Multiparametric simultaneous hybrid 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) incorporating intratumoral and peritumoral regions for grading of glioma.

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.

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.

Dysarthria as a Presenting Symptom With Rapidly Progressive Imaging Features in Sporadic Creutzfeldt-Jakob Disease: A Case Report.

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.

Evaluating the added value of synthetic magnetic resonance imaging in predicting sentinel lymph node status in breast cancer.

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.

Comparison of the monoexponential and biexponential models of diffusion-weighted magnetic imaging in grading clear-cell renal cell carcinoma: a case-control study.

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.

Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy.

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.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling.

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.

Higher perfusion of rectum carcinoma relative to tumor-free rectal wall: quantification by a new imaging biomarker diffusion-derived vessel density (DDVD).

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.

Effect of contrast agent on T2-weighted fat-suppressed imaging and diffusion-weighted imaging in the diagnosis of breast tumors.

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.

Radiological insights into rheumatoid meningitis - a rare central nervous system manifestation of rheumatoid arthritis: a retrospective review of six cases.

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.

A Rare and Challenging Presentation of Acute Hemorrhagic Leukoencephalitis With Tumefactive Demyelinating Lesions in a 41-Year-Old Male.

Acute hemorrhagic leukoencephalitis (AHLE) is a rare and severe inflammatory condition of the central nervous system (CNS), characterized by hemorrhagic lesions in the brain's white matter. Here, we present a case of AHLE with concurrent tumefactive demyelinating disease, highlighting the diagnostic and management challenges associated with this complex presentation. Tumefactive multiple sclerosis (MS) is a rare variant of MS characterized by large, space-occupying lesions in the CNS. Concurrently, hemorrhagic leukoencephalitis (HLE) represents a severe inflammatory disorder characterized by hemorrhagic lesions within the CNS white matter. The diagnosis of tumefactive MS with associated HLE posed significant diagnostic challenges due to overlapping clinical and radiological features. Management involved high-dose corticosteroid therapy and supportive care measures, with longitudinal follow-up to assess treatment response and prevent complications. The patient exhibited a favorable clinical response to treatment, with gradual improvement in symptoms and resolution of radiological abnormalities. The coexistence of tumefactive MS with HLE is exceptionally rare and presents diagnostic and therapeutic challenges. We report a 41-year-old male presenting with acute neurological symptoms, including severe headache, confusion, left-sided body weakness, slurred speech, and blurred vision. Neurological examination revealed dysarthric speech, right homonymous hemianopia, left upper motor neuron facial palsy, and motor deficits. MRI demonstrated multifocal areas of T2 hyperintensity with associated hemorrhage, suggestive of tumefactive MS with associated HLE. Diagnostic workup included neurological examination, MRI imaging, cerebrospinal fluid analysis, and serological testing. Management involved high-dose corticosteroid therapy and supportive care measures. The patient exhibited a favorable clinical response to treatment, with gradual improvement in symptoms and resolution of radiological abnormalities. Longitudinal follow-up confirmed sustained improvement. In conclusion, the coexistence of tumefactive MS with HLE poses diagnostic challenges due to overlapping features. This case underscores the importance of considering rare and atypical presentations of CNS demyelinating disease and the potential complications, including associated HLE. Comprehensive evaluation, multidisciplinary collaboration, and individualized management are essential for optimizing outcomes in patients with complex CNS inflammatory disorders.

Evaluation of magnetic resonance imaging for bladder cancer detection following transurethral resection of bladder tumour (TURBT).

PURPOSE: To evaluate the performance of MRI for detection of bladder cancer following transurethral resection of bladder tumour (TURBT). METHODS: This single-centre retrospective study included forty-one consecutive patients with bladder cancer who underwent bladder MRI after TURBT. Two uroradiologists retrospectively assessed the presence of tumour using bladder MRI with and without DWI (diffusion weighted imaging) using a five-point Likert scale. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated and inter-reader agreement was assessed. Histopathology was used as the reference standard. RESULTS: 24 out of 41 patients (58.5%) had no residual tumour or Tis (carcinoma in situ) after TURBT. Sensitivity, specificity, PPV and NPV for detection of tumour using T1WI (T1-weighted imaging) and T2WI (T2-weighted imaging) was 50.0%, 54.6%, 21.1%, and 81.8%, respectively and for T1WI, T2WI and DWI combined was 100%, 76.5%, 50.0% and 100%, respectively. Overestimation of tumour was more common than underestimation. MRI showed high accuracy for patients in whom there was no residual tumour (78.9%). Inter-reader agreement for tumour detection improved from fair (κ = 0.54) to moderate (κ = 0.70) when DWI was included. CONCLUSION: Non-contrast MRI with DWI showed high sensitivity and relatively high specificity for detection of residual tumour after TURBT. Inter-reader agreement improved from fair to moderate with the addition of DWI. MRI can be useful after TURBT in order to guide further management.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma.

