Spontaneous rupture of a uterine leiomyoma accompanied by a hematoma appearing as a cystic lesion on imaging: A case report.

The rupture of a uterine leiomyoma is a rare complication. We report a case of ruptured leiomyoma that formed a hematoma that was initially suggestive of an ovarian origin. Magnetic resonance imaging revealed intact ovaries and a cystic lesion adjacent to leiomyomas. During surgery, the cystic lesion was found to be a hematoma caused by a rupture of the leiomyoma.

Differentiation between pleomorphic adenoma and schwannoma in the parapharyngeal space: histogram analysis of apparent diffusion coefficient.

OBJECTIVES: To elucidate the differences between pleomorphic adenomas and schwannomas occurring in the parapharyngeal space by histogram analyses of apparent diffusion coefficient (ADC) values measured with diffusion-weighted MRI. METHODS: This retrospective study included 29 patients with pleomorphic adenoma and 22 patients with schwannoma arising in the parapharyngeal space or extending into the parapharyngeal space from the parotid region. Using pre-operative MR images, ADC values of tumor lesions showing the maximum diameter were measured. The regions of interest for ADC measurement were placed by contouring the tumor margin, and the histogram metrics of ADC values were compared between pleomorphic adenomas and schwannomas regarding the mean, skewness, and kurtosis by Wilcoxon's rank sum test. Subsequent to the primary analysis which included all lesions, we performed two subgroup analyses regarding b-values and magnetic field strength used for MRI. RESULTS: The mean ADC values did not show significant differences between pleomorphic adenomas and schwannomas for the primary and subgroup analyses. Schwannomas showed higher skewness (p = 0.0001) and lower kurtosis (p = 0.003) of ADC histograms compared with pleomorphic adenomas in the primary analysis. Skewness was significantly higher in schwannomas in all the subgroup analyses. Kurtosis was consistently lower in schwannomas but did not reach statistical significance in one subgroup analysis. CONCLUSIONS: Skewness and kurtosis showed significant differences between pleomorphic adenomas and schwannomas occupying the parapharyngeal space, but the mean ADC values did not. Our results suggest that the skewness and kurtosis of ADC histograms may be useful in differentiating these two parapharyngeal tumors.

Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer.

PURPOSE: To assess the possibility of reducing the image acquisition time for diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) by denoising with deep learning-based reconstruction (dDLR). METHODS: Seventeen patients with prostate cancer who underwent DWIBS by 1.5 T magnetic resonance imaging with a number of excitations of 2 (NEX2) and 8 (NEX8) were prospectively enrolled. The NEX2 image data were processed by dDLR (dDLR-NEX2), and the NEX2, dDLR-NEX2, and NEX8 image data were analyzed. In qualitative analysis, two radiologists rated the perceived coarseness, conspicuity of metastatic lesions (lymph nodes and bone), and overall image quality. The contrast-to-noise ratios (CNRs), contrast ratios, and mean apparent diffusion coefficients (ADCs) of metastatic lesions were calculated in a quantitative analysis. RESULTS: The image acquisition time of NEX2 was 2.8 times shorter than that of NEX8 (3 min 30 s vs 9 min 48 s). The perceived coarseness and overall image quality scores reported by both readers were significantly higher for dDLR-NEX2 than for NEX2 (P = 0.005-0.040). There was no significant difference between dDLR-NEX2 and NEX8 in the qualitative analysis. The CNR of bone metastasis was significantly greater for dDLR-NEX2 than for NEX2 and NEX8 (P = 0.012 for both comparisons). The contrast ratios and mean ADCs were not significantly different among the three image types. CONCLUSIONS: dDLR improved the image quality of DWIBS with NEX2. In the context of lymph node and bone metastasis evaluation with DWIBS in patients with prostate cancer, dDLR-NEX2 has potential to be an alternative to NEX8 and reduce the image acquisition time.

Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI.

