Analysis of diffusion changes in cerebral tissues of Parki̇nson's patients who underwent subthalamic nucleus deep brain stimulation: Correlation of improvements in motor and neuropsychiatric symptoms.

OBJECTIVE: Parkinson's disease (PD) as a neurodegenerative disorder characterized by a reduction in both the quantity and functionality of dopaminergic neurons. This succinctly highlights the central pathological feature of PD and its association with dopaminergic neuron degeneration, which underlies the motor and non-motor symptoms of the disease. This study aims to elucidate the nuances of apparent diffusion coefficient (ADC) changes in different cerebral regions by after the bilateral subthalamic nucleus (STN) deep brain stimulation (DBS) surgery of PD, as well as to investigate their potential interactions with the motor and neuropsychiatric spectrum. METHODS: Patients who underwent STN-DBS surgery for PD between 2017 and 2019 were included in this study. The results of diffusion magnetic resonance imaging (MRI), Unified Parkinson Disease Rating Scale (UPDRS) III scores, Beck and Hamilton depression tests were recorded before and at the 3rd month of postoperative stimulation. The data obtained were evaluated with the Wilcoxon signed rank test. Result of the statistical tests were within the 95 % confidence interval and p values were significant below 0.05. RESULTS: Our study was conducted with a total of 13 patients, 8 men and 5 women. As a result of measurements made in a total of 32 different regions, especially in the motor and neuropsychiatric areas of the brain, an increase in ADC values was found in all areas. ADC changes of eight localizations such as left corpus callosum, right corona radiata, left corona radiata, hippocampus, right insula, left superior cerebellar peduncle, left caudate nucleus and left putamen were statistically significant. UPDRS III scores improved by 57 % (p <0.05), and Beck and Hamilton depression scores by 25 % and 33 %, respectively (p> 0.05). CONCLUSIONS: This article implicate that bilateral STN-DBS surgery potentially exerts beneficial effects on both motor and neuropsychiatric symptomatology in individuals with PD. We believe that this therapeutic mechanism is hypothesized to involve modulation of diffusion alterations within distinct cerebral tissues.

A Case With Bilateral Hippocampal Infarction Resembling Transient Global Amnesia.

Transient global amnesia (TGA) is a benign and transient condition with a sudden short-term amnesia. One of the conditions resembling TGA is hippocampal infarction, which requires relapse prevention treatments. In this report, we present a case with bilateral hippocampal infarction in whom distinguishing these two conditions was difficult for up to 1 week from the onset. A 60-year-old female visited our hospital with sudden onset retrograde and anterograde amnesia. Thin-slice magnetic resonance imaging (MRI) with 2-mm thickness revealed hyperintense signals on diffusion-weighted imaging (DWI) with signal loss on apparent diffusion coefficient (ADC) on both sides of the hippocampus. MRI with 5-mm thickness on day 7 revealed persistent restricted diffusion on both sides, one of which was still with decreased ADC values. Based on this finding, the diagnosis of bilateral hippocampal infarction was reached, and the relapse-preventive antiplatelet was continued. This case implied the potential difficulty of distinguishing cases with TGA and those with hippocampal infarction based on MRI findings within the first several days after onset. Thin-slice brain MRI, careful search of potential cardiovascular risks, and follow-up MRI ≥ 7 days after onset will be helpful to reach a correct diagnosis in cases with sudden amnesia.

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

Background and purpose: 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). Materials and methods: 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. Results: 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. Conclusion: 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.

Diagnostic performance of ADC and ADCratio in MRI-based prostate cancer assessment: A systematic review and meta-analysis.

