Postcontrast Magnetic Resonance Imaging Research Articles

P.438 The capacity of schizophrenia and bipolar disorder individuals for autonomous treatment decision making

To compare the diagnostic efficacy of Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) vs. multidetector computed tomography (MDCT) for the detection and classification of focal liver lesions, differentiated also for lesion entity and size; a separate analysis of pre- and postcontrast images as well as T2-weighted MRI sequences of focal and exclusively solid lesions was integrated.Twenty-nine patients with 130 focal liver lesions underwent MDCT (64-detector-row; contrast medium iopromide; native, arterial, portalvenous, venous phase) and MRI (1.5-T; dynamic and tissue-specific phase 20 min after application of Gd-EOB-DTPA). Hepatic lesions were verified against a standard of reference (SOR). CT and MR images were independently analysed by four blinded radiologists on an ordinal 6-point-scale, determining lesion classification and diagnostic confidence.Among 130 lesions, 68 were classified as malignant and 62 as benign by SOR. The detection of malignant and benign lesions differed significantly between combined and postcontrast MRI vs. MDCT; overall detection rate was 91.5% for combined MRI and 80.4% for combined MDCT (p < 0.05). Considering all four readers together, combined MDCT achieved sensitivity of 66.2%, specificity of 79.0%, and diagnostic accuracy of 72.3%; combined MRI reached superior diagnostic efficacy: sensitivity 86.8%, specificity 94.4%, accuracy 90.4% (p < 0.05). Differentiated for lesion size, in particular lesions <20 mm revealed diagnostic benefit by MRI. Postcontrast MRI also achieved higher overall sensitivity, specificity, and accuracy compared to postcontrast MDCT for focal and exclusively solid liver lesions (p < 0.05).Combined and postcontrast Gd-EOB-DTPA-enhanced MRI provided significantly higher overall detection rate and diagnostic accuracy, including low inter-observer variability, compared to MDCT in a single centre study.

MetNet: Computer-aided segmentation of brain metastases in post-contrast T1-weighted magnetic resonance imaging

PurposeBrain metastases are manually contoured during stereotactic radiosurgery (SRS) treatment planning, which is time-consuming, potentially challenging, and laborious. The purpose of this study was to develop and investigate a 2-stage deep learning (DL) approach (MetNet) for brain metastasis segmentation in pre-treatment magnetic resonance imaging (MRI). Materials and methodsWe retrospectively analyzed postcontrast 3D T1-weighted spoiled gradient echo MRIs from 934 patients who underwent SRS between August 2009 and August 2018. Neuroradiologists manually identified brain metastases in the MRIs. The treating radiation oncologist or physicist contoured the brain metastases. We constructed a 2-stage DL ensemble consisting of detection and segmentation models to segment the brain metastases on the MRIs. We evaluated the performance of MetNet by computing sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC) with respect to metastasis size, as well as free-response receiver operating characteristics. ResultsThe 934 patients (mean [±standard deviation] age 59 ± 13 years, 474 women) were randomly split into 80% training and 20% testing groups (748:186). For patients with metastases 1–52 mm (n = 766), 648 (85%) were detected and segmented with a mean segmentation DSC of 81% ± 15%. Patient-averaged sensitivity was 88% ± 19%, PPV was 58% ± 25%, and DSC was 85% ± 13% with 3 ± 3 false positives (FPs) per patient. When considering only metastases ≥6 mm, patient-averaged sensitivity was 99% ± 5%, PPV was 67% ± 28%, and DSC was 87% ± 13% with 1 ± 2 FPs per patient. ConclusionMetNet can segment brain metastases across a broad range of metastasis sizes with high sensitivity, low FPs, and high segmentation accuracy in postcontrast T1-weighted MRI, potentially aiding treatment planning for SRS.

Traditional and Advanced Neuroimaging Contributions to the Diagnosis and Differential Diagnosis of Central Nervous System Lymphoma Patients Visiting a Comprehensive Medical Center

Introduction: The diagnosis of Central Nervous System Lymphoma, especially the Primary Central Nervous System Lymphoma is carried out based on brain imaging, thus avoiding an unnecessary extend of surgery. But the traditional imaging techniques, such as Computed Tomography and Magnetic Resonance Imaging, were not satisfactory. Aims: This study was conducted to characterize the spectrum of advanced Neuroimaging, such as the advanced Magnetic Resonance Imaging features in the Central Nervous System Lymphoma patients in a comprehensive medical center in Lebanon, and compare them to what has been described in the literature review. Methods: It is a retrospective exploratory study of the clinical data and imaging features for patients admitted to the emergency and radiology departments with ages above 10 years, and who were diagnosed histopathologically with intracranial lymphoma. This study may be the first to make a Radiological evaluation of Central Nervous System Lymphoma on the local population of patients over 9 years . Results: Results showed that the study of the Computed Tomography and Magnetic Resonance Imaging data of 10 immunocompetent patients with Central Nervous System Lymphoma concurs with the previously described patient populations, except for the gender parameter. Tumors were mostly presented in the fifth or Sixth decade and they could be solitary or multi-focal. Lesions were typically located Preprint submitted to The Open Neuroimaging Journal May 14, 2020 in the supratentorial compartment. On the brain Computed Tomography, the lesions were hyperdense, and in pre-contrast Magnetic Resonance images, the lesions appeared hypointense on T1 and hyperintense on T2-Weighted images, but hypointense with respect to the grey matter. The lesions were also surrounded with a mild to moderate edema as compared to other intracranial neoplasms, such as glioblastomas. Evaluation results showed that on post-contrast Magnetic Resonance images, the majority of lesions exhibited a homogeneous enhancement of 50%. Majority of the lesions also showed a less common heterogeneous ring-like enhancement of 40%, and revealed the uncommon absence of enhancement of 10%. Calcifications, hemorrhage, and necrosis were rare findings and were present in only one patient. Conclusion: As a future prospect, studying whether the advanced imaging techniques may provide not only non-invasive and morphological characteristics but also non-invasive biological characteristics and thus accurate diagnosis could be considered.