Objectives: To investigate the application of apparent diffusion coefficient (ADC) histogram analysis in differentiating between benign and malignant breast lesions detected as non-mass enhancement on MRI. Materials and Methods: A retrospective study was conducted for 25 malignant and 26 benign breast lesions showing non-mass enhancement on breast MRI. An experienced radiologist without prior knowledge of the pathological results drew a region of interest (ROI) outlining the periphery of each lesion on the ADC map. A histogram was then made for each lesion. Following a univariate analysis of 18 summary statistics values, we conducted statistical discrimination after hierarchical clustering using Ward's method. A comparison between the malignant and the benign groups was made using multiple logistic regression analysis and the Mann-Whitney U test. A P -value of less than 0.05 was considered statistically significant. Results: Univariate analysis for the 18 summary statistics values showed the malignant group had greater entropy (P < 0.001) and lower uniformity (P < 0.001). While there was no significant difference in mean and skewness values, the malignant group tended to show a lower mean (P = 0.090) and a higher skewness (P = 0.065). Hierarchical clustering of the 18 summary statistics values identified four values (10th percentile, entropy, skewness, and uniformity) of which the 10th percentile values were significantly lower for the malignant group (P = 0.035). Conclusions: Whole-lesion ADC histogram analysis may be useful for differentiating malignant from benign lesions which show non-mass enhancement on breast MRI.

Tumor size in patients with severe pulmonary emphysema might be underestimated on preoperative CT.

OBJECTIVES: To evaluate the effect of emphysema on tumor diameter measured on preoperative computed tomography (CT) images versus pathological specimens. MATERIALS AND METHODS: We investigated patients who underwent primary lung cancer surgery: 55 patients (57 tumors) with severe emphysema and 57 patients (57 tumors) without emphysema. The tumor diameters measured in the postoperative pathological specimens were compared with those measured on the axial CT images and on multiplanar reconstruction (MPR) CT images by two independent radiologists; a subgroup analysis according to tumor size was also performed. A paired or unpaired t test was performed, depending on the tested subjects. RESULTS: In the emphysema group, the mean axial CT diameter was significantly smaller than the mean pathological diameter (p = 0.025/0.001 for reader 1/2), whereas in the non-emphysema group, the mean axial CT diameter was not significantly different from the pathological one for both readers. The difference between CT axial diameter and pathological diameter (= CT diameter - pathological diameter) was significantly smaller (i.e., had a stronger tendency toward underestimation on radiological measurements) in the emphysema group compared with the non-emphysema group (p = 0.014/0.008 for reader 1/2), and the difference was significantly smaller in tumors sized > 30 mm than tumors sized ≤ 20 mm in both groups. CONCLUSIONS: Tumor size is significantly smaller on preoperative CT in patients with severe emphysema compared to patients without emphysema, especially in the case of large tumors. MPR measurement using the widest of three dimensions should be used to select T-stage for patients with severe emphysema. KEY POINTS: • The presence of emphysema affects the accuracy of tumor size measurements on CT. • Compared to patients without emphysema, the tumor size in severe emphysema patients tends to be measured smaller in preoperative CT than the pathological specimen. • This trend is more evident when large tumors are measured on axial CT images alone.

Texture Analysis in Brain Tumor MR Imaging.

Texture analysis, as well as its broader category radiomics, describes a variety of techniques for image analysis that quantify the variation in surface intensity or patterns, including some that are imperceptible to the human visual system. Cerebral gliomas have been most rigorously studied in brain tumors using MR-based texture analysis (MRTA) to determine the correlation of various clinical measures with MRTA features. Promising results in cerebral gliomas have been shown in the previous MRTA studies in terms of the correlation with the World Health Organization grades, risk stratification in gliomas, and the differentiation of gliomas from other brain tumors. Multiple MRTA studies in gliomas have repeatedly shown high performance of entropy, a measure of the randomness in image intensity values, of either histogram- or gray-level co-occurrence matrix parameters. Similarly, researchers have applied MRTA to other brain tumors, including meningiomas and pediatric posterior fossa tumors.However, the value of MRTA in the clinical use remains undetermined, probably because previous studies have shown only limited reproducibility of the result in the real world. The low-to-modest generalizability may be attributed to variations in MRTA methods, sampling bias that originates from single-institution studies, and overfitting problems to a limited number of samples.To enhance the reliability and reproducibility of MRTA studies, researchers have realized the importance of standardizing methods in the field of radiomics. Another advancement is the recent development of a comprehensive assessment system to ensure the quality of a radiomics study. These two-way approaches will secure the validity of upcoming MRTA studies. The clinical use of texture analysis in brain MRI will be accelerated by these continuous efforts.

Adenocarcinoma in situ and minimally invasive adenocarcinoma in lungs of smokers: image feature differences from those in lungs of non-smokers.

