Higher Apparent Diffusion Coefficient Research Articles

Improving the Performance of the Layered Nickel Manganese Oxide Cathode of Sodium-Ion Batteries by Direct Coating with Sodium Niobium Oxide.

This research highlights the efficacy of NaNbO3 as a coating for P2-Na2/3Ni1/3Mn2/3O2 cathodes in sodium-ion batteries. The coating enhances the kinetic behavior and cyclability of the electrochemical cells, as shown by electrochemical measurements. XRD analysis indicates that Nb does not incorporate into the cathode structure, implying a physical interaction between the coating and the cathode material. XRF analysis and EDX mapping confirm the actual composition and uniform dispersion of elements throughout the sample, while the electron micrographs evidence the occurrence of NaNbO3 particles modifying the surface of the layered oxide. The Ni4+/Ni3+ and Ni3+/Ni2+ redox pairs, along with the partially reversible oxidation of oxide to peroxide anions, contribute significantly to cell capacity, as revealed by XPS spectra. This last effect and the appearance of a co-intercalated phase at high voltage are positive factors to provide fast kinetics. Cyclic voltammograms show that samples coated with 2-3% NaNbO3 have superior rate capability, with high capacitive response and apparent diffusion coefficients. These samples also have low impedance at the electrode-electrolyte interface, which helps deliver a high capacity at 5C. Further cycling at 1C shows improved cyclability in the bare and 3% coated samples, due to their higher diffusion coefficients on charging. Notably, the 3% NaNbO3-coated sample exhibits excellent cyclability below 0 °C, making it a promising cathode material for sodium-ion batteries.

Comparison of Diffusion-weighted MRI using Singe-Shot Echo-planar Imaging (SS-EPI) and Split Acquisition of Fast Spin Echo Signal (SPLICE) Imaging, a non-EPI technique, in Tumors of the Head and Neck.

Diffusion-weighted imaging (DWI) using single-shot echo planar imaging (DW-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, Split acquisition of fast spin echo signals for diffusion imaging (DWSPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DW-EPI through quantitative and qualitative analyses. The DW-SPLICE sequence was incorporated into the standard 3.0T head and neck MRI protocol with DW-EPI. Retrospective analysis was conducted on two subgroups: firstly benign or malignant lesions, and secondly post-treatment SCC recurrence. In both subgroups Image quality and distortion were scored by two independent radiologists, blinded for DW-technique, and evaluated using mixed-effect linear models. Lesion apparent diffusion coefficient (ADC) values were assessed with inter-class correlation (ICC) and Bland-Altman analyses. DWI's delineation geometric similarity to T1-weighted post-contrast (T1Wc) MRI was evaluated using the Dice Similarity Coefficient (DSC) before and after registration. Recurrence in post-treatment SCC scans was evaluated by the same two radiologists blinded for DW-technique. Recurrence detection rates were then compared between DW-SPLICE and DW-EPI using mixed logistic regression at six months and at one-year post-scan follow-up data. From August 2020 to January 2022, 55 benign or malignant lesion scans (55 patients) and 74 post-treatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DW-EPI (0.04<p<0.001). There was high ADC measurement reliability (ICC=0.93, p<0.001), though a proportional bias was also observed (β=0.11, p=0.03), indicating the bias increases as ADC values rise. DWSPLICE exhibited greater geometric similarity to T1Wc before registration (DSC 0.63 vs 0.47, p<0.001) and outperformed DW-EPI by more accurately identifying recurrences after one year (OR=0.96, p=0.05) but not after six months (OR=0.72, p=0.13). DW-SPLICE surpasses DW-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the HN. Consistent use of one method for follow-up is advised, as ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice. ANTs = Advanced Normalization Tools; DSC = Dice Similarity Coefficient; DW-EPI = Diffusion-weighted single-shot echo planar imaging; DW-MS-EPI = Diffusion-weighted multi-shot echo planar imaging; DW-SPLICE = Diffusion-weighted split acquisition of fast spin echo signals for diffusion imaging; DW-TSE = Diffusion-weighted Turbo Spin Echo; ICC = Intraclass Correlation Coefficient; ROC = Receiver Operating Characteristic; SCC = Squamous cell carcinoma; T1WIc = T1 weighted imaging with gadolinium contrast.