Background and purpose: Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response. Materials and methods: Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease. Results: ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed. Conclusion: The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

Comparison of conventional diffusion-weighted imaging, diffusion kurtosis imaging and intravoxel incoherent motion in characterization of sonographically indeterminate adnexal masses.

PURPOSE: To evaluate the role of conventional diffusion weighted imaging, diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) in distinguishing benign from malignant adnexal masses. METHODS: 38 patients with 45 adnexal masses were enrolled in this prospective study and assessed with multiparametric MRI, including the IVIM-DKI sequence, on a 3 T MRI system. The mean apparent diffusion coefficient (ADC) from conventional DWI, the apparent diffusion coefficient derived from DKI (Dapp), the apparent kurtosis coefficient (Kapp), true diffusion coefficient (Dt), perfusion fraction (f) and pseudo-diffusion coefficient (Dp) were measured. RESULTS: The mean ADC, Dapp, and Dt were significantly higher in benign adnexal masses than in malignant adnexal masses (p < 0.001). f and Dp were also significantly higher in benign adnexal masses, with p values of 0.026 and 0.002, respectively. Kapp was higher in malignant masses (p < 0.001). Among mean ADC, Dapp, and Dt, mean ADC had the highest area under the curve (AUC) of 0.885. However, no statistically significant differences were observed between the ROCs of various diffusion parameters. CONCLUSION: The mean ADC, Dapp, and Kapp are useful parameters in discriminating between benign and malignant adnexal masses. Dt derived from IVIM also helps in distinguishing benign and malignant adnexal masses; however, no incremental role of IVIM and DKI over ADC could be identified in our study.

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links Through Daily Activity Patterns and Brain Connectivity Analysis.

BACKGROUND: Better understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors. METHODS: Resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry. RESULTS: We found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs. CONCLUSIONS: Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

Diagnostic efficacy and interobserver agreement among readers with variable experience of the Prostate Imaging for Recurrence Reporting system with whole-mount histology after androgen deprivation therapy as a reference.

Background: The Prostate Imaging for Recurrence Reporting (PI-RR) system was recently proposed to assess the local recurrence of prostate cancer (PCa), but its exact performance for the prostate after radiotherapy or radical prostatectomy is difficult to determine. We aimed to evaluate the diagnostic performance and interreader agreement of this system using whole-mount histology of the prostate after androgen deprivation therapy (ADT) as the standard of reference. Methods: In total, 119 patients with PCa post-ADT underwent multiparametric magnetic resonance imaging (mp-MRI) before prostatectomy. Three radiologists analyzed the MRI images independently, scoring imaging findings according to PI-RR. Spearman correlation was performed to assess the relationship between the percentage of sectors with residual cancer and PI-RR score. The diagnostic performance for detection of residual cancer was assessed on a per-sector basis. The chi-squared test was used to compare the cancer detection rate (CDR) among readers. Overall and pairwise interreader agreement in assigning PI-RR categories and residual cancer sectors with a score ≥3 or ≥4 were evaluated with the Cohen kappa coefficient. Results: Histology revealed 209 sectors with residual cancer. The percentage of pathologically positive sectors increased with the increase in PI-RR score for all readers. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at a cutoff of score 3 ranged from 74.2% to 83.7%, 86.4% to 92.7%, 51.3% to 64.3%, and 95.4% to 96.9%, respectively, and at a cutoff of score 4, they ranged from 47.4% to 56.5%, 97.9% to 98.6%, 82.5% to 85.3%, and 91.6% to 92.9%, respectively. There was no significant difference among the CDR of readers. In PI-RR categories and detection of residual cancer sectors, overall interreader agreement was moderate for all readers, but agreement was higher between the more experienced readers (moderate to substantial) than between the more and less experienced readers (fair to moderate). Conclusions: MRI scoring with the PI-RR assessment provided accurate evaluation of PCa after ADT, but readers' experience influenced interreader agreement and cancer diagnosis.

Diagnostic accuracy of diffusion weighted MRI in differentiating malignant from benign liver lesions taking histopathology as gold standard.

Objective: To determine the diagnostic accuracy of Diffusion Weighted MRI in differentiating malignant from benign liver lesions taking histopathology as gold standard. Methods: This Cross-sectional study was conducted at Departments of Radiology and Medicine, JPMC, Karachi from February 23, 2019 till September 25, 2019. Data was prospectively collected from patients after taking consent. One hundred twenty five patients presenting with hepatic mass who met the inclusion criteria were included. Quantitative data was presented as simple descriptive statistics giving mean and standard deviation and qualitative variables as frequency and percentages. Sensitivity, specificity, positive and negative predictive values and diagnostic accuracy were calculated. P-value of ≤0.05 was considered as significant. Results: Mean age in our study was 59.75±8.57 years. Total 71 (56.8%) were male and 54 (43.2%) were female. Out of 125 patients, sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of DW MRI for the diagnosis of malignant focal liver lesion by taking histopathology as gold standard was found to be 92.3%, 93.6%, 96%, 88% and 92.8% respectively. Conclusion: DW MRI scan has high diagnostic accuracy and being accurate in making a diagnosis and differentiation of benign from malignant focal liver lesion would decrease need of invasive modality of histopathology.