PURPOSE: We aimed to examine the characteristics of imaging findings of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) in the lungs of smokers compared with those of non-smokers. MATERIALS AND METHODS: We included seven cases of AIS and 20 cases of MIA in lungs of smokers (pack-years ≥ 20) and the same number of cases of AIS and MIA in lungs of non-smokers (pack-years = 0). We compared the diameter of the entire lesion and solid component measured on computed tomography (CT) images, pathological size and invasive component diameter measured from pathological specimens, and CT values of the entire lesion and ground-glass opacity (GGO) portions between the smoker and non-smoker groups. RESULTS: The diameters of AIS and MIA on CT images and pathological specimens of the smoker group were significantly larger than those of the non-smoker group (p = 0.036 and 0.008, respectively), whereas there was no significant difference in the diameter of the solid component on CT images or invasive component of pathological specimens between the two groups. Additionally, mean CT values of the entire lesion and GGO component of the lesions in the smoker group were significantly lower than those in the non-smoker group (p = 0.036 and 0.040, respectively). CONCLUSION: AIS and MIA in smoker's lung tended to have larger lesion diameter and lower internal CT values compared with lesions in non-smoker's lung. This study calls an attention on smoking status in CT-based diagnosis for early stage adenocarcinoma.

Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.

OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based reconstruction (dDLR) at 1.5 T. METHODS: Forty-two patients underwent MRCP at 1.5 T MRI. The following imaging sequences were performed: Resp-MRCP and BH-MRCP. We applied the dDLR method to the BH-MRCP data (BH-dDLR-MRCP). As a qualitative analysis, two radiologists rated the visibility of the proximal common bile duct (CBD), pancreaticobiliary junction, distal main pancreatic duct, cystic duct, and right and left hepatic ducts. Artifacts and overall image quality were also rated. The signal-to-noise ratios (SNRs), contrast ratios, and contrast-to-noise ratios (CNRs) of the CBD images were calculated for quantitative analysis. RESULTS: BH-MRCP was successfully performed in a single BH. The qualitative and quantitative measurements for BH-dDLR-MRCP were significantly higher than for BH-MRCP (P < 0.02 and P < 0.001, respectively), and the qualitative measurements for BH-dDLR-MRCP were equivalent to or higher than for Resp-MRCP (P = 0.048-1.000). The SNRs and CNRs for BH-dDLR-MRCP were significantly higher than for Resp-MRCP (P < 0.001 and P = 0.001, respectively). CONCLUSION: dDLR is useful and clinically feasible for BH-MRCP at 1.5 T MRI, and enables rapid imaging without loss of image quality compared to conventional Resp-MRCP.

Detectability of pancreatic lesions by low-dose unenhanced computed tomography using iterative reconstruction.

OBJECTIVES: To investigate the detectability of pancreatic cystic lesions and main pancreatic duct dilation by low-dose unenhanced computed tomography (CT). MATERIAL AND METHODS: This study included 2684 patients who underwent low-dose unenhanced CT using iterative reconstruction and magnetic resonance imaging (MRI) as a part of a health-screening program between February 1, 2019 and December 31, 2019. Patients diagnosed with pancreatic cystic lesions and/or dilatations of the main pancreatic duct on MRI were identified. Detection rates by low dose CT in terms of lesion size were tested for significance by Fisher's exact test. RESULTS: Of the 2684 patients, 558 (20.8 %) had pancreatic cystic lesions and 22 (0.8 %) had main pancreatic duct dilatation on MRI. The low-dose CT detection rates among the pancreatic cystic lesions were as follows: 1-9-mm cysts, three (0.65 %) of 461; 10-19-mm cysts, 17 (21.25 %) of 80, and ≥20-mm cysts, eight (47.06 %) of 17. The detection rates were significantly higher in the 10-19-mm and the ≥20-mm cyst group than in the 1-9-mm cyst group (p <  0.001). The detection rates among the main pancreatic duct dilatations were as follows: 3-5-mm dilatations, two (11.76 %) of 17 and ≥6-mm dilatations, four (80 %) of five, which were significantly higher rates than that for the 3-5-mm dilatations (p =  0.009). CONCLUSION: Small pancreatic cysts and slight main pancreatic duct dilatation were practically undetectable by low-dose unenhanced CT. The application of a low-dose CT protocol as a screening tool in the detection of pancreatic abnormalities is not recommended.

Clinical efficacy of haematopoietic stem cell transplantation for adult adrenoleukodystrophy.