OBJECTIVES: To identify factors influencing the diagnostic performance of the quantitative imaging biomarkers ADC and ADCratio in prostate cancer (PCa) detection. MATERIALS AND METHODS: A systematic literature search was conducted in Embase, Medline and Web of Science, for studies evaluating ADC values and ADCratio for PCa diagnosis, using the same patient cohorts and using histopathological references as ground truth. Pooled sensitivities, specificities, summary ROC curves and AUCs were calculated from constructed contingency data tables. Diagnostic performance (AUC) was quantitatively pooled using a bivariate mixed effects model. For identifying influencing factors, subgroup analysis, publication bias and heterogeneity assessment were investigated. RESULTS: Thirteen studies, involving 1038 patients and 1441 lesions, were included. For ADC, the pooled sensitivity and specificity was 80% (95% CI: 74-85%) and 78% (95% CI: 70-85%), respectively. For ADCratio pooled sensitivity and specificity was 80% (95% CI: 74-84%) and 80% (95% CI: 71-87%). Summary ROC analysis revealed AUCs of 0.86 (95% CI: 0.83-0.89) and 0.86 (95% CI: 0.83-0.89), respectively. Meta-regression showed heterogeneity between both imaging biomarkers. Subgroup analysis showed that ADCratio improved diagnostic performance in comparison to ADC when including both peripheral and transitional zone lesions (AUC: 0.87 [95% CI: 0.84-0.90] and 0.82 [95% CI: 0.79-0.85], respectively). CONCLUSION: Both ADC and ADCratio imaging biomarkers showed good and comparable diagnostic performance in PCa diagnosis. However, ADCratio shows better diagnostic performance than ADC in diagnosing transition zone cancers. CLINICAL RELEVANCE STATEMENT: In quantitative MRI-based PCa diagnosis, the imaging biomarker ADCratio is useful in challenging MRI readings of lesions. Understanding the performance of quantitative imaging biomarkers better can aid diagnostic MRI protocols, enhancing the precision of PCa assessments. KEY POINTS: MRI diffusion-weighted imaging-based ADC and ADCratio have comparable diagnostic performance in PCa assessment. In contrast to ADC, the ADCratio improves diagnostic performance, when assessing whole gland lesions. Compared to ADCratio, the ADC demonstrates enhanced diagnostic performance when evaluating peripheral zone lesions.

Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions.

OBJECTIVE: To explore the feasibility and efficacy of clinical-imaging metrics in the diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in prostate imaging-reporting and data system (PI-RADS) category 3 lesions. METHODS: A retrospective analysis was conducted on lesions diagnosed as PI-RADS 3. They were categorized into benign, non-csPCa and csPCa groups. Apparent diffusion coefficient (ADC), T2-weighted imaging signal intensity (T2WISI), coefficient of variation of ADC and T2WISI, prostate-specific antigen density (PSAD), ADC density (ADCD), prostate-specific antigen lesion volume density (PSAVD) and ADC lesion volume density (ADCVD) were measured and calculated. Univariate and multivariate analyses were used to identify risk factors associated with PCa and csPCa. Receiver operating characteristic curve (ROC) and decision curves were utilized to assess the efficacy and net benefit of independent risk factors. RESULTS: Among 202 patients, 133 had benign prostate disease, 25 non-csPCa and 44 csPCa. Age, PSA and lesion location showed no significant differences (P > 0.05) among the groups. T2WISI and coefficient of variation of ADC (ADCcv) were independent risk factors for PCa in PI-RADS 3 lesions, yielding an area under the curve (AUC) of 0.68. ADC was an independent risk factor for csPCa in PI-RADS 3 lesions, yielding an AUC of 0.65. Decision curve analysis showed net benefit for patients at certain probability thresholds. CONCLUSIONS: T2WISI and ADCcv, along with ADC, respectively showed considerable promise in enhancing the diagnosis of PCa and csPCa in PI-RADS 3 lesions.

Total Tumor ADC Histogram Analysis: A New Tool for Predicting High-Risk Cytogenetic Abnormalities in Multiple Myeloma Patients.