Characterization of Classic Meningioma with Use of Conventional Magnetic Resonance and Diffusion Tensor Imaging

Introduction: The conventional magnetic resonance imaging (MRI) method is widely considered ‘with limited success’ in differentiating the meningioma types but may fail to localize the tumor occupation of white-matter fiber bundles accurately. Diffusion tensor imaging (DTI) is considered as an imaging modality that may elucidate the microstructure of brain tumors. We provide characteristics of meningioma using DTI-based-three-dimensional tracing of white matter to portray meningioma in a noninvasive approach and its structural contact to contiguous tumors and elucidate the influence of occupying lesions on white-matter fiber bundles. Case Presentation: A 28-year-old female presented with visuospatial disturbances and persistent headaches for 2 years. Conventional and advanced MRI studies were performed. Diffusion-weighted Images (DWI) and Apparent Diffusion Coefficient (ADC) values were measured in the lesion using routine MRI sequences. Advanced MRI using DTI was also performed. Conventional MRI outcomes showed tumor parenchyma, peritumoral edema, and compression on the circumnavigated brain tissue. There was hyperintense on DW trace image and isointense on ADC map. On T2-weighted image (T2WI) and Fluid-Attenuated Inversion Recovery (FLAIR) images, there was an increased signal intensity that demonstrated an extra-axial lesion, while T1-weighted imaging signals showed hypointensity. DTI fractional anisotropy (FA) marker is an unclear optic radiation in the concerned area, indicating the shift or destruction of the optic radiation. The mean FA values of solid-enhancing areas of meningioma were 0.28 ± 0.17. Mean ADC values (103 mm2/s) were 0.764 ± 0.172. Conclusions: Classic meningioma in this case has low intratumoral FA and high ADC. DTI displayed that intratumoral microscopic water motion is disorganized.

MerlinS13 phosphorylation regulates meningioma Wnt signaling and magnetic resonance imaging features

Meningiomas are associated with inactivation of NF2/Merlin, but approximately one-third of meningiomas with favorable clinical outcomes retain Merlin expression. Biochemical mechanisms underlying Merlin-intact meningioma growth are incompletely understood, and non-invasive biomarkers that may be used to guide treatment de-escalation or imaging surveillance are lacking. Here, we use single-cell RNA sequencing, proximity-labeling proteomic mass spectrometry, mechanistic and functional approaches, and magnetic resonance imaging (MRI) across meningioma xenografts and patients to define biochemical mechanisms and an imaging biomarker that underlie Merlin-intact meningiomas. We find Merlin serine 13 (S13) dephosphorylation drives meningioma Wnt signaling and tumor growth by attenuating inhibitory interactions with β-catenin and activating the Wnt pathway. MRI analyses show Merlin-intact meningiomas with S13 phosphorylation and favorable clinical outcomes are associated with high apparent diffusion coefficient (ADC). These results define mechanisms underlying a potential imaging biomarker that could be used to guide treatment de-escalation or imaging surveillance for patients with Merlin-intact meningiomas.

Tumor Apparent Diffusion Coefficient is Associated with Early Recurrence of Intrahepatic Cholangiocarcinoma

Rationale and ObjectivesIdentifying intrahepatic cholangiocarcinoma (iCCA) patients who are at high risk for early recurrence (ER) can guide personalized treatment strategy and improve survival. This study aimed to investigate the value of preoperative MRI, especially diffusion-weighted imaging, in predicting ER, including in patients receiving neoadjuvant therapy. Materials and methodsThis study included 175 pathologically-confirmed iCCA patients who underwent curative resection (114 men, 61 women; mean age 59.0±9.56 years). MRI features, particularly apparent diffusion coefficient (ADC), were analyzed and compared between ER and non-ER cases. Survival analyses of ER were evaluated using Cox regression and Kaplan-Meier analysis. ResultsER occurred in 54.3% (95/175) of patients. Multivariate logistic regression analysis identified tumor ADC as the only independent predictor of ER (odds ratio=0.034, P<0.001), with AUCs of 0.758 (95%CI 0.664, 0.836) in the testing cohort and 0.779 (95%CI 0.622, 0.893) in the validation cohort. The optimal ADC threshold was 1.273×10-3mm2/s. Tumor ADC was comparable to the AJCC 8th staging system in predicting ER (AUC 0.758 vs 0.650 in testing cohort and 0.779 vs 0.661 in validation cohort). Multivariate Cox analysis identified high tumor burden score (HR=1.109, P=0.009), non-smooth margin (HR=2.265, P=0.008) and tumor ADC (HR=0.111, P<0.001) as independent risk factors for ER. Lower ADC values were linked to shorter RFS in both testing and validation cohorts (P<0.001 and 0.0219), as well as in patients receiving neoadjuvant therapy (P=0.003). ConclusionPreoperative MRI, particularly ADC, can help predict ER in iCCA, regardless of the application of neoadjuvant therapy, comparable to the AJCC 8th staging system.

Direct correlation of MR-DWI and histopathology of Wilms' tumours through a patient-specific 3D-printed cutting guide.