Accumulated experience supports the efficacy of allogenic haematopoietic stem cell transplantation in arresting the progression of childhood-onset cerebral form of adrenoleukodystrophy in early stages. For adulthood-onset cerebral form of adrenoleukodystrophy, however, there have been only a few reports on haematopoietic stem cell transplantation and the clinical efficacy and safety of that for adulthood-onset cerebral form of adrenoleukodystrophy remain to be established. To evaluate the clinical efficacy and safety of haematopoietic stem cell transplantation, we conducted haematopoietic stem cell transplantation on 12 patients with adolescent-/adult-onset cerebral form/cerebello-brainstem form of adrenoleukodystrophy in a single-institution-based prospective study. Through careful prospective follow-up of 45 male adrenoleukodystrophy patients, we aimed to enrol patients with adolescent-/adult-onset cerebral form/cerebello-brainstem form of adrenoleukodystrophy at early stages. Indications for haematopoietic stem cell transplantation included cerebral form of adrenoleukodystrophy or cerebello-brainstem form of adrenoleukodystrophy with Loes scores up to 13, the presence of progressively enlarging white matter lesions and/or lesions with gadolinium enhancement on brain MRI. Clinical outcomes of haematopoietic stem cell transplantation were evaluated by the survival rate as well as by serial evaluation of clinical rating scale scores and neurological and MRI findings. Clinical courses of eight patients who did not undergo haematopoietic stem cell transplantation were also evaluated for comparison of the survival rate. All the patients who underwent haematopoietic stem cell transplantation survived to date with a median follow-up period of 28.6 months (4.2-125.3 months) without fatality. Neurological findings attributable to cerebral/cerebellar/brainstem lesions became stable or partially improved in all the patients. Gadolinium-enhanced brain lesions disappeared or became obscure within 3.5 months and the white matter lesions of MRI became stable or small. The median Loes scores before haematopoietic stem cell transplantation and at the last follow-up visit were 6.0 and 5.25, respectively. Of the eight patients who did not undergo haematopoietic stem cell transplantation, six patients died 69.1 months (median period; range 16.0-104.1 months) after the onset of the cerebral/cerebellar/brainstem lesions, confirming that the survival probability was significantly higher in patients with haematopoietic stem cell transplantation compared with that in patients without haematopoietic stem cell transplantation (P = 0.0089). The present study showed that haematopoietic stem cell transplantation was conducted safely and arrested the inflammatory demyelination in all the patients with adolescent-/adult-onset cerebral form/cerebello-brainstem form of adrenoleukodystrophy when haematopoietic stem cell transplantation was conducted in the early stages. Further studies are warranted to optimize the procedures of haematopoietic stem cell transplantation for adolescent-/adult-onset cerebral form/cerebello-brainstem form of adrenoleukodystrophy.

Differentiation between solitary fibrous tumors and schwannomas of the head and neck: an apparent diffusion coefficient histogram analysis.

METHODS:: Our study included 5 patients with SFT and 18 patients with schwannoma in the head and neck region for whom pre-operative ADC images were obtained using either 1.5 or 3.0 T MRI system with two b-values. An ADC image that showed the tumor at the largest major diameter was selected for each patient, and a region of interest was set circumscribing the tumor. The histogram distributions of ADC values within the region of interest were compared between SFTs and schwannomas with respect to the mean, standard deviation, median, skewness, kurtosis, and percentile. RESULTS:: The mean and the median ADC values were significantly higher for schwannomas than in SFTs (p = 0.007 in both). Skewness and kurtosis of ADC histograms were significantly lower for schwannomas than for SFTs (p = 0.002 and 0.005, respectively). ADC values differed greatest between the two tumor groups at the 90th percentile, and were significantly higher for schwannomas than for SFTs (p = 0.005). On receiver operating characteristic curve analysis, the area under the curve for kurtosis, skewness, and the 90th percentile ADC values was 0.92, 0.90, and 0.90, respectively. CONCLUSIONS:: Our study suggests that skewness on ADC histograms may be the most useful diagnostic factor, followed by kurtosis and the 90th percentile ADC values, for differentiation between SFTs and schwannomas.

Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.