RATIONALE AND OBJECTIVES: We explored the feasibility of using total tumor apparent diffusion coefficient (ttADC) histogram parameters to predict high-risk cytogenetic abnormalities (HRCA) in patients with multiple myeloma (MM) and compared the performance of an image prediction model based on these parameters with that of a combined prediction model based on these parameters and clinical indicators. METHODS: We retrospectively analyzed the parameters of the ttADC histogram based on whole-body diffusion-weighted images(WB-DWI) and clinical indicators in 92 patients with MM. The patients were divided into HRCA and non-HRCA groups according to the results of the fluorescence in situ hybridization. Logistic regression analysis was used to construct the image prediction and combined prediction models. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of the models to identify HRCA. The DeLong test was used to compare the AUC differences of each prediction model. RESULTS: Logistic regression analysis results revealed that the ttADC histogram parameter, ttADC entropy < 7.959 (OR: 39.167; 95% confidence interval [CI]: 3.891-394.208; P < 0.05), was an independent risk factor for HRCA. The image prediction model consisted of ttADC entropy and ttADC SD. The combined prediction model included ttADC entropy along with patient clinical indicators such as biological sex and M protein percentage. The AUCs of the image prediction and combined prediction models were 0.739 and 0.811, respectively (P < .05). The image prediction model showed a sensitivity of 73.9% and a specificity of 68.1%. The combined prediction model showed 82.6% sensitivity and 72.5% specificity. CONCLUSIONS: Using ttADC histogram parameters based on WB-DWI images to predict HRCA in patients with MM is feasible, and combining ttADC parameters with clinical indicators can achieve better predictive performance.

Evaluation of preoperative magnetic resonance imaging features and diagnostic effectiveness of grades II and III intracranial solitary fibroma.

OBJECTIVES: To explore the value of preoperative magnetic resonance imaging (MRI) characterization of intracranial solitary fibrous tumors (ISFT) and to evaluate the effectiveness of preoperative MRI features in predicting pathological grading. MATERIALS AND METHODS: This retrospective analysis comprised the clinical and preoperative MRI characterization of 55 patients with ISFT in our hospital, including 27 grade II cases and 28 grade III cases confirmed by postoperative pathology. Variables included age, sex, tumor location, cross-midline status, signal characteristics of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery (T2-FLAIR), and diffusion­weighted imaging (DWI), peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel, maximum tumor diameter, maximum, minimum, and average values of apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumors enhancement mode, meningeal tail sign, skull invasion, cerebral parenchymal invasion, and venous sinus involvement. The independent samples t test or Mann-Whitney U test was performed to compare continuous data between the two groups, and the Pearson chi-squared test or Fisher's exact test was used to compare categorical data. In addition, bivariate logistic regression was performed to construct a comprehensive model, and receiver operating characteristic (ROC) curves were generated to calculate the areas under the curve (AUCs), thereby determining the value of each parameter in the differential diagnosis of grades II and III ISFT. RESULTS: The mean age at onset was similar between patients with grades II and III ISFT (46.77 ± 14.66 years and 45.82 ± 12.07 years, respectively). The proportions of men among patients with grades II and III ISFT were slightly higher than those of female patients (male/female: 1.25 [15/12] and 1.33 [16/12], respectively). There were significant differences between grades II and III ISFT in the T2-FLAIR and DWI signal characteristics, maximum, minimum, and average values of the apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumor location, and skull invasion (P = 0.001, P = 0.018, P = 0.000, P = 0.000, P = 0.000, P = 0.010, and P = 0.032, respectively). However, no significant differences were noted between grades II and III ISFT in age, sex, cross-midline status, T1WI and T2WI signal characteristics, peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel shadow, enhancement mode, meningeal tail sign, maximum tumor diameter, brain parenchyma invasion, or venous sinus involvement (all P > 0.05). Moreover, binary logistic regression analysis showed that the model accuracy was 89.1% when ADCmin was included in the regression equation. Moreover, ROC curve analysis showed that the AUC of ADCmin was 0.805 (0.688, 0.922), sensitivity was 74.1%, specificity was 75.0%, and the cutoff value was 672 mm2/s. CONCLUSIONS: Grade III ISFT patients displayed more mixed T2-FLAIR signal characteristics and DWI signal characteristics than grade II patients, as shown by higher skull invasion and tumor mass collapse midline distribution and lower ADCmax, ADCmean, and ADCmin values. The ADCmin value was significant in the preoperative assignment of grades II and III ISFT, thereby contributing to enhanced accuracy in the imaging grading diagnosis of the disease.