The International Society of Paediatric Oncology-Renal Tumour Study Group (SIOP-RTSG) discourages invasive procedures to determine the histology of paediatric renal neoplasms at diagnosis. Therefore, the histological subtype of Wilms' tumours (WT) is unknown at the start of neoadjuvant chemotherapy. MR-DWI shows potential value as a non-invasive biomarker through apparent diffusion coefficients (ADCs). This study aimed to describe MR characteristics and ADC values of paediatric renal tumours to differentiate subtypes. Children with a renal tumour undergoing surgery within the SIOP-RTSG 2016-UMBRELLA protocol were prospectively included between May 2021 and 2023. In the case of a total nephrectomy, a patient-specific cutting guide based on the neoadjuvant MR was 3D-printed, allowing a correlation between imaging and histopathology. Whole-tumour volumes and ADC values were statistically compared with the Mann-Whitney U-test. Direct correlation on the microscopic slide level was analysed through mixed model analysis. Fifty-nine lesions of 54 patients (58% male, median age 3.0 years (range 0-17.7 years)) were included. Forty-four lesions involved a WT. Stromal type WT showed the lowest median decrease in volume after neoadjuvant chemotherapy (48.1 cm3, range 561.5-(+)332.7 cm3, p = 0.035). On a microscopic slide level (n = 240 slides) after direct correlation through the cutting guide, stromal areas showed a significantly higher median ADC value compared to epithelial and blastemal foci (p < 0.001). With a cut-off value of 1.195 * 10-3 mm2/s, sensitivity, and specificity were 95.2% (95% confidence interval 87.6-98.4%) and 90.5% (95% confidence interval 68.2-98.3%), respectively. Correlation between histopathology and MR-DWI through a patient-specific 3D-printed cutting guide resulted in significant discrimination of stromal type WT from epithelial and blastemal subtypes. Stromal Wilms' tumours could be discriminated from epithelial- and blastemal lesions based on high apparent diffusion coefficient values and limited decrease in volume after neoadjuvant chemotherapy. This may aid in future decision-making, especially concerning discrimination between low- and high-risk neoplasms. MR-DWI shows potential value as a non-invasive biomarker in paediatric renal tumours. The patient-specific cutting guide leads to a correlation between apparent diffusion coefficient values and Wilms' tumour subtype. Stromal areas could be discriminated from epithelial and blastemal foci in Wilms' tumours based on apparent diffusion coefficient values.

Extraocular muscle Diffusion Weighted Imaging as a quantitative metric of posterior orbital involvement in thyroid associated orbitopathy

ObjectivesThe clinical activity score (CAS) and European severity scale (ESS) are established clinical tools to assess thyroid eye disease (TED) but are limited in terms of subjectivity and their reliability in non-Caucasian individuals, and can underestimate significant disease in the posterior orbit. Preliminary data from pilot studies have shown that diffusion-weighted imaging (DWI) using extraocular muscle (EOM) apparent diffusion coefficient (ADC) measurements may provide complementary information in TED. This study expands on previous research to assess for correlations between clinical scores and EOM-ADCs in stratifying disease activity and severity in a large patient cohort from an ethnically diverse population.MethodsA retrospective review of TED clinics between 2011 and 2021 identified 96 patients with a documented CAS and ESS and an orbital MRI that included DWI. From regions of interest manually placed on EOM bellies, the highest ADC was computed for each patient and analysed for correlations and associations with CAS and ESS using Spearman Rank correlation and Mann–Whitney U tests, and any potential discriminatory cut-offs using Receiver Operator Curve analyses. A p-value < 0.05 indicated statistical significance.ResultsEOM-ADCs showed a positive association with CAS (p ≤ 0.001). EOM-ADCs were higher in sight-threatening compared to mild disease (p ≤ 0.01). A cut-off of 995 mm2/s achieved AUC = 0.7744, equating to 77% sensitivity and 67% specificity for discrimination between mild-moderate and sight-threatening disease.ConclusionEOM-ADCs correlate with higher scores of disease severity and activity in TED. Besides providing quantitative data to support clinical tools, EOM-ADC cut-offs may identify patients at risk of developing sight-threatening diseases.Critical relevance statementThis study critically evaluates the limitations of conventional clinical assessment tools for TED and demonstrates the utility of DWI scans with ADC measurements in identifying active disease, offering valuable insights to advance clinical radiology practice.Key PointsConventional tools for TED assessment have subjective limitations.ADCs from non-echoplanar diffusion-weighted imaging correlate with clinical activity.Non-echoplanar diffusion-weighted imaging offers quantitative assessment to aid clinical practice reliability.Graphical

Association between mpMRI detected tumor apparent diffusion coefficient and 5-year biochemical recurrence risk after radical prostatectomy.