PURPOSE: Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classification by support vector machine, a method of traditional machine learning, using texture features computed from contrast-enhanced T1-weighted images. METHODS: This retrospective study on preoperative brain tumor MRI included 76 consecutives, initially treated patients with glioblastoma (n = 55) or PCNSL (n = 21) from one institution, consisting of independent training group (n = 60: 44 glioblastomas and 16 PCNSLs) and test group (n = 16: 11 glioblastomas and 5 PCNSLs) sequentially separated by time periods. A total set of 67 texture features was computed on routine contrast-enhanced T1-weighted images of the training group, and the top four most discriminating features were selected as input variables to train support vector machine classifiers. These features were then evaluated on the test group with subsequent image classification. RESULTS: The area under the receiver operating characteristic curves on the training data was calculated at 0.99 (95% confidence interval [CI]: 0.96-1.00) for the classifier with a Gaussian kernel and 0.87 (95% CI: 0.77-0.95) for the classifier with a linear kernel. On the test data, both of the classifiers showed prediction accuracy of 75% (12/16) of the test images. CONCLUSIONS: Although further improvement is needed, our preliminary results suggest that machine learning-based image classification may provide complementary diagnostic information on routine brain MRI.

Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid-enhanced Hepatobiliary Phase MR Images.

Purpose To investigate the performance of a deep convolutional neural network (DCNN) model in the staging of liver fibrosis using gadoxetic acid-enhanced hepatobiliary phase magnetic resonance (MR) imaging. Materials and Methods This retrospective study included patients for whom input data (hepatobiliary phase MR images, static magnetic field of the imaging unit, and hepatitis B and C virus testing results available, either positive or negative) and reference standard data (liver fibrosis stage evaluated from biopsy or surgical specimens obtained within 6 months of the MR examinations) were available were assigned to the training (534 patients) or the test (100 patients) group. For the training group (54, 53, 81, 113, and 233 patients with fibrosis stages F0, F1, F2, F3, and F4, respectively; mean patient age, 67.4 ± 9.7 years; 388 men and 146 women), MR images with three different section levels were augmented 90-fold (rotated, parallel-shifted, brightness-changed and contrast-changed images were generated; a total of 144 180 images). Supervised training was performed by using the DCNN model to minimize the difference between the output data (fibrosis score obtained through deep learning [FDL score]) and liver fibrosis stage. The performance of the DCNN model was evaluated in the test group (10, 10, 15, 20, and 45 patients with fibrosis stages F0, F1, F2, F3, and F4, respectively; mean patient age, 66.8 years ± 10.7; 71 male patients and 29 female patients) with receiver operating characteristic (ROC) analyses. Results The FDL score was correlated significantly with fibrosis stage (Spearman rank correlation coefficient: 0.63; P < .001). Fibrosis stages F4, F3, and F2 were diagnosed with areas under the ROC curve of 0.84, 0.84, and 0.85, respectively. Conclusion The DCNN model exhibited a high diagnostic performance in the staging of liver fibrosis. © RSNA, 2017 Online supplemental material is available for this article.

Comparison between Glioblastoma and Primary Central Nervous System Lymphoma Using MR Image-based Texture Analysis.

PURPOSE: To elucidate differences between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) with MR image-based texture features. METHODS: This was an Institutional Review Board (IRB)-approved retrospective study. Consecutive, pathologically proven, initially treated 44 patients with GBM and 16 patients with PCNSL were enrolled. We calculated a total of 67 image texture features on the largest contrast-enhancing lesion in each patient on post-contrast T1-weighted images. Texture analyses included first-order features (histogram) and second-order features calculated with gray level co-occurrence matrix, gray level run length matrix (GLRLM), gray level size zone matrix, and multiple gray level size zone matrix. All texture features were measured by two neuroradiologists independently and the intraclass correlation coefficients were calculated. Reproducible features with the intraclass correlation coefficients of greater than 0.7 were used for hierarchical clustering between the cases and the features along with unpaired t statistics-based comparisons under the control of false discovery rate (FDR) < 0.05. Principal component analysis (PCA) was performed to find the predominant features in evaluating the differences between GBM and PCNSL. RESULTS: Twenty-one out of the 67 features satisfied the acceptable intraclass correlation coefficient and the FDR constraints. PCA suggested first-order entropy, median, GLRLM-based run length non-uniformity, and run percentage as the distinguished features. Compared with PCNSL, run percentage and median were significantly lower, and entropy and run length non-uniformity were significantly higher in GBM. CONCLUSIONS: Among MR image-based textures, first-order entropy, median, GLRLM-based run length non-uniformity, and run percentage are considered to enhance differences between GBM and PCNSL.

