Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

PURPOSE: By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). METHODS: A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. RESULTS: There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. CONCLUSIONS: The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Development of real-time individualized risk prediction models for contrast associated acute kidney injury and 30-day dialysis after contrast enhanced computed tomography.

PURPOSE: This study aimed to develop preprocedural real-time artificial intelligence (AI)-based systems for predicting individualized risks of contrast-associated acute kidney injury (CA-AKI) and dialysis requirement within 30 days following contrast-enhanced computed tomography (CECT). METHOD: This single-center, retrospective study analyzed adult patients from emergency or in-patient departments who underwent CECT; 18,895 patients were included after excluding those who were already on dialysis, had stage V chronic kidney disease, or had missing data regarding serum creatinine levels within 7 days before and after CECT. Clinical parameters, laboratory data, medication exposure, and comorbid diseases were selected as predictive features. The patients were randomly divided into model training and testing groups at a 7:3 ratio. Logistic regression (LR) and random forest (RF) were employed to create prediction models, which were evaluated using receiver operating characteristic curves. RESULTS: The incidence rates of CA-AKI and dialysis within 30 days post-CECT were 6.69% and 0.98%, respectively. For CA-AKI prediction, LR and RF exhibited similar performance, with areas under curve (AUCs) of 0.769 and 0.757, respectively. For 30-day dialysis prediction, LR (AUC, 0.863) and RF (AUC, 0.872) also exhibited similar performance. Relative to eGFR-alone, the LR and RF models produced significantly higher AUCs for CA-AKI prediction (LR vs. eGFR alone, 0.769 vs. 0.626, p < 0.001) and 30-day dialysis prediction (RF vs. eGFR alone, 0.872 vs. 0.738, p < 0.001). CONCLUSIONS: The proposed AI prediction models significantly outperformed eGFR-alone for predicting the CA-AKI and 30-day dialysis risks of emergency department and hospitalized patients who underwent CECT.

Cytotoxic Lesions beyond the Corpus Callosum Following Acute Meningoencephalitis and Mycoplasma Pneumoniae Infection: A Case Report and Literature Review.

Cytotoxic lesions of the corpus callosum (CLOCCs) are secondary lesions associated with a variety of clinical causes. The presence of a small and reversible lesion in the splenium of corpus callosum with restricted diffusion on cranial magnetic resonance imaging is the defining feature. The clinical-radiological manifestations have been documented as mild and reversible. Severer presentations were scarcely reported. In this report, we described a 25-year-old man with preceding fever, worsening somnolence, and convulsions. He was diagnosed with acute meningoencephalitis and Mycoplasma pneumoniae infection after workups. After medical treatments, he had neurological deterioration and progressing CLOCCs from a small oval lesion in the center of splenium extending to the whole corpus callosum and bilaterally adjacent white matter. The patient received intravenous methylprednisolone and immunoglobulin successively, and his neurological conditions improved. The CLOCCs, not always mild and reversible, could present with severe clinicoradiological features.

Prediction of poor outcome in stroke patients using radiomics analysis of intraparenchymal and intraventricular hemorrhage and clinical factors.

PURPOSE: To build three prognostic models using radiomics analysis of the hemorrhagic lesions, clinical variables, and their combination, to predict the outcome of stroke patients with spontaneous intracerebral hemorrhage (sICH). MATERIALS AND METHODS: Eighty-three sICH patients were included. Among them, 40 patients (48.2%) had poor prognosis with modified Rankin scale (mRS) of 5 and 6 at discharge, and the prognostic model was built to differentiate mRS ≤ 4 vs. 5 + 6. The region of interest (ROI) of intraparenchymal hemorrhage (IPH) and intraventricular hemorrhage (IVH) were separately segmented. Features were extracted using PyRadiomics, and the support vector machine was applied to select features and build radiomics models based on IPH and IPH + IVH. The clinical models were built using multivariate logistic regression, and then the radiomics scores were combined with clinical variables to build the combined model. RESULTS: When using IPH, the AUC for radiomics, clinical, and combined model was 0.78, 0.82, and 0.87, respectively. When using IPH + IVH, the AUC was increased to 0.80, 0.84, and 0.90, respectively. The combined model had a significantly improved AUC compared to the radiomics by DeLong test. A clinical prognostic model based on the ICH score of 0-1 only achieved AUC of 0.71. CONCLUSIONS: The combined model using the radiomics score derived from IPH + IVH and the clinical factors could achieve a high accuracy in prediction of sICH patients with poor outcome, which may be used to assist in making the decision about the optimal care.