To assess the ability of tumor apparent diffusion coefficient (ADC) values obtained from multiparametric magnetic resonance imaging (mpMRI) to predict the risk of 5-year biochemical recurrence (BCR) after radical prostatectomy (RP). This retrospective analysis included 1207 peripheral and 232 non-peripheral zone prostate cancer (PCa) patients who underwent mpMRI before RP (2012-2015), with the outcome of interest being 5-year BCR. ADC was evaluated as a continuous variable and as categories: low (< 850µm2/s), intermediate (850-1100µm2/s), and high (> 1100µm2/s). Kaplan-Meier curves with log-rank testing of BCR-free survival, multivariable Cox proportional hazard regression models were formed to estimate the risk of BCR. Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025µm2/s, p < 0.001). Five-year BCR-free survival rates were 52.3%, 74.4%, and 87% for patients in the low, intermediate, and high ADC value categories, respectively (p < 0.0001). Lower ADC was associated with BCR, both as continuously coded variable (HR: 5.35; p < 0.001) and as ADC categories (intermediate versus high ADC-HR: 1.56, p = 0.017; low vs. high ADC-HR; 2.36, p < 0.001). In the non-peripheral zone PCa patients, no association between ADC and BCR was observed. Tumor ADC values and categories were found to be predictive of the 5-year BCR risk after RP in patients with peripheral zone PCa and may serve as a prognostic biomarker.

Radiomics by Quantitative Diffusion-weighted MRI for Predicting Response in Patients with Extremity Soft-tissue Undifferentiated Pleomorphic Sarcoma

Purpose: This study aimed to determine the relevance of first- and high-order radiomic features derived from Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) maps for predicting treatment response in patients with Undifferentiated Pleomorphic Sarcoma (UPS). Methods: This retrospective study included 33 extremity UPS patients with pre-surgical DWI/ADC and surgical resection. Manual volumetric tumor segmentation was performed on DWI/ADC maps acquired at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The percentage of pathology-assessed treatment effect (PATE) in surgical specimens categorized patients into responders (R; PATE ≥ 90%; 16 patients), partial-responders (PR; 89% - 31% PATE; 10 patients), and non-responders (NR; PATE ≤ 30%; 7 patients). 107 radiomic features were extracted from BL, PC, and PRT ADC maps. Statistical analyses compared R vs. PR/NR. Results: Pseudo-progression at PC and universal stability at PRT were observed in R and PR/NR based on RECIST, WHO, and volumetric assessments. At PRT, responders displayed a 35% increase in ADC mean (p = 0.0034), a 136% decrease in skewness (p = 0.0001), and a 363% increase in the 90th percentile proportion (p = 0.0009). Comparing R vs. PR/NR at BL, statistically significant differences were observed in glrlm_highgraylevelrunemphasis (p = 0.0081), glrlm_shortrunhighgraylevelemphasis (p = 0.0138), gldm_highgraylevelemphasis (p = 0.0138), glcm_sumaverage (p = 0.0164), glcm_jointaverage (p = 0.0164), and glcm_autocorrelation (p = 0.0193). At PC, firstorder_meanabsolutedeviation (p = 0.0078), firstorder_interquartilerange (p = 0.0109), firstorder_variance (p = 0.0109), and firstorder_robustmeanabsolutedeviation (p = 0.0151) provided statistically significant differences. Conclusion: Observing a high post-therapeutic ADC mean, low skewness, and high 90th percentile proportion with respect to baseline is predictive of successfully treated UPS patients presenting &gt; 90% PATE. Highly significant higher-order radiomic results include glrlm-highgraylevelrunemphasis (BL) and first-order-mean absolute deviation (PC).

Apparent Diffusion Coefficient on Diffusion-Weighted Magnetic Resonance Imaging to Predict the Prognosis of Patients with Endometrial Cancer: A Meta-Analysis.

Apparent diffusion coefficient (ADC) derived from diffusion-weighted magnetic resonance imaging (DWI) may help diagnose endometrial cancer (EC). However, the association between ADC and the recurrence and survival of EC remains unknown. We performed a systematic review and meta-analysis to investigate whether pretreatment ADC on DWI could predict the prognosis of women with EC. PubMed, Embase, and Cochrane's Library were searched for relevant cohort studies comparing the clinical outcomes between women with EC having low versus high ADC on pretreatment DWI. Two authors independently conducted data collection, literature searching, and statistical analysis. Using a heterogeneity-incorporating random-effects model, we analyzed the results. In the meta-analysis, 1358 women with EC were included from eight cohort studies and followed for a median duration of 40 months. Pooled results showed that a low pretreatment ADC on DWI was associated with poor disease-free survival (DFS, hazard ratio [HR]: 3.29, 95% CI: 2.04 to 5.31, p < 0.001; I2 = 41%). Subgroup analysis according to study design, tumor stage, MRI Tesla strength, ADC cutoff, follow-up duration, and study quality score showed consistent results (p for subgroup analysis all > 0.05). The predictive value of low ADC for poor DFS in women with EC decreased in multivariate studies compared to univariate studies (HR: 2.59 versus 32.57, p = 0.002). Further studies showed that a low ADC was also associated with poor overall survival (HR: 3.36, 95% CI: 1.33 to 8.50, p = 0.01, I2 = 0). In conclusion, a low ADC on pretreatment DWI examination may predict disease recurrence and survival in women with EC.