Skull Base Tumors and Tumor-Like Lesions: A Pictorial Review.

A number of tumors and tumor-like non-neoplastic lesions with different cell types on histology occur in the skull base. A wide variety in disease and lesion appearance often complicates the process of radiological diagnosis. The main role of radiographic imaging is the detection and characterization of skull base lesions, with evaluation of the extent of invasion or preservation of adjacent critical organs. Evaluation of the skull base anatomy and surgical planning by using image guidance are also important for surgeons. Computed tomography (CT) and magnetic resonance (MR) imaging are the preferred modalities for the evaluation of skull base lesions. CT and MR are used for lesion detection, tissue characterization and assessment of neurovascular and bone involvement by the lesions. Both modalities provide useful information, one sometimes of greater value than the other. T1-weighted MR imaging is useful in detecting skull base lesions, typically surrounded by abundant fatty bone marrow. T2-weighted MR imaging is generally useful for tumor tissue characterization. CT surpasses MR imaging in evaluating intratumoral calcification and bone destruction or hyperostosis. To date, imaging features have been well-reported in individual skull base tumors; however, correct diagnosis by imaging alone still presents a challenge. Knowledge of clinical issues and awareness of variants of skull base tumors are of help in making a diagnosis. The purpose of this article is to review pertinent clinical issues, typical imaging appearances and certain imaging variations of common skull base lesions.

Diffusion imaging of reversible and irreversible microstructural changes within the corticospinal tract in idiopathic normal pressure hydrocephalus.

The symptoms of idiopathic normal pressure hydrocephalus (iNPH) can be improved by shunt surgery, but prediction of treatment outcome is not established. We investigated changes of the corticospinal tract (CST) in iNPH before and after shunt surgery by using diffusion microstructural imaging, which infers more specific tissue properties than conventional diffusion tensor imaging. Two biophysical models were used: neurite orientation dispersion and density imaging (NODDI) and white matter tract integrity (WMTI). In both methods, the orientational coherence within the CSTs was higher in patients than in controls, and some normalization occurred after the surgery in patients, indicating axon stretching and recovery. The estimated axon density was lower in patients than in controls but remained unchanged after the surgery, suggesting its potential as a marker for irreversible neuronal damage. In a Monte-Carlo simulation that represented model axons as undulating cylinders, both NODDI and WMTI separated the effects of axon density and undulation. Thus, diffusion MRI may distinguish between reversible and irreversible microstructural changes in iNPH. Our findings constitute a step towards a quantitative image biomarker that reflects pathological process and treatment outcomes of iNPH.

Variants of meningiomas: a review of imaging findings and clinical features.

Meningiomas are common neoplasms that frequently occur in the brain and spine. Among the 15 histological subtypes of meningiomas in the WHO classification, the incidence of meningothelial meningiomas is the highest, followed by fibrous and transitional meningiomas. These three subtypes account for approximately 80 % of all meningiomas, and thus could be regarded as typical meningiomas. For this reason, other uncommon histological subtypes may be considered as imaging variants, and diagnosis is often challenging for radiologists solely based on imaging features of typical meningiomas. In addition to the histological subtypes, meningiomas arising in atypical locations could be easily mistaken for other lesions more commonly observed in those locations. The purpose of this article is to review characteristic clinical and imaging findings of uncommon meningiomas, including histological variants and meningiomas occurring in relatively rare locations.

Combined use of diffusion tensor tractography and multifused contrast-enhanced FIESTA for predicting facial and cochlear nerve positions in relation to vestibular schwannoma.