Comparison of apparent diffusion coefficient (ADC) values obtained by echo planar imaging diffusion-weighted imaging (DWI) and radial acquisition regime DWI in low field MRI systems: A phantom study.

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.

Effects of semaglutide, empagliflozin and their combination on renal diffusion-weighted MRI and total kidney volume in patients with type 2 diabetes: a post hoc analysis from a 32 week randomised trial.

AIMS/HYPOTHESIS: The apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI (DWI-MRI) has been proposed as a measure of changes in kidney microstructure, including kidney fibrosis. In advanced kidney disease, the kidneys often become atrophic; however, in the initial phase of type 2 diabetes, there is an increase in renal size. Glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors both provide protection against progression of kidney disease in diabetes. However, the mechanisms are incompletely understood. To explore this, we examined the effects of semaglutide, empagliflozin and their combination on renal ADC and total kidney volume (TKV). METHODS: This was a substudy of a randomised clinical trial on the effects of semaglutide and empagliflozin alone or in combination. Eighty patients with type 2 diabetes and high risk of CVD were randomised into four groups (n=20 in each) receiving either tablet placebo, empagliflozin, a combination of semaglutide and tablet placebo (herein referred to as the 'semaglutide' group), or the combination of semaglutide and empagliflozin (referred to as the 'combination-therapy' group). The semaglutide and the combination-therapy group had semaglutide treatment for 16 weeks and then had either tablet placebo or empagliflozin added to the treatment, respectively, for a further 16 weeks; the placebo and empagliflozin groups were treated with the respective monotherapy for 32 weeks. We analysed the effects of treatment on changes in ADC (cortical, medullary and the cortico-medullary difference [ΔADC; medullary ADC subtracted from cortical ADC]), as well as TKV measured by MRI. RESULTS: Both semaglutide and empagliflozin decreased cortical ADC significantly compared with placebo (semaglutide: -0.20×10-3 mm2/s [95% CI -0.30, -0.10], p<0.001; empagliflozin: -0.15×10-3 mm2/s [95% CI -0.26, -0.04], p=0.01). No significant change was observed in the combination-therapy group (-0.05×10-3 mm2/s [95%CI -0.15, 0.05]; p=0.29 vs placebo). The changes in cortical ADC were not associated with changes in GFR, albuminuria, TKV or markers of inflammation. Further, there were no changes in medullary ADC in any of the groups compared with placebo. Only treatment with semaglutide changed ΔADC significantly from placebo, showing a decrease of -0.13×10-3 mm2/s (95% CI -0.22, -0.04; p=0.01). Compared with placebo, TKV decreased by -3% (95% CI -5%, -0.3%; p=0.04), -3% (95% CI -5%, -0.4%; p=0.02) and -5% (95% CI -8%, -2%; p<0.001) in the semaglutide, empagliflozin and combination-therapy group, respectively. The changes in TKV were associated with changes in GFR, albuminuria and HbA1c. CONCLUSIONS/INTERPRETATION: In a population with type 2 diabetes and high risk of CVD, semaglutide and empagliflozin significantly reduced cortical ADC compared with placebo, indicating microstructural changes in the kidneys. These changes were not associated with changes in GFR, albuminuria or inflammation. Further, we found a decrease in TKV in all active treatment groups, which was possibly mediated by a reduction in hyperfiltration. Our findings suggest that DWI-MRI may serve as a promising tool for investigating the underlying mechanisms of medical interventions in individuals with type 2 diabetes but may reflect effects not related to fibrosis. TRIAL REGISTRATION: European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) 2019-000781-38.

Determination of hemorrhagic transformation risk in acute ischemic cerebrovascular disease: The relationship between ADC values and GRE hemo sequence microhemorrhage.

Background and purpose:

To determine the risk of hemorrhagic transformation in patients with acute ischemic cerebrovascular disease, we investigated the relationship between Apparent Diffusion Coefficient Magnetic Resonance Imaging values measured within the infarct area and microbleeds observed on Gradient Echo Sequence Magnetic Resonance Imaging.