Patient-Specific 3D-Print Extracranial Vascular Simulators and Infrared Imaging Platform for Diagnostic Cerebral Angiography Training.

Tortuous aortic arch is always challenging for beginner neuro-interventionalists. Herein, we share our experience of using 3D-printed extracranial vascular simulators (VSs) and the infrared imaging platform (IRIP) in two training courses for diagnostic cerebral angiography in the past 4 years. A total of four full-scale patient-specific carotid-aortic-iliac models were fabricated, including one type I arch, one bovine variant, and two type III arches. With an angiography machine (AM) as the imaging platform for the practice and final test, the first course was held in March 2018 had 10 participants, including three first-year residents (R1), three second-year residents (R2), and four third-year residents (R3). With introduction of the IRIP as the imaging platform for practice, the second course in March 2022 had nine participants, including 3 R1s, 3 R2s, and 3 R3s. The total manipulation time (TMT) to complete type III aortic arch navigation was recorded. In the first course, the average TMT of the first trial was 13.1 min. Among 3 R1s and 3 R2s attending the second trial, the average TMT of the second trial was 3.4 min less than that of the first trial. In the second course using IRIP, the average TMT of the first and second trials was 6.7 min and 4.8 min, respectively. The TMT of the second trial (range 2.2~14.4 min; median 5.9 min) was significantly shorter than that of the first trial (range 3.6~18 min; median 8.7 min), regardless of whether AM or IRIP was used (p = 0.001). Compared with first trial, the TMT of the second trial was reduced by an average of 3.7 min for 6 R1s, which was significantly greater than the 1.7 min of R2 and R3 (p = 0.049). Patient-specific VSs with radiation-free IRIP could be a useful training platform for junior residents with little experience in neuroangiography.

The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage.

Background: Among patients undergoing head computed tomography (CT) scans within 3 h of spontaneous intracerebral hemorrhage (sICH), 28% to 38% have hematoma expansion (HE) on follow-up CT. This study aimed to predict HE using radiomics analysis and investigate the impact of intraventricular hemorrhage (IVH) compared with the conventional approach based on intraparenchymal hemorrhage (IPH) alone. Methods: This retrospective study enrolled 127 patients with baseline and follow-up non-contrast CT (NCCT) within 4~72 h of sICH. IPH and IVH were outlined separately for performing radiomics analysis. HE was defined as an absolute hematoma growth > 6 mL or percentage growth > 33% of either IPH (HEP) or a combination of IPH and IVH (HEP+V) at follow-up. Radiomic features were extracted using PyRadiomics, and then the support vector machine (SVM) was used to build the classification model. For each case, a radiomics score was generated to indicate the probability of HE. Results: There were 57 (44.9%) HEP and 70 (55.1%) non-HEP based on IPH alone, and 58 (45.7%) HEP+V and 69 (54.3%) non-HEP+V based on IPH + IVH. The majority (>94%) of HE patients had poor early outcomes (death or modified Rankin Scale > 3 at discharge). The radiomics model built using baseline IPH to predict HEP (RMP) showed 76.4% accuracy and 0.73 area under the ROC curve (AUC). The other model using IPH + IVH to predict HEP+V (RMP+V) had higher accuracy (81.9%) with AUC = 0.80, and this model could predict poor outcomes. The sensitivity/specificity of RMP and RMP+V for HE prediction were 71.9%/80.0% and 79.3%/84.1%, respectively. Conclusion: The proposed radiomics approach with additional IVH information can improve the accuracy in prediction of HE, which is associated with poor clinical outcomes. A reliable radiomics model may provide a robust tool to help manage ICH patients and to enroll high-risk ICH cases into anti-expansion or neuroprotection drug trials.

Prediction of Intraparenchymal Hemorrhage Progression and Neurologic Outcome in Traumatic Brain Injury Patients Using Radiomics Score and Clinical Parameters.