OBJECT: The authors assessed whether the combined use of diffusion tensor tractography (DTT) and contrast-enhanced (CE) fast imaging employing steady-state acquisition (FIESTA) could improve the accuracy of predicting the courses of the facial and cochlear nerves before surgery. METHODS: The population was composed of 22 patients with vestibular schwannoma in whom both the facial and cochlear nerves could be identified during surgery. According to DTT, depicted fibers running from the internal auditory canal to the brainstem were judged to represent the facial or vestibulocochlear nerve. With regard to imaging, the authors investigated multifused CE-FIESTA scans, in which all 3D vessel models were shown simultaneously, from various angles. The low-intensity areas running along the tumor from brainstem to the internal auditory canal were judged to represent the facial or vestibulocochlear nerve. RESULTS: For all 22 patients, the rate of fibers depicted by DTT coinciding with the facial nerve was 13.6% (3/22), and that of fibers depicted by DTT coinciding with the cochlear nerve was 63.6% (14/22). The rate of candidates for nerves predicted by multifused CE-FIESTA coinciding with the facial nerve was 59.1% (13/22), and that of candidates for nerves predicted by multifused CE-FIESTA coinciding with the cochlear nerve was 4.5% (1/22). The rate of candidates for nerves predicted by combined DTT and multifused CE-FIESTA coinciding with the facial nerve was 63.6% (14/22), and that of candidates for nerves predicted by combined DTT and multifused CE-FIESTA coinciding with the cochlear nerve was 63.6% (14/22). The rate of candidates predicted by DTT coinciding with both facial and cochlear nerves was 0.0% (0/22), that of candidates predicted by multifused CE-FIESTA coinciding with both facial and cochlear nerves was 4.5% (1/22), and that of candidates predicted by combined DTT and multifused CE-FIESTA coinciding with both the facial and cochlear nerves was 45.5% (10/22). CONCLUSIONS: By using a combination of DTT and multifused CE-FIESTA, the authors were able to increase the number of vestibular schwannoma patients for whom predicted results corresponded with the courses of both the facial and cochlear nerves, a result that has been considered difficult to achieve by use of a single modality only. Although the 3D image including these prediction results helped with comprehension of the 3D operative anatomy, the reliability of prediction remains to be established.

Feasibility of diffusion tensor tractography for preoperative prediction of the location of the facial and vestibulocochlear nerves in relation to vestibular schwannoma.

BACKGROUND: According to recent findings, diffusion tensor tractography (DTT) only allows prediction of facial nerve location in relation to vestibular schwannoma (VS) with high probability. However, previous studies have not mentioned why only the facial nerve was selectively visualized. Our previous report investigated the optimal conditions of DTT for normal facial and vestibulocochlear nerves. In the present study, we applied the optimal conditions of DTT to VS patients to assess the feasibility of DTT for the facial and vestibulocochlear nerves. METHODS: We investigated 11 patients with VS who underwent tumor resection. Visualized tracts were compared with locations of the facial and cochlear nerves as identified by intraoperative electrophysiological monitoring. RESULTS: With the proposed method, visualized tracts corresponded to pathway area of the facial or cochlear nerves in nine of 11 patients (81.8%); specifically, to the pathway area of the facial nerve in three of 11 patients (27.3%), and to the pathway area of the cochlear nerve in six of 11 patients (54.5%). CONCLUSIONS: We visualized facial or vestibulocochlear nerves in nine of 11 patients (81.8%). For the first time, DTT proved able to visualize not only the facial nerve but also the vestibulocochlear nerve in VS patients. Despite our findings, good methods for distinguishing whether a visualized nerve tract represents facial nerve, vestibulocochlear nerve, or only noise remain unavailable. Close attention should therefore be paid to the interpretation of visualized fibers.

Diffusion tensor tractography of normal facial and vestibulocochlear nerves.

PURPOSE: Diffusion tensor tractography (DTT) is not adequately reliable for prediction of facial and vestibulocochlear (VII-VIII) nerve locations, especially relative to a vestibular schwannoma (VS). Furthermore, it is often not possible to visualize normal VII-VIII nerves by DTT (visualization rates were 12.5-63.6%). Therefore, DTT post-processing was optimized for normal VII-VIII nerve visualization with and without manual noise elimination. METHODS: DTT examinations of ten patients were evaluated to assess the improvement in performance by modifying seed region of interest (ROI) and fractional anisotropy (FA) threshold. Seed ROI was placed at the porus of the internal auditory meatus, and FA threshold values were either fixed or variable for each patient. DTT visualization of cranial nerves VII-VIII was evaluated and the noise effect was measured. RESULTS: Cranial nerves VII-VIII were visualized in 90% of patients without using manual noise elimination by modifying the seed ROI and FA threshold. The visualization rate with FA threshold of the upper limit in each patient (100%) was significantly higher than that with FA threshold of 0.1 (75%) (p = 0.02). The incidence rate of noise with FA threshold of the upper limit (10%) was not significantly different than the FA threshold of 0.1 (20%) (p = 0.66). CONCLUSION: Seed ROI modification and FA thresholding can improve the visualization of cranial nerve VII-VIII locations in DTT. This technique is promising for its potential to determine the relationship of cranial nerves VII-VIII to VS.