A total of 172 patients who were hospitalized to the Neurology Clinic of the Istanbul Provincial Directorate of Health Erenkoy Mental and Nervous Diseases Training and Research Hospital between June 2019 and March 2020 were included in this cross-sectional study. The patients were classified according to their demographic and clinical characteristics, by age, gender, hypertension, diabetes mellitus, smoking, and alcohol use. In the Cranial Magnetic Resonance Imaging taken in the application for the diagnosis of acute ischemic cerebrovascular disease, the infarction area in Apparent Diffusion Coefficient sequences with the Region of Interest value and the relationship between microhemorrhage observed in Gradient Echo hemo-sequence was evaluated in Magnetic Resonance Imaging applied between 3-7 days. While calculating spherical Region of Interest values, 5 Region of Interest values were obtained for lesions larger than 1.5x1.5 cm, and their arithmetic mean was obtained, and single spherical Region of Interest value was taken for smaller ones. Apparent Diffusion Coefficient Magnetic Resonance Imaging Region of Interest mean values were divided into 2 groups as <500x10–6 mm2 /s and >500x10–6 mm2/s. 

Patients in the group with Apparent Diffusion Coefficient Region of Interest mean values below 500x10-6 mm2/s, had a significantly higher probability for microhemorrhage observes in Gradient Echo Sequence Magnetic Resonance Imaging (p: 0.001) and also more likely to experience microhemorrhage in other areas, which was statistically significant (p: 0.001).The probability of another micro-bleeding observed in patients with microhemorrhage Gradient Echo Sequence Magnetic Resonance Imaging was also statistically significant (p: 0,001). The risk of microbleeding in areas other than ischemia was also found to be significantly higher in patients with microbleeding in the ischemia area in Gradient Echo Sequence Magnetic Resonance Imaging.

In our study, a statistically significant relationship was found between the microhemorrhage in the infarct area and the Apparent Diffusion Coefficient Region of Interest values. When the literature was reviewed, no such study was found to determine the risk of bleeding.

Effects of Multimodal Physical Therapy on Pain, Disability, H-reflex, and Diffusion Tensor Imaging Parameters in Patients With Lumbosacral Radiculopathy Due to Lumbar Disc Herniation: A Preliminary Trial.

Background Lumbosacral radiculopathy (LSR) due to lumbar disc herniation (LDH) is a condition caused by mechanical compression of nerve roots. Various physical therapy interventions have been proposed for the conservative management of LSR due to LDH. However, the study of physical therapy interventions in a multimodal form is lacking. Additionally, the effect of physical therapy on diffusion tensor imaging (DTI) parameters of the compressed nerve root has not been studied. This study aimed to investigate the effects of multimodal physical therapy (MPT) on pain, disability, soleus H-reflex, and DTI parameters of the compressed nerve root in patients with chronic unilateral LSR due to LDH. Methods A prospective preliminary pre-post clinical trial with a convenience sample was conducted. A total of 14 patients with chronic unilateral LSR due to paracentral L4-L5 or L5-S1 LDH were recruited for the study. Participants received a total of 18 sessions of a six-week MPT program that consisted of electrophysical agents, manual therapy interventions, and core stability exercises. Electrophysical agents involved interferential current and hot pack. Manual therapy interventions included myofascial release, side posture positional distraction, passive spinal rotation mobilization, and high-velocity low-amplitude manipulation. Visual analog scale (VAS), Roland-Morris Disability Questionnaire (RMDQ), soleus H-reflex amplitude, side-to-side amplitude (H/H) ratio, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) of the compressed nerve root were measured at baseline and post-intervention. Results There were significant improvements in VAS, RMDQ, H/H ratio, FA, and ADC of the compressed nerve root. Furthermore, significant improvement was found in the affected side compared with the contralateral side in H-reflex amplitude. Conclusions The observations of this preliminary trial suggest that MPT is a successful intervention in patients with chronic unilateral LSR due to LDH. Regarding DTI parameters of the compressed nerve root, FA increased and ADC decreased. Future studies with a control group, large sample sizes, and longer follow-up periods are needed.