Predicting long-term outcomes for acute ischemic stroke using multi-model MRI radiomics and clinical variables.

Purpose: The objective of this study was to create and validate a novel prediction model that incorporated both multi-modal radiomics features and multi-clinical features, with the aim of accurately identifying acute ischemic stroke (AIS) patients who faced a higher risk of poor outcomes. Methods: A cohort of 461 patients diagnosed with AIS from four centers was divided into a training cohort and a validation cohort. Radiomics features were extracted and selected from diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images to create a radiomic signature. Prediction models were developed using multi-clinical and selected radiomics features from DWI and ADC. Results: A total of 49 radiomics features were selected from DWI and ADC images by the least absolute shrinkage and selection operator (LASSO). Additionally, 20 variables were collected as multi-clinical features. In terms of predicting poor outcomes in validation set, the area under the curve (AUC) was 0.727 for the DWI radiomics model, 0.821 for the ADC radiomics model, 0.825 for the DWI + ADC radiomics model, and 0.808 for the multi-clinical model. Furthermore, a prediction model was built using all selected features, the AUC for predicting poor outcomes increased to 0.86. Conclusion: Radiomics features extracted from DWI and ADC images can serve as valuable biomarkers for predicting poor clinical outcomes in patients with AIS. Furthermore, when these radiomics features were combined with multi-clinical features, the predictive performance was enhanced. The prediction model has the potential to provide guidance for tailoring rehabilitation therapies based on individual patient risks for poor outcomes.

Comparison of continuous-time random walk and fractional order calculus models in characterizing breast lesions using histogram analysis.

OBJECTIVE: To compare the diagnostic performance of different mathematical models for DWI and explore whether parameters reflecting spatial and temporal heterogeneity can demonstrate better diagnostic accuracy than the diffusion coefficient parameter in distinguishing benign and malignant breast lesions, using whole-tumor histogram analysis. METHODS: This retrospective study was approved by the institutional ethics committee and included 104 malignant and 42 benign cases. All patients underwent breast magnetic resonance imaging (MRI) with a 3.0 T MR scanner using the simultaneous multi-slice (SMS) readout-segment ed echo-planar imaging (rs-EPI). Histogram metrics of Mono- apparent diffusion coefficient (ADC), CTRW, and FROC-derived parameters were compared between benign and malignant breast lesions, and the diagnostic performance of each diffusion parameter was evaluated. Statistical analysis was performed using Mann-Whitney U test and receiver operating characteristic (ROC) curve. RESULTS: The DFROC-median exhibited the highest AUC for distinguishing benign and malignant breast lesions (AUC = 0.965). The temporal heterogeneity parameter αCTRW-median generated a statistically higher AUC compared to the spatial heterogeneity parameter ßCTRW-median (AUC = 0.850 and 0.741, respectively; p = 0.047). Finally, the combination of median values of CTRW parameters displayed a slightly higher AUC than that of FROC parameters, with no significant difference however (AUC = 0.971 and 0.965, respectively; p = 0.172). CONCLUSIONS: The diffusion coefficient parameter exhibited superior diagnostic performance in distinguishing breast lesions when compared to the temporal and spatial heterogeneity parameters.

Impact of Image Enhancement on the Radiomics Stability of Diffusion-Weighted MRI Images of Cervical Cancer.

The diffusion-weighted imaging (DWI) technique is known for its capability to differentiate the diffusion of water molecules between cancerous and non-cancerous cervix tissues, which enhances the accuracy of detection. Despite the potential of DWI-MRI, its accuracy is limited by technical factors influencing in vivo data acquisition, thus impacting the quantification of radiomics features. This study aimed to measure the radiomics stability of manual and semi-automated segmentation on contrast limited adaptive histogram equalization (CLAHE)-enhanced DWI-MRI cervical images. Eighty diffusion-weighted MRI images were obtained from patients diagnosed with cervical cancer, and an active contour model was used to analyze the data. Radiomics analysis was conducted to extract the first statistical order, shape, and textural features with intraclass correlation coefficient (ICC) measurement. The results of the CLAHE segmentation approach showed a marked improvement when compared to the manual and semi-automated segmentation methods, with an ICC value of 0.990 ± 0.005 (p<0.05), compared to 0.864 ± 0.033 (p<0.05) and 0.554 ± 0.185 (p>0.05), respectively. The CLAHE segmentation displayed a higher level of robustness than the manual groups in terms of the features present in both categories. Thus, CLAHE segmentation is owing to its potential to generate radiomics features that are more durable and consistent.