Unveiling the Energy Storage Mechanism of MnO2 Polymorphs for Zinc‐Manganese Dioxide Batteries

AbstractThe energy storage mechanism of MnO2 in aqueous zinc ion batteries (ZIBs) is investigated using four types of MnO2 with crystal phases corresponding to α‐, β‐, γ‐, and δ‐MnO2. Experimental and theoretical calculation results reveal that all MnO2 follow the H+ and Zn2+ co‐intercalation mechanism during discharge, with ZnMn2O4, MnOOH, and Zn4(SO4)(OH)6·4H2O being the main products. ZnMn2O4 is formed from Zn2+ intercalation, while MnOOH and Zn4(SO4)(OH)6·4H2O are formed from H+ intercalation. Charging generates MnO2 through the extraction of Zn2+ and H+ from ZnMn2O4 and MnOOH, indicating reversible reactions. The study also reveals that H+ intercalation exhibits better kinetics than Zn2+ intercalation due to its higher diffusion ability and easier charge transfer. The crystal structures and diffusion energy barriers differences are responsible for the differences of H+ and Zn2+ diffusion in MnO2, with the layered δ phase exhibiting the lowest diffusion energy barrier and highest apparent diffusion coefficient, while the α phase exhibits the highest diffusion energy barrier and lowest apparent diffusion coefficient. These findings highlight the importance of crystal phases in determining the diffusion ability and energy storage of MnO2, which can inform strategies for design of multiphase MnO2 cathodes for high‐performance ZIBs.

Evaluation of the neoadjuvant chemotherapy response in osteosarcoma using the MRI DWI-based machine learning radiomics nomogram.

To evaluate the value of a nomogram combined MRI Diffusion Weighted Imaging (DWI) and clinical features to predict the treatment response of Neoadjuvant Chemotherapy (NAC) in patients with osteosarcoma. A retrospective analysis was conducted on 209 osteosarcoma patients admitted into two bone cancer treatment centers (133 males, 76females; mean age 16.31 ± 11.42 years) from January 2016 to January 2022. Patients were classified as pathological good responders (pGRs) if postoperative histopathological examination revealed ≥90% tumor necrosis, and non-pGRs if <90%. Their clinical features were subjected to univariate and multivariate analysis, and features with statistically significance were utilized to construct a clinical signature using machine learning algorithms. Apparent diffusion coefficient (ADC) values pre-NAC (ADC 0) and post two chemotherapy cycles (ADC 1) were recorded. Regions of interest (ROIs) were delineated from pre-treatment DWI images (b=1000 s/mm²) for radiomic features extraction. Variance thresholding, SelectKBest, and LASSO regression were used to select features with strong relevance, and three machine learning models (Logistic Regression, RandomForest and XGBoost) were used to construct radiomics signatures for predicting treatment response. Finally, the clinical and radiomics signatures were integrated to establish a comprehensive nomogram model. Predictive performance was assessed using ROC curve analysis, with model clinical utility appraised through AUC and decision curve analysis (DCA). Of the 209patients, 51 (24.4%) were pGRs, while 158 (75.6%) were non-pGRs. No significant ADC1 difference was observed between groups (P>0.05), but pGRs had a higher ADC 0 (P<0.01). ROC analysis indicated an AUC of 0.681 (95% CI: 0.482-0.862) for ADC 0 at the threshold of ≥1.37×10-3 mm²/s, achieving 74.7% sensitivity and 75.7% specificity. The clinical and radiomics models reached AUCs of 0.669 (95% CI: 0.401-0.826) and 0.768 (95% CI: 0.681-0.922) respectively in the test set. The combined nomogram displayed superior discrimination with an AUC of 0.848 (95% CI: 0.668-0.951) and 75.8% accuracy. The DCA suggested the clinical utility of the nomogram. The nomogram based on combined radiomics and clinical features outperformed standalone clinical or radiomics model, offering enhanced accuracy in evaluating NAC response in osteosarcoma. It held significant promise for clinical applications.

