADC yielded an AUC of 0.71 [95% confidence interval (CI): 0.618-0.802], with a sensitivity of 78.72% and a specificity of 51.85%; After addition of syMRI-derived PD to the prediction model, the AUC increased significantly to 0.86 (AUC: 0.86 vs. 0.71; 95% CI: 0.778-0.922; P=0.002), with a sensitivity of 80.85% and a specificity of 81.50%. Conclusions: Combined with conventional MRI and DWI, syMRI can offer additional value in enhancing the predictive performance of determining SLN status before surgery in patients with BC.
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This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Neoplasias Encefálicas , Glioma , Imagen por Resonancia Magnética , Humanos , Glioma/diagnóstico por imagen , Glioma/genética , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/genética , Imagen por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Imagen de Difusión por Resonancia Magnética/métodos , Biomarcadores de Tumor/genéticaRESUMEN
RATIONALE AND OBJECTIVES: The aim of this study was to ascertain whether the utilization of multiple b-value diffusion-weighted habitat imaging, a technique that depicts tumor heterogeneity, could aid in identifying breast cancer patients who would derive substantial benefit from neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: This prospective study enrolled 143 women (II-III breast cancer), who underwent multi-b-value diffusion-weighted imaging (DWI) in 3-T magnetic resonance (MR) before NAC. The patient cohort was partitioned into a training set (consisting of 100 patients, of which 36 demonstrated a pathologic complete response [pCR]) and a test set (featuring 43 patients, 16 of whom exhibited pCR). Utilizing the training set, predictive models for pCR, were constructed using different parameters: whole-tumor radiomics (ModelWH), diffusion-weighted habitat-imaging (ModelHabitats), conventional MRI features (ModelCF), along with combined models ModelHabitats+CF. The performance of these models was assessed based on the area under the receiver operating characteristic curve (AUC) and calibration slope. RESULTS: In the prediction of pCR, ModelWH, ModelHabitats, ModelCF, and ModelHabitats+CF achieved AUCs of 0.733, 0.722, 0.705, and 0.756 respectively, within the training set. These scores corresponded to AUCs of 0.625, 0.801, 0.700, and 0.824 respectively in the test set. The DeLong test revealed no significant difference between ModelWH and ModelHabitats (P = 0.182), between ModelHabitats and ModelHabitats+CF (P = 0.113). CONCLUSION: The habitat model we developed, incorporating first-order features along with conventional MRI features, has demonstrated accurate predication of pCR prior to NAC. This model holds the potential to augment decision-making processes in personalized treatment strategies for breast cancer.
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BACKGROUND: The objective is to analyze and review the clinical, laboratory, and neuroimaging characteristics of rheumatoid meningitis (RM) in six patients with known rheumatoid arthritis (RA). METHODS: We performed a retrospective review of patients diagnosed with RM from August 2012 to June 2023. To identify the cases, we used medical term search engines and the hospital´s radiology case database. Clinical information and laboratory findings were gathered from the medical records. A neuroradiologist with five years of experience reviewed and analyzed the RM to determine the characteristics findings of RM. RESULTS: Six patients with RM are included. Seizures along with headaches were among the clinical signs that were documented. All the patients had high levels of rheumatoid factor (RF) and anti-cyclic citrullinated peptides (ACPA) in the peripheral blood. Biopsy in two cases confirmed typical rheumatoid nodules. Leptomeningeal enhancement was found bilaterally in all cases and was predominantly found in the frontoparietal region. "Mismatch DWI/FLAIR" was found in five patients. Bilateral subdural collections could be found in two patients. Brain PET scan revealed increased metabolism in two cases. CONCLUSION: Rheumatoid meningitis is a rare complication of rheumatoid arthritis (RA) with challenging clinical diagnosis due to non-specific symptoms. This study highlights the importance of MR in detecting characteristic neuroimaging patterns, including "mismatch DWI/FLAIR", to aid in early diagnosis. Increased awareness of this condition may facilitate timely intervention and improve prognosis. These results still need to be verified by large studies.