(1) Background: Radiomics analysis of spontaneous intracerebral hemorrhages on computed tomography (CT) images has been proven effective in predicting hematoma expansion and poor neurologic outcome. In contrast, there is limited evidence on its predictive abilities for traumatic intraparenchymal hemorrhage (IPH). (2) Methods: A retrospective analysis of 107 traumatic IPH patients was conducted. Among them, 45 patients (42.1%) showed hemorrhagic progression of contusion (HPC) and 51 patients (47.7%) had poor neurological outcome. The IPH on the initial CT was manually segmented for radiomics analysis. After feature extraction, selection and repeatability evaluation, several machine learning algorithms were used to derive radiomics scores (R-scores) for the prediction of HPC and poor neurologic outcome. (3) Results: The AUCs for R-scores alone to predict HPC and poor neurologic outcome were 0.76 and 0.81, respectively. Clinical parameters were used to build comparison models. For HPC prediction, variables including age, multiple IPH, subdural hemorrhage, Injury Severity Score (ISS), international normalized ratio (INR) and IPH volume taken together yielded an AUC of 0.74, which was significantly (p = 0.022) increased to 0.83 after incorporation of the R-score in a combined model. For poor neurologic outcome prediction, clinical variables of age, Glasgow Coma Scale, ISS, INR and IPH volume showed high predictability with an AUC of 0.92, and further incorporation of the R-score did not improve the AUC. (4) Conclusion: The results suggest that radiomics analysis of IPH lesions on initial CT images has the potential to predict HPC and poor neurologic outcome in traumatic IPH patients. The clinical and R-score combined model further improves the performance of HPC prediction.

Solid tumor size for prediction of recurrence in large and giant non-functioning pituitary adenomas.

A subset of large non-functioning pituitary adenomas (lNFPA) and giant non-functioning pituitary adenomas (gNFPA) undergoes early progression/recurrence (P/R) after surgery. This study revealed the clinical and image predictors of P/R in lNFPA and gNFPA, with emphasis on solid tumor size. This retrospective study investigated the preoperative MR imaging features for the prediction of P/R in lNFPA (> 3 cm) and gNFPA (> 4 cm). Only the patients with a complete preoperative brain MRI and undergone postoperative MRI follow-ups for more than 1 year were included. From November 2010 to December 2020, a total of 34 patients diagnosed with lNFPA and gNFPA were included (median follow-up time 47.6 months) in this study. A total of twenty-three (23/34, 67.6%) patients had P/R, and the median time to P/R is 25.2 months. Solid tumor diameter (STD), solid tumor volume (STV), and extent of resection are associated with P/R (p < 0.05). Multivariate analysis showed large STV is a risk factor for P/R (p < 0.05) with a hazard ratio of 30.79. The cutoff points of STD and STV for prediction of P/R are 26 mm and 7.6 cm3, with AUCs of 0.78 and 0.79 respectively. Kaplan-Meier analysis of tumor P/R trends showed that patients with larger STD and STV exhibited shorter progression-free survival (p < 0.05). For lNFPA and gNFPA, preoperative STD and STV are significant predictors of P/R. The results offer objective and valuable information for treatment planning in this subgroup.

Longitudinal alterations of the cisternal segment of trigeminal nerve and brain pain-matrix regions in patients with trigeminal neuralgia before and after treatment.

BACKGROUND: Trigeminal neuralgia (TN) is the most common type of chronic neuropathic facial pain, but the etiology and pathophysiological mechanisms after treatment are still not well understood. The purpose of this study was to investigate the longitudinal changes of the cisternal segment of the trigeminal nerve and brain pain-related regions in patients with TN before and after treatment using readout segmentation of long variable echo-train (RESOLVE) diffusion tensor imaging (DTI) and transverse relaxation (T2)-weighted sampling perfection with application-optimized contrast at different flip angle evolutions (T2-SPACE). METHODS: Twelve patients with TN and four healthy controls were enrolled in this study. All patients underwent assessment of the visual analog scale (VAS), and acquisition of RESOLVE DTI and T2-SPACE images before and at 1, 6, and 12 months after treatments. Regions-of-interest were placed on the bilateral anterior, middle, and posterior parts of the cisternal segment of the trigeminal nerve, the bilateral root entry zone (REZ), bilateral nuclear zone, and the center of pontocerebellar tracts, respectively. Voxel-based morphometry (VBM) analysis was conducted with T2-SPACE images, and gray matter volumes (GMV) were measured from brain pain-matrix regions. RESULTS: The results demonstrated that the VAS scores, the axial diffusivity of the middle part of the affected cisternal trigeminal nerve, the fractional anisotropy of the bilateral nuclear zones, and the mean diffusivity of the center of pontocerebellar tract significantly changed over time before and after treatment. The changes of GMV in the pain-matrix regions exhibited similar trends to the VAS before and after treatment. CONCLUSION: We conclude that magnetic resonance imaging with RESOLVE DTI and VBM with T2-SPACE images were helpful in the understanding of the pathophysiological mechanisms in patients with TN before and after treatment.