Prostate diffusion-weighted imaging (DWI) in MR-guided radiotherapy: Reproducibility assessment on 1.5 T MR-Linac and 1.5 T MR-simulator

PurposeDiffusion-weighted imaging (DWI) holds promise for image-guided radiotherapy (MRgRT) in prostate cancer. However, challenges persist due to image distortion, artifacts, and apparent diffusion coefficient (ADC) reproducibility issues. This study aimed to assess DWI image quality and ADC reproducibility on both a 1.5 T MR-simulator and a 1.5 T MR-Linac, employing measurements from both an ACR MRI phantom and prostate cancer patients undergoing MRgRT. MethodsDW-MRI scans were conducted on 19 patients (mean age = 69 ± 8 years, with 23 MR-visible intra-prostatic lesions) and an ACR MRI phantom using a 1.5 T MR-simulator (b-values = 0, 800, 1400s/mm2) and a 1.5 T MR-Linac (b-values = 50, 500, 800 s/mm2). ADC homogeneity in the phantom was evaluated via 1D profile flatness (FL) in three directions. Image quality was assessed through qualitative 5-point Likert scale ratings and quantitative ADC and signal-to-noise ratio (SNR) measurements. Intra-observer reproducibility of image quality scores was evaluated using ICC(1, 2). Geometric distortion was measured by comparing landmark sizes on the ACR phantom against the ground truth. Mean ADC and reproducibility were assessed using Bland-Altman plots. ResultsBoth MR-simulator and MR-Linac demonstrated high ADC homogeneity (FL > 87.5% - MR-simulator: 97.23 ± 0.62%, MR-Linac: 94.75 ± 0.62%, p < 0.05) in the phantom. Image quality scores revealed acceptable ratings (≥3) for capsule demarcation, image artifacts, and geometric distortion in patients. However, intra-prostatic lesions were barely discernible in b800 images for both MR-simulator (average score = 2.37 ± 1.33) and MR-Linac (average score = 2.16 ± 1.28). While MR-Linac DWI scans exhibited significantly more severe geometric distortion than MR-simulator scans (p < 0.01), most phantom measurements fell within the image in-plane resolution of 3 mm. Significant differences were noted in MR-simulator ADC (CTV: 1.20 ± 0.14 × 10−3 mm2/s (MR-simulator) vs 1.06 ± 0.10 × 10–3 mm2/s (MR-Linac); GTV: 1.05 ± 0.21 × 10−3 mm2/s vs 0.91 ± 0.16 × 10 mm2/s, all p < 0.05), with a small non-zero bias observed in the Bland-Altman analysis (CTV: 12.3%; GTV: 14.5%). ConclusionThe significantly larger MR-simulator ADC and the small non-zero bias hint at potential systematic differences in ADC values acquired from an MR-simulator and an MR-Linac, both at 1.5 T. Although acceptable ADC homogeneity was noted, caution is warranted in interpreting MR-Linac DWI images due to occasional severe artifacts. Further studies are essential to validate DWI and ADC as reliable imaging markers in prostate cancer MRgRT.

Development and validation of cardiac diffusion weighted magnetic resonance imaging for the diagnosis of myocardial injury in small animal models

Cardiac diffusion weighted-magnetic resonance imaging (DWI) has slowly developed due to its technical difficulties. However, this limitation could be overcome by advanced techniques, including a stimulated echo technique and a gradient moment nulling technique. This study aimed to develop and validate a high-order DWI sequence, using echo-planar imaging (EPI) and second-order motion-compensated (M012) diffusion gradient applied to cardiac imaging in small-sized animals with fast heart and respiratory rates, and to investigate the feasibility of cardiac DWI, diagnosing acute myocardial injury in isoproterenol-induced myocardial injury rat models. The M012 diffusion gradient sequence was designed for diffusion tensor imaging of the rat myocardium and validated in the polyvinylpyrrolidone phantom. Following sequence optimization, 23 rats with isoproterenol-induced acute myocardial injury and five healthy control rats underwent cardiac MRI, including cine imaging, T1 mapping, and DWI. Diffusion gradient was applied using a 9.4-T MRI scanner (Bruker, BioSpec 94/20, gradient amplitude = 440 mT/m, maximum slew rate = 3440 T/m/s) with double gating (electrocardiogram and respiratory gating). Troponin I was used as a serum biomarker for myocardial injury. Histopathologic examination of the heart was subsequently performed. The developed DWI sequence using EPI and M012 provided the interpretable images of rat hearts. The apparent diffusion coefficient (ADC) values were significantly higher in rats with acute myocardial injury than in the control group (1.847 ± 0.326 * 10–3 mm2/s vs. 1.578 ± 0.144 * 10–3 mm2/s, P < 0.001). Troponin I levels were increased in the blood samples of rats with acute myocardial injury (P < 0.001). Histopathologic examinations detected myocardial damage and subendocardial fibrosis in rats with acute myocardial injury. The newly developed DWI technique has the ability to detect myocardial injury in small animal models, representing high ADC values on the myocardium with isoproterenol-induced injury.

MR Imaging Findings of Uterine Adenomatoid Tumors.