Diagnostic efficiency of intravoxel incoherent motion-based virtual magnetic resonance elastography in pulmonary neoplasms.

BACKGROUND: The aim of the study were as below. (1) To investigate the feasibility of intravoxel incoherent motion (IVIM)-based virtual magnetic resonance elastography (vMRE) to provide quantitative estimates of tissue stiffness in pulmonary neoplasms. (2) To verify the diagnostic performance of shifted apparent diffusion coefficient (sADC) and reconstructed virtual stiffness values in distinguishing neoplasm nature. METHODS: This study enrolled 59 patients (37 males, 22 females) with one pulmonary neoplasm who underwent computed tomography-guided percutaneous transthoracic needle biopsy (PTNB) with pathological diagnosis (26 adenocarcinoma, 10 squamous cell carcinoma, 3 small cell carcinoma, 4 tuberculosis and 16 non-specific benign; mean age, 60.81 ± 9.80 years). IVIM was performed on a 3 T magnetic resonance imaging scanner before biopsy. sADC and virtual shear stiffness maps reflecting lesion stiffness were reconstructed. sADC and virtual stiffness values of neoplasm were extracted, and the diagnostic performance of vMRE in distinguishing benign and malignant and detailed pathological type were explored. RESULTS: Compared to benign neoplasms, malignant ones had a significantly lower sADC and a higher virtual stiffness value (P < 0.001). Subsequent subtype analyses showed that the sADC values of adenocarcinoma and squamous cell carcinoma groups were significantly lower than non-specific benign group (P = 0.013 and 0.001, respectively). Additionally, virtual stiffness values of the adenocarcinoma and squamous cell carcinoma subtypes were significantly higher than non-specific benign group (P = 0.008 and 0.001, respectively). However, no significant correlation was found among other subtype groups. CONCLUSIONS: Non-invasive vMRE demonstrated diagnostic efficiency in differentiating the nature of pulmonary neoplasm. vMRE is promising as a new method for clinical diagnosis.

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

PURPOSE: 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). MATERIALS AND METHODS: 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 (< 850 µm2/s), intermediate (850-1100 µm2/s), and high (> 1100 µm2/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. RESULTS: Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59 months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025 µm2/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. CONCLUSION: 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.

MRI for Differentiation between HPV-Positive and HPV-Negative Oropharyngeal Squamous Cell Carcinoma: A Systematic Review.

Human papillomavirus (HPV) is an important risk factor for oropharyngeal squamous cell carcinoma (OPSCC). HPV-positive (HPV+) cases are associated with a different pathophysiology, microstructure, and prognosis compared to HPV-negative (HPV-) cases. This review aimed to investigate the potential of magnetic resonance imaging (MRI) to discriminate between HPV+ and HPV- tumours and predict HPV status in OPSCC patients. A systematic literature search was performed on 15 December 2022 on EMBASE, MEDLINE ALL, Web of Science, and Cochrane according to PRISMA guidelines. Twenty-eight studies (n = 2634 patients) were included. Five, nineteen, and seven studies investigated structural MRI (e.g., T1, T2-weighted), diffusion-weighted MRI, and other sequences, respectively. Three out of four studies found that HPV+ tumours were significantly smaller in size, and their lymph node metastases were more cystic in structure than HPV- ones. Eleven out of thirteen studies found that the mean apparent diffusion coefficient was significantly higher in HPV- than HPV+ primary tumours. Other sequences need further investigation. Fourteen studies used MRI to predict HPV status using clinical, radiological, and radiomics features. The reported areas under the curve (AUC) values ranged between 0.697 and 0.944. MRI can potentially be used to find differences between HPV+ and HPV- OPSCC patients and predict HPV status with reasonable accuracy. Larger studies with external model validation using independent datasets are needed before clinical implementation.

Predicting High-risk Capsular Features in Pleomorphic Adenoma of the Parotid Gland Through a Nomogram Model Based on ADC Imaging.