Pre-operative MRI Radiomics for the Prediction of Progression and Recurrence in Meningiomas.

Objectives: A subset of meningiomas may show progression/recurrence (P/R) after surgical resection. This study applied pre-operative MR radiomics based on support vector machine (SVM) to predict P/R in meningiomas. Methods: From January 2007 to January 2018, 128 patients with pathologically confirmed WHO grade I meningiomas were included. Only patients who had undergone pre-operative MRIs and post-operative follow-up MRIs for more than 1 year were studied. Pre-operative T2WI and contrast-enhanced T1WI were analyzed. On each set of images, 32 first-order features and 75 textural features were extracted. The SVM classifier was utilized to evaluate the significance of extracted features, and the most significant four features were selected to calculate SVM score for each patient. Results: Gross total resection (Simpson grades I-III) was performed in 93 (93/128, 72.7%) patients, and 19 (19/128, 14.8%) patients had P/R after surgery. Subtotal tumor resection, bone invasion, low apparent diffusion coefficient (ADC) value, and high SVM score were more frequently encountered in the P/R group (p < 0.05). In multivariate Cox hazards analysis, bone invasion, ADC value, and SVM score were high-risk factors for P/R (p < 0.05) with hazard ratios of 7.31, 4.67, and 8.13, respectively. Using the SVM score, an AUC of 0.80 with optimal cutoff value of 0.224 was obtained for predicting P/R. Patients with higher SVM scores were associated with shorter progression-free survival (p = 0.003). Conclusions: Our preliminary results showed that pre-operative MR radiomic features may have the potential to offer valuable information in treatment planning for meningiomas.

Prediction of mTICI 3 recanalization and clinical outcomes in endovascular thrombectomy for acute ischemic stroke: a retrospective study in the Taiwan registry.

PURPOSE: Early recanalization for acute ischemic stroke (AIS) due to large vessel occlusion (LVO) by endovascular thrombectomy (EVT) is strongly related to improved functional outcomes. With data obtained from the Taiwan registry, the factors associated with mTICI 3 recanalization and clinical outcomes in EVT are investigated. METHODS: From January 2014 to September 2016, 108 patients who underwent EVT for AIS due to LVO in 11 medical centers throughout Taiwan were included. Complete recanalization is defined as achieving modified thrombolysis in cerebral infarction (mTICI) grade 3. Good clinical outcomes are defined by the modified Rankin scale (mRS) 0-2 at 3 months after EVT. Clinical and imaging parameters for predicting mTICI 3 recanalization and good clinical outcomes are analyzed. RESULTS: Of the 108 patients who received EVT, 54 (50%) patients had mTICI 3 recanalization. Having received aspiration only and the use of IV-tPA are shown to be significant predictors for mTICI 3 recanalization with odds ratios of 2.61 and 2.53 respectively. Forty-six (42.6%) patients experienced good 3-month clinical outcomes (mRS 0-2). Pretreatment collateral statuses, NIHSS scores, time lapses between symptoms to needle, and the occurrence of hemorrhage at 24 h are all significant predictors for good outcomes with odds ratios of 2.88, 0.91, 0.99, and 0.31 respectively. CONCLUSIONS: Prediction of mTICI 3 recanalization and clinical outcomes offer valuable clinical information for treatment planning in EVT.

Correlation of internal carotid artery diameter and carotid flow with asymmetry of the circle of Willis.