Adenomatoid tumor is a rare benign genital tract neoplasm of mesothelial origin. Uterine adenomatoid tumors occur in the outer myometrium and may mimic leiomyomas. Because hormonal treatment is not applicable to adenomatoid tumors and laparoscopic enucleation is not easy as myomectomy, it is important to differentiate adenomatoid tumors from leiomyomas for the adequate treatment. The purpose of this study is to evaluate the MRI findings of adenomatoid tumor for the differentiation from leiomyoma. MRI findings of surgically proven 10 uterine adenomatoid tumors in 9 women were retrospectively evaluated with correlation to histopathological findings. All 10 tumors appeared as solid myometrial masses and showed heterogeneous signal intensity with admixture of partially ill-defined slight high-intensity areas containing abundant tubular tumor cells and well-defined myoma-like low-intensity areas reflecting smooth muscle hypertrophy on T2WI including 4 lesions with peripheral ring-like high intensity. High-intensity areas on T2WI tended to show high intensity on diffusion-weighted imaging (DWI) with relatively high apparent diffusion coefficient (ADC), suggesting T2 shine-through effect due to abundant tubules. Intra-tumoral hemorrhage revealed on MRI was rare. Early intense contrast-enhanced areas on dynamic contrast-enhanced study were observed dominantly within the high-intensity areas but rarely within the low-intensity areas on T2WI. The outer myometrial mass with the admixture of well-defined low- and ill-defined high-intensity areas on T2WI may be suggestive of adenomatoid tumor. Peripheral ring-like high intensity on T2WI and DWI may also be suggestive. Dynamic contrast-enhanced MR study may be helpful for the differentiation from leiomyoma.

Prediction of overall survival in patients with locally advanced pancreatic cancer using longitudinal diffusion-weighted MRI.

Biomarkers for prediction of outcome in patients with pancreatic cancer are wanted in order to personalize the treatment. This study investigated the value of longitudinal diffusion-weighted magnetic resonance imaging (DWI) for prediction of overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiotherapy (SBRT). The study included 45 patients with LAPC who received 5 fractions of 10 Gy on a 1.5T MRI-Linac. DWI was acquired prior to irradiation at each fraction. The analysis included baseline values and time-trends of the apparent diffusion coefficient (ADC) and DWI parameters obtained using a decomposition method. A multivariable Cox proportional hazards model for OS was made using best-subset selection, using cross-validation based on Bootstrap. The median OS from the first day of SBRT was 15.5 months (95% CI: 13.2-20.6), and the median potential follow-up time was 19.8 months. The best-performing multivariable model for OS included two decomposition-based DWI parameters: one baseline and one time-trend parameter. The C-Harrell index describing the model's discriminating power was 0.754. High baseline ADC values were associated with reduced OS, whereas no association between the ADC time-trend and OS was observed. Decomposition-based DWI parameters indicated value in the prediction of OS in LAPC. A DWI time-trend parameter was included in the best-performing model, indicating a potential benefit of acquiring longitudinal DWI during the SBRT course. These findings support both baseline and longitudinal DWI as candidate prognostic biomarkers, which may become tools for personalization of the treatment of patients with LAPC.

Habitat Radiomics Based on MRI for Predicting Platinum Resistance in Patients with High-Grade Serous Ovarian Carcinoma: A Multicenter Study

Rationale and ObjectivesThis study aims to explore the feasibility of MRI-based habitat radiomics for predicting response of platinum-based chemotherapy in patients with high-grade serous ovarian carcinoma (HGSOC), and compared with conventional radiomics and deep learning models. Materials and methodsA retrospective study was conducted on HGSOC patients from three hospitals. K-means algorithm was used to perform clustering on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (CE-T1WI), and apparent diffusion coefficient (ADC) maps. After feature extraction and selection, the radiomics model, habitat model, and deep learning model were constructed respectively to identify platinum-resistant and platinum-sensitive patients. A nomogram was developed by integrating the optimal model and clinical independent predictors. The model performance and benefit was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI). ResultsA total of 394 eligible patients were incorporated. Three habitats were clustered, a significant difference in habitat 2 (weak enhancement, high ADC values, and moderate T2WI signal) was found between the platinum-resistant and platinum-sensitive groups (P<0.05). Compared with the radiomics model (0.640) and deep learning model (0.603), the habitat model had a higher AUC (0.710). The nomogram, combining habitat signatures with a clinical independent predictor (neoadjuvant chemotherapy), yielded a highest AUC (0.721) among four models, with positive NRI and IDI. ConclusionMRI-based habitat radiomics had the potential to predict response of platinum-based chemotherapy in patients with HGSOC. The nomogram combining with habitat signature had a best performance and good model gains for identifying platinum-resistant patients.

Recent Developments in Speeding up Prostate MRI.