RATIONALE AND OBJECTIVES: Based on Apparent Diffusion Coefficient (ADC) images, a nomogram model is established to accurately predict the high-risk capsular characteristics associated with pleomorphic adenoma of the parotid gland (PAP) recurrence. MATERIALS AND METHODS: This retrospective study analyzed 190 patients with PAPs. Significant clinical radiological factors were identified through univariate difference analysis and multivariate regression analysis. The optimal threshold was determined by analyzing the average ADC value of the entire tumor, using the best Youden index and sensitivity analysis, and tumor subregions were delineated accordingly. Three radiomic models were constructed for the whole tumor and for high/low ADC areas, with the best model determined through statistical analysis. Ultimately, a nomogram model was constructed by combining the independent predictive factor of high-risk capsular features with the optimal radiomic predictive score. Model performance was comprehensively assessed by the area under the receiver operating characteristic curve (ROC AUC), accuracy, sensitivity, and specificity. RESULTS: The best ADC division threshold as 1.25 × 10-3 mm2/s. Multivariate analysis identified High-ADC Zone Volume Percentage as an independent predictor for PAPs with high-risk capsular characteristics. The radiomic model based on the low ADC tumor subregion was optimal (AUC 0.899). The nomogram model, combining independent predictors and optimal imaging studies predictive score, demonstrated high performance (AUC 0.909). Decision curve analysis confirmed the nomogram's clinical applicability. CONCLUSION: The nomogram model constructed from ADC quantitative imaging can predict PAPs patients with high-risk capsular features. These patients require intraoperative preventive measures to avoid tumor spillage and residuals, as well as extended postoperative follow-up.

A Combination of Amide Proton Transfer, Tumor Blood Flow, and Apparent Diffusion Coefficient Histogram Analysis Is Useful for Differentiating Malignant from Benign Intracranial Tumors in Young Patients: A Preliminary Study.

PURPOSE: To evaluate the amide proton transfer (APT), tumor blood flow (TBF), and apparent diffusion coefficient (ADC) combined diagnostic value for differentiating intracranial malignant tumors (MTs) from benign tumors (BTs) in young patients, as defined by the 2021 World Health Organization classification of central nervous system tumors. METHODS: Fifteen patients with intracranial MTs and 10 patients with BTs aged 0-30 years underwent MRI with APT, pseudocontinuous arterial spin labeling (pCASL), and diffusion-weighted imaging. All tumors were evaluated through the use of histogram analysis and the Mann-Whitney U test to compare 10 parameters for each sequence between the groups. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: The APT maximum, mean, 10th, 25th, 50th, 75th, and 90th percentiles were significantly higher in MTs than in BTs; the TBF minimum (min) was significantly lower in MTs than in BTs; TBF kurtosis was significantly higher in MTs than in BTs; the ADC min, 10th, and 25th percentiles were significantly lower in MTs than in BTs (all p < 0.05). The APT 50th percentile (0.900), TBF min (0.813), and ADC min (0.900) had the highest area under the curve (AUC) values of the parameters in each sequence. The AUC for the combination of these three parameters was 0.933. CONCLUSIONS: The combination of APT, TBF, and ADC evaluated through histogram analysis may be useful for differentiating intracranial MTs from BTs in young patients.

The contrast-free diffusion MRI multiple index for the early prediction of pathological response to neoadjuvant chemotherapy in breast cancer.

Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC-diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T1WI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller-Payne G4/5) and nonmajor histological responders (nMHRs, Miller-Payne G1-3). Three b values were used for DWI to derive the S index; ADC-diff values were obtained using b = 0 and 1000 s/mm2. The different interquartile ranges of percentile S-index and ADC-diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S-index parameters and ADC-diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S-index parameters or ADC-diff values between progesterone receptor positive and negative or for Ki-67 tumors (all P > 0.05). No differences were found in the dynamic contrast-enhanced MRI characteristics between the two groups. HER-2 expression and kurtosis of the S-index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC-diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S-index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC-diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials.

The value of apparent diffusion coefficient values in predicting Gleason grading of low to intermediate-risk prostate cancer.