BACKGROUND: The purpose of this study was to clarify the effect of asymmetric COW variants on carotid flow changes, and proposed an easy estimate of the representative carotid flow volume for accurate numerical simulation. METHODS: A total of 210 healthy adults receiving magnetic resonance angiography and carotid duplex sonography were included. Three anterior cerebral artery asymmetry (AA) groups were defined based on the diameter ratio difference (DRD) of bilateral A1 segments: AA1 group, one-side A1 aplasia; AA2, A1 DRD ≥ 50%; AA3, A1 DRD between 10 and 50%. Similarly, 3 posterior communicating artery (PcomA) asymmetry (PA) groups were defined: PA1 group, one fetal-origin posterior cerebral artery and absent contralateral PcomA; PA2, PcomA DRD ≥ 50%; PA3, PcomA DRD between 10 and 50%. RESULTS: With A1 asymmetry, the ICA diameter of the dominant A1 is significantly greater than the contralateral side. Significant differences of bilateral ICA flow were present in the AA1 and AA2 groups (mean flow difference 42.9 and 30.7%, respectively). Significant bilateral ICA diameter and flow differences were only found in the PA1 group. Linear regression analysis of ICA diameter and flow found a moderately positive correlation between ICA diameter and flow in all AA groups, with a 1 mm increment in vessel diameter corresponding to a 62.6 ml increment of flow volume. The product of bilateral ICA diameter and flow volume difference (ICA-PDF) could be a potential discriminator with a cutoff of 4.31 to predict A1 asymmetry ≥50% with a sensitivity of 0.81 and specificity of 0.76. CONCLUSIONS: The study verifies that A1 asymmetry causes unequal bilateral carotid inflow, and consequently different bilateral ICA diameters. Adjustment of the inflow boundary conditions according to the COW variants would be necessary to improve the accuracy of numerical simulation.

Magnetic-Resonance Diffusion-Tensor Tractography in the Diagnosis of Tumefactive Spinal-Cord Lesions in Neuromyelitis Optica.

Magnetic-resonance (MR) imaging is the modality of choice for the evaluation of spinal-cord lesions. However, challenges persist in discriminating demyelinating processes from neoplastic lesions using conventional MR sequences. Consequently, an invasive spinal-cord biopsy is likely for most patients. MR diffusion-tensor imaging is an emerging noninvasive and powerful method for characterizing changes in tissue microstructure associated with spinal disorders. We currently present the case of a middle-aged woman suffering from neuromyelitis optica, and highlight that MR diffusion-tensor tractography can be helpful in the identification of tumefactive spinal-cord lesions.

Discrepancy between two-dimensional and three-dimensional digital subtraction angiography for the planning of endovascular coiling of small cerebral aneurysms <5 mm.

BACKGROUND: To investigate the discrepancy between two-dimensional digital subtraction angiography and three-dimensional rotational angiography for small (<5 mm) cerebral aneurysms and the impact on decision making among neuro-interventional experts as evaluated by online questionnaire. MATERIALS AND METHODS: Eight small (<5 mm) ruptured aneurysms were visually identified in 16 image sets in either two-dimensional or three-dimensional format for placement in a questionnaire for 11 invited neuro-interventionalists. For each set, two questions were posed: Question 1: "Which of the following is the preferred treatment choice: simple coiling, balloon remodeling or stent assisted coiling?"; Question 2: "Is it achievable to secure the aneurysm with pure simple coiling?" The discrepancies of angio-architecture parameters and treatment choices between two-dimensional-digital subtraction angiography and three-dimensional rotational angiography were evaluated. RESULTS: In all eight cases, the neck images via three-dimensional rotational angiography were larger than two-dimensional-digital subtraction angiography with a mean difference of 0.95 mm. All eight cases analyzed with three-dimensional rotational angiography, but only one case with two-dimensional-digital subtraction angiography were classified as wide-neck aneurysms with dome-to-neck ratio < 1.5. The treatment choices based on the two-dimensional or three-dimensional information were different in 56 of 88 (63.6%) paired answers. Simple coiling was the preferred choice in 66 (75%) and 26 (29.6%) answers based on two-dimensional and three-dimensional information, respectively. Three types of angio-architecture with a narrow gap between the aneurysm sidewall and parent artery were proposed as an explanation for neck overestimation with three-dimensional rotational angiography. CONCLUSIONS: Aneurysm neck overestimation with three-dimensional rotational angiography predisposed neuro-interventionalists to more complex treatment techniques. Additional two-dimensional information is crucial for endovascular treatment planning for small cerebral aneurysms.

Radiomics approach for prediction of recurrence in skull base meningiomas.