The increasing incidence of prostate cancer cases worldwide has led to a tremendous demand for multiparametric MRI (mpMRI). In order to relieve the pressure on healthcare, reducing mpMRI scan time is necessary. This review focuses on recent techniques proposed for faster mpMRI acquisition, specifically shortening T2W and DWI sequences while adhering to the PI-RADS (Prostate Imaging Reporting and Data System) guidelines. Speeding up techniques in the reviewed studies rely on more efficient sampling of data, ranging from the acquisition of fewer averages or b-values to adjustment of the pulse sequence. Novel acquisition methods based on undersampling techniques are often followed by suitable reconstruction methods typically incorporating synthetic priori information. These reconstruction methods often use artificial intelligence for various tasks such as denoising, artifact correction, improvement of image quality, and in the case of DWI, for the generation of synthetic high b-value images or apparent diffusion coefficient maps. Reduction of mpMRI scan time is possible, but it is crucial to maintain diagnostic quality, confirmed through radiological evaluation, to integrate the proposed methods into the standard mpMRI protocol. Additionally, before clinical integration, prospective studies are recommended to validate undersampling techniques to avoid potentially inaccurate results demonstrated by retrospective analysis. This review provides an overview of recently proposed techniques, discussing their implementation, advantages, disadvantages, and diagnostic performance according to PI-RADS guidelines compared to conventional methods. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Microvascular proliferation is associated with high tumour blood flow by mpMRI and disease progression in primary prostate cancer

Active angiogenesis may be assessed by immunohistochemistry using Nestin, a marker of newly formed vessels, combined with Ki67 for proliferating cells. Here, we studied microvascular proliferation by Nestin-Ki67 co-expression in prostate cancer, focusing on relations to quantitative imaging parameters from anatomically matched areas obtained by preoperative mpMRI, clinico-pathological features and prognosis. Tumour slides from 67 patients (radical prostatectomies) were stained for Nestin-Ki67. Proliferative microvessel density (pMVD) and presence of glomeruloid microvascular proliferation (GMP) were recorded. From mpMRI, forward volume transfer constant (Ktrans), reverse volume transfer constant (kep), volume of EES (ve), blood flow, and apparent diffusion coefficient (ADC) were obtained. High pMVD was associated with high blood flow (p = 0.008) and low ADC (p = 0.032). High Ktrans, kep, and blood flow were associated with high Gleason score. High pMVD, GMP, and low ADC were associated with most adverse clinico-pathological factors. Regarding prognosis, high pMVD, Ktrans, kep, and low ADC were associated with reduced biochemical recurrence-free- and metastasis-free survival (p ≤ 0.044) and high blood flow with reduced time to biochemical- and clinical recurrence (p < 0.026). In multivariate analyses however, microvascular proliferation was a stronger predictor compared with blood flow. Indirect, dynamic markers of angiogenesis from mpMRI and direct, static markers of angiogenesis from immunohistochemistry may aid in the stratification and therapy planning of prostate cancer patients.

Ultra high b-value diffusion weighted imaging enables better molecular grading stratification over histological grading in adult-type diffuse glioma

PurposeAccurate preoperative radiological staging of adult-type diffuse glioma is crucial for effective prognostic stratification and selection of appropriate therapeutic interventions. The purpose of this study was to compare the effectiveness of apparent diffusion coefficient (ADC) maps generated from ultrahigh b-value diffusion-weighted imaging (DWI) for molecular grading with that for histological grading of adult-type diffuse glioma, and to evaluate the correlation between these ADC maps and molecular and histological biomarkers. MethodsThis study retrospectively enrolled forty adult-type diffuse glioma patients, diagnosed using the 2021 WHO classification criteria. Preoperative imaging data, including multiple b-value DWI and conventional magnetic resonance imaging, were collected. Tumors were graded using both histological and molecular criteria. Histogram analysis was conducted to generate 14 parameters for each tumor. Receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate tumor grading and molecular status differentiation. Analysis of histological biomarkers was performed by calculating the Pearson and Spearman correlation coefficients of continuous and hierarchical variables, respectively. ResultsThe intensity-related parameters for molecular grading were found to be superior to those for histological grading for the identification of WHO grade 4 (WHO4) adult-type diffuse glioma. The AUC of both grading systems increased with increasing b-values, with ADC8000-based histogram parameters showing the best results (molecular grading, square root: AUC = 0.897; histological grading, median: AUC = 0.737). The intensity-related parameters could also differentiate molecular WHO4 gliomas from histologically lower-grade gliomas (ADC8000-based square root: AUC = 0.919), and different ADC8000-based kurtosis was observed between molecular and histological WHO4 gliomas (AUC = 0.833). Significant correlations between the Ki-67 index and molecular status prediction for IDH, CDKN2A, and EGFR were also demonstrated. ConclusionThe histogram parameters derived from high b-value ADC maps were found to be more effective for differentiating molecular grades of WHO4 adult-type diffuse glioma than for differentiating histological grades.