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Artritis Reumatoide , Meningitis , Humanos , Artritis Reumatoide/complicaciones , Artritis Reumatoide/diagnóstico por imagen , Estudios Retrospectivos , Femenino , Meningitis/diagnóstico por imagen , Meningitis/etiología , Meningitis/complicaciones , Meningitis/diagnóstico , Persona de Mediana Edad , Masculino , Anciano , Adulto , Imagen por Resonancia Magnética , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Factor Reumatoide/sangreRESUMEN
Background: Diffusion-derived vessel density (DDVD) is a physiological surrogate of the area of micro-vessels per unit tissue area. DDVD is calculated according to: DDVD(b0b5) = Sb0/ROIarea0 - Sb5/ROIarea5, where Sb0 and Sb5 refer to the tissue signal when b is 0 or 5 s/mm2. This study applied DDVD to assess the perfusion of rectal carcinoma (RC). Methods: MRI was performed with a 3.0-T magnet. Diffusion weighted image with b-values of 0, 5 s/mm2 were acquired in 113 patients with non-mucinous RC and 15 patients with mucinous RC. Diffusion-derived vessel density ratio [DDVDr(b0b5)] was DDVD(b0b5) of RC divided by DDVD(b0b5) of tumor-free rectal wall. Results: The median value of the DDVDr(b0b5) for non-mucinous RCs was 1.430, with the majority of RCs showing a higher DDVD than the adjacent tumor-free wall [i.e., with DDVDr(b0b5) >1]. 90.3% (102/113) of non-mucinous RCs were hypervascular, 1.77% (2/113) were iso-vascular, and 7.96% (9/113) were hypovascular. The median value of the DDVDr(b0b5) for mucinous RCs was 1.660. 73.3% (11/15) of mucinous RCs were hypervascular, and 26.7% (4/15) were hypovascular. A trend (P=0.09) was noted that earlier clinical grades non-mucinous RCs had a higher DDVDr(b0b5) than those of the advanced clinical grades (2.245 for grade 0&I, 1.460 for grade II, 1.430 for grade III, 1.130 for grade IV). A non-significant trend was noted with well and moderately differentiated non-mucinous RCs had a higher DDVDr(b0b5)than that of poorly differentiated non-mucinous RCs (median: 1.460 vs. 1.320). A non-significant trend was noted with MRI-detected extramural vascular invasion (mrEMVI) positive non-mucinous RCs had a higher DDVDr(b0b5) than that of mrEMVI negative non-mucinous RCs (1.630 vs. 1.370). Conclusions: DDVD results in this study approximately agree with contrast agent dynamically enhanced CT literature data.
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Background: Although previous studies have shown that the injection of contrast agents can improve image quality, the specific impact of this on T2-weighted fat-suppressed (T2 FS) and diffusion-weighted imaging (DWI) sequences in the diagnosis of breast cancer remains incompletely understood. In particular, there is insufficient research on how contrast agents affect the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values within these sequences, and how these changes influence the diagnosis of benign and malignant breast tumors. Methods: Breast magnetic resonance images (MRI) were obtained from 178 consecutive patients on a 3T scanner. The SNR and CNR of lesions on T2 FS sequence were calculated before and after contrast agent injection and compared. Differences between pre- and post-contrast ADC in identifying different tumor types were compared using the Kruskal-Wallis H-test and the paired comparison test. The accuracy of ADC values between pre- and post-contrast in distinguishing benign and malignant breast masses was assessed using receiver operating characteristic (ROC) curves. Results: The SNR and CNR of T2 FS sequence increased after contrast injection, and especially for invasive cancer and benign tumor, the increase was significant. For DWI, there was a slight increase or decrease of ADC values after contrast injection, but the ADC values before and after contrast had a similar effect in identifying different types of tumors. In the ROC curve analysis for assessing benign and malignant breast tumors, the area under the curve (AUC) before and after contrast showed similar results. Conclusions: Contrast agent injection can improve the SNR and CNR of T2 FS sequence, thus providing higher quality images for the diagnosis of breast lesions. Furthermore, injection of contrast agent had little effect on the ability of ADC values to identify different types of lesions and both ADC values before and after the contrast agent were able to distinguish between benign and malignant tumors with almost the same accuracy.