PURPOSE: A subset of skull base meningiomas (SBM) may show early progression/recurrence (P/R) as a result of incomplete resection. The purpose of this study is the implementation of MR radiomics to predict P/R in SBM. METHODS: From October 2006 to December 2017, 60 patients diagnosed with pathologically confirmed SBM (WHO grade I, 56; grade II, 3; grade III, 1) were included in this study. Preoperative MRI including T2WI, diffusion-weighted imaging (DWI), and contrast-enhanced T1WI were analyzed. On each imaging modality, 13 histogram parameters and 20 textural gray level co-occurrence matrix (GLCM) features were extracted. Random forest algorithms were utilized to evaluate the importance of these parameters, and the most significant three parameters were selected to build a decision tree for prediction of P/R in SBM. Furthermore, ADC values obtained from manually placed ROI in tumor were also used to predict P/R in SBM for comparison. RESULTS: Gross-total resection (Simpson Grades I-III) was performed in 33 (33/60, 55%) patients, and 27 patients received subtotal resection. Twenty-one patients had P/R (21/60, 35%) after a postoperative follow-up period of at least 12 months. The three most significant parameters included in the final radiomics model were T1 max probability, T1 cluster shade, and ADC correlation. In the radiomics model, the accuracy for prediction of P/R was 90%; by comparison, the accuracy was 83% using ADC values measured from manually placed tumor ROI. CONCLUSIONS: The results show that the radiomics approach in preoperative MRI offer objective and valuable clinical information for treatment planning in SBM.

Prediction of recurrence in solid nonfunctioning pituitary macroadenomas: additional benefits of diffusion-weighted MR imaging.

OBJECTIVE: A subset of benign, nonfunctioning pituitary macroadenomas (NFMAs) has been shown to undergo early progression/recurrence (P/R) during the first years after surgical resection. The aim of this study was to determine preoperative MR imaging features for the prediction of P/R in benign solid NFMAs, with emphasis on apparent diffusion coefficient (ADC) values. METHODS: We retrospectively investigated the preoperative MR imaging features for the prediction of P/R in benign solid NFMAs. Only the patients who had undergone preoperative MRI and postoperative MRI follow-ups for more than 1 year (at least every 6-12 months) were included. From November 2010 to December 2016, a total of 30 patients diagnosed with benign solid NFMAs were included (median follow-up time 45 months), and 19 (63.3%) patients had P/R (median time to P/R 24 months). RESULTS: Benign solid NFMAs with cavernous sinus invasion, failed chiasmatic decompression, large tumor height and tumor volume, high diffusion-weighted imaging (DWI) signal, and lower ADC values/ratios were significantly associated with P/R (p < 0.05). The cutoff points of ADC value and ADC ratio for prediction of P/R are 0.77 × 10-3 mm2/sec and 1.01, respectively, with area under the curve (AUC) values (0.9 and 0.91) (p < 0.01). In multivariate Cox proportional hazards analysis, low ADC value (< 0.77 × 10-3 mm2/sec) is a high-risk factor of P/R (p < 0.05) with a hazard ratio of 14.07. CONCLUSIONS: Benign solid NFMAs with low ADC values/ratios are at a significantly increased risk of P/R, and aggressive treatments accompanied by close follow-up with imaging studies should be considered.

Prediction of Recurrence in Parasagittal and Parafalcine Meningiomas: Added Value of Diffusion-Weighted Magnetic Resonance Imaging.