OBJECTIVES: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) for low to intermediate-risk prostate cancer (PCa), as well as its correlation with the prognostic Gleason score (GS). MATERIALS AND METHODS: Retrospective analysis of MRI images and relevant clinical data from patients with prostate disease. The differences in ADC between different GS groups were compared, and the efficacy of ADC in PCa diagnosis were analyzed. Furthermore, the diagnostic performance of the mean ADC (ADCmean) and minimum ADC (ADCmin) values was compared. RESULTS: There were 1414 patients with 1631 lesions. In terms of GS, both ADCmin and ADCmean values of the GS 4 + 3 group were significantly lower than those of the GS 3 + 4 group, GS 3 + 3 group, and the benign group, with all differences being statistically significant (p < 0.01). The AUC values for diagnosing PCa based on ADCmin and ADCmean were 0.914 and 0.944, respectively. The corresponding diagnostic thresholds were 0.703 × 10-3 mm2/s for ADCmin and 0.927 × 10-3 mm2/s for ADCmean. The magnitudes of ADCmin and ADCmean values exhibited a negative correlation with GS values (ρ = -0.750, p < 0.001; ρ = -0.752, p < 0.001). CONCLUSIONS: ADC values demonstrate an inverse relationship with the invasiveness of PCa, indicating that higher invasiveness is associated with lower ADC values. Additionally, ADC values exhibit high diagnostic potential, sensitivity, and specificity for distinguishing between GS 3 + 4 and GS 4 + 3 lesions. Moreover, the diagnostic value of ADCmean is even more significant, highlighting its crucial role in the diagnosis of low to intermediate-risk PCa. CRITICAL RELEVANCE STATEMENT: ADC values are a valuable tool for distinguishing different levels of aggressiveness in PCa. They help in the preoperative assessment of the biological characteristics of PCa, allowing clinicians to develop personalized treatment strategies, effectively mitigating the risk of unnecessary interventions. KEY POINTS: The preoperative GS is crucial for planning the clinical treatment of PCa. The invasiveness of PCa is inversely correlated with ADC values. ADC values play a crucial role in the accurate preoperative evaluation of low to intermediate-risk PCa, thus aiding clinicians in developing tailored treatment plans.

Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer.

This study systematically reviewed the role of diffusion-weighted imaging (DWI) in the assessment of molecular prognostic biomarkers in breast cancer, focusing on the correlation of apparent diffusion coefficient (ADC) with hormone receptor status and prognostic biomarkers. Our meta-analysis includes data from 52 studies examining ADC values in relation to estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67 status. The results indicated significant differences in ADC values among different receptor statuses, with ER-positive, PgR-positive, HER2-negative, and Ki-67-positive tumors having lower ADC values compared to their negative counterparts. This study also highlights the potential of advanced DWI techniques such as intravoxel incoherent motion and non-Gaussian DWI to provide additional insights beyond ADC. Despite these promising findings, the high heterogeneity among the studies underscores the need for standardized DWI protocols to improve their clinical utility in breast cancer management.

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI.

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays a crucial role in improving patient outcomes. This study introduces a non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the detection and diagnosis of prostate cancer (PCa). IVIM imaging enables the differentiation of water molecule diffusion within capillaries and outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes a two-step segmentation approach through the use of three U-Net architectures for extracting tumor-containing regions of interest (ROIs) from the segmented images. The performance of the CAD system is thoroughly evaluated, considering the optimal classifier and IVIM parameters for differentiation and comparing the diagnostic value of IVIM parameters with the commonly used apparent diffusion coefficient (ADC). The results demonstrate that the combination of central zone (CZ) and peripheral zone (PZ) features with the Random Forest Classifier (RFC) yields the best performance. The CAD system achieves an accuracy of 84.08% and a balanced accuracy of 82.60%. This combination showcases high sensitivity (93.24%) and reasonable specificity (71.96%), along with good precision (81.48%) and F1 score (86.96%). These findings highlight the effectiveness of the proposed CAD system in accurately segmenting and diagnosing PCa. This study represents a significant advancement in non-invasive methods for early detection and diagnosis of PCa, showcasing the potential of IVIM parameters in combination with machine learning techniques. This developed solution has the potential to revolutionize PCa diagnosis, leading to improved patient outcomes and reduced healthcare costs.