BACKGROUND: Parasagittal and parafalcine (PSPF) meningiomas recur more frequently than other intracranial meningiomas owing to the difficulty in achieving gross total resection. The present study investigated the preoperative magnetic resonance imaging (MRI) features for the prediction of progression/recurrence (P/R) in benign PSPF meningiomas with an emphasis on the apparent diffusion coefficient (ADC) values. METHODS: We retrospectively investigated the preoperative MRI features for the prediction of P/R in benign (World Health Organization grade I) PSPF meningiomas. Only patients who had undergone preoperative and postoperative MRI follow-up studies for ≥1 year were included. From October 2006 to December 2015, 48 patients with a diagnosis of benign PSPF meningioma were included (median follow-up period, 42.5 months). Of these 48 patients, 12 (25%) developed P/R (median time to P/R, 23 months). RESULTS: PSPF meningiomas in male patients, subtotal resection, large tumor diameter, high diffusion-weighted imaging signal, and lower ADC values or ratios were significantly associated with P/R (P < 0.05). The cutoff points of the ADC value and ADC ratio for the prediction of P/R were 0.83 × 10-3 mm2/second and 0.99, with an area under the curve of 0.82 and 0.83, respectively (P = 0.001). On multivariate Cox proportional hazards analysis, male sex and low ADC values (<0.83 × 10-3 mm2/second) were high-risk factors for P/R, with a hazard ratio of 12.37 and 30.2, respectively (P < 0.05). Kaplan-Meier analysis showed that lower ADC values and ratios predicted for significantly shorter progression-free survival (P < 0.05). CONCLUSIONS: The preoperative ADC values and ratios for the prediction of P/R offer additional valuable information for the treatment planning for PSPF meningiomas.

Added value of delayed computed tomography angiography in primary intracranial hemorrhage and hematoma size for predicting spot sign.

Background The computed tomography angiography (CTA) spot sign represents active contrast extravasation within acute primary intracerebral hemorrhage (ICH) and is an independent predictor of hematoma expansion (HE) and poor clinical outcomes. The spot sign could be detected on first-pass CTA (fpCTA) or delayed CTA (dCTA). Purpose To investigate the additional benefits of dCTA spot sign in primary ICH and hematoma size for predicting spot sign. Material and Methods This is a retrospective study of 100 patients who underwent non-contrast CT (NCCT) and CTA within 24 h of onset of primary ICH. The presence of spot sign on fpCTA or dCTA, and hematoma size on NCCT were recorded. The spot sign on fpCTA or dCTA for predicting significant HE, in-hospital mortality, and poor clinical outcomes (mRS ≥ 4) are calculated. The hematoma size for prediction of CTA spot sign was also analyzed. Results Only the spot sign on dCTA could predict high risk of significant HE and poor clinical outcomes as on fpCTA ( P < 0.05). With dCTA, there is increased sensitivity and negative predictive value (NPV) for predicting significant HE, in-hospital mortality, and poor clinical outcomes. The XY value (product of the two maximum perpendicular axial dimensions) is the best predictor (area under the curve [AUC] = 0.82) for predicting spot sign on fpCTA or dCTA in the absence of intraventricular and subarachnoid hemorrhage. Conclusion This study clarifies that dCTA imaging could improve predictive performance of CTA in primary ICH. Furthermore, the XY value is the best predictor for CTA spot sign.

Quantitative Magnetic Resonance Diffusion-Weighted Imaging Evaluation of the Supratentorial Brain Regions in Patients Diagnosed with Brainstem Variant of Posterior Reversible Encephalopathy Syndrome: A Preliminary Study.

BACKGROUND AND PURPOSE: Posterior reversible encephalopathy syndrome (PRES) is a clinicoradiologic entity with several causes, characterized by rapid onset of symptoms and typical neuroimaging features, which usually resolve if promptly recognized and treated. Brainstem variant of PRES presents with vasogenic edema in brainstem regions on magnetic resonance (MR) images and there is sparing of the supratentorial regions. Because PRES is usually caused by a hypertensive crisis, which would likely have a systemic effect and global manifestations on the brain tissue, we thus proposed that some microscopic abnormalities of the supratentorial regions could be detected with diffusion-weighted imaging (DWI) using apparent diffusion coefficient (ADC) analysis in brainstem variant of PRES and hypothesized that "normal-looking" supratentorial regions will increase water diffusion. METHODS: We retrospectively identified patients with PRES who underwent brain magnetic resonance imaging studies. We identified 11 brainstem variants of PRES patients, who formed the study cohort, and 11 typical PRES patients and 20 normal control subjects as the comparison cohorts for this study. Nineteen regions of interest were drawn and systematically placed. The mean ADC values were measured and compared among these 3 groups. RESULTS: ADC values of the typical PRES group were consistently elevated compared with those in normal control subjects. ADC values of the brainstem variant group were consistently elevated compared with those in normal control subjects. ADC values of the typical PRES group and brainstem variant group did not differ significantly, except for the pons area. CONCLUSIONS: Quantitative MR DWI may aid in the evaluation of supratentorial microscopic abnormalities in brainstem variant of PRES patients.