A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study

BackgroundPrediction of brain invasion pre-operatively rather than postoperatively would contribute to the selection of surgical techniques, predicting meningioma grading and prognosis. Here, we aimed to predict the risk of brain invasion in meningioma pre-operatively using a nomogram by incorporating radiomic and clinical features.MethodsIn this case-control study, 1728 patients from Beijing Tiantan Hospital (training cohort: n = 1070) and Lanzhou University Second Hospital (external validation cohort: n = 658) were diagnosed with meningiomas by histopathology. Radiomic features were extracted from the T1-weighted post-contrast and T2-weighted magnetic resonance imaging. The least absolute shrinkage and selection operator was used to select the most informative features of different modalities. The support vector machine algorithm was used to predict the risk of brain invasion. Furthermore, a nomogram was constructed by incorporating radiomics signature and clinical risk factors, and decision curve analysis was used to validate the clinical usefulness of the nomogram.FindingsSixteen features were significantly correlated with brain invasion. The clinicoradiomic model derived from the fusing MRI sequences and sex resulted in the best discrimination ability for risk prediction of brain invasion, with areas under the curves (AUCs) of 0•857 (95% CI, 0•831–0•887) and 0•819 (95% CI, 0•775–0•863) and sensitivities of 72•8% and 90•1% in the training and validation cohorts, respectively.InterpretationOur clinicoradiomic model showed good performance and high sensitivity for risk prediction of brain invasion in meningioma, and can be applied in patients with meningiomas.FundingThis work was supported by the 10.13039/501100001809National Natural Science Foundation of China (81772006, 81922040); the 10.13039/501100004739Youth Innovation Promotion Association CAS (grant numbers 2019136); special fund project for doctoral training program of 10.13039/100012899Lanzhou University Second Hospital (grant numbers YJS-BD-33).

Treatment outcomes and target delineation utilizing CT and MRI in 13 dogs treated with a uniform stereotactic radiation therapy protocol (16 Gy single fraction) for pituitary masses: (2014-2017).

Canine pituitary tumours are increasingly treated with stereotactic radiotherapy (SRT). Here, we report clinical outcomes in dogs treated with single-fraction SRT; we also explore technical aspects of SRT treatment planning. A single-institution retrospective study was performed, including any dog with a pituitary mass (PM) that was treated using a standardized single-fraction (16 Gy) SRT protocol between 2014 and 2017. Via medical records review, 13 cases were identified. Nine dogs neurologically improved after SRT. Four dogs experienced MRI-documented tumour volume reduction. Nine dogs experienced neurologic decline in 1.5 to 18 months after SRT and were euthanized. The median overall survival time was 357 days, with 15% alive 18 months after SRT. To better understand whether SRT target delineation is predictably altered by use of magnetic resonance imaging (MRI) in addition to computed tomography (CT), two radiation oncologists (RO) retrospectively re-evaluated all imaging studies used for SRT planning in these 13 cases. Gross tumour volume (GTV) was contoured on co-registered CT and MRIs for each case. In seven cases, CT alone was deemed inadequate for GTV contouring by at least one RO. T1 post-contrast MRI was considered the ideal image for GTV contouring in 11 cases. Contouring on MRI yielded larger GTV than CT for 11 cases. Inter-observer variability existed in each case and was greater for MRI. In summary, use of co-registered CT and MRI images is generally considered advantageous for PM delineation when using SRT. Notably, survival times reported herein are shorter than what has previously been reported for PM treated with finely fractionated full-course RT protocols.

Significance of high signal intensity in the endolymphatic duct on magnetic resonance imaging in ears with otological disorders

BackgroundHigh signal intensity in the endolymphatic duct (ED) is occasionally observed on magnetic resonance imaging (MRI) in ears that have otological disorders.ObjectiveThe signal intensity (SI) in the ED on post-contrast MRI was investigated in subjects with various otological disorders, and the meaning of high SI in the ED was evaluated.Material and methods392 patients with otological disorders and 21 controls without otological symptoms underwent 3 T MRI. The SIs of the ED and the cerebellum were measured, the SI ratio (SIR) was calculated, and ears with SIR ≥4 were identified.ResultsA high SIR was identified in the ED of 3.7% of ears affected by definite Meniere’s disease (dMD), 100% of ears affected by large vestibular aqueduct syndrome (LVAS), and 7.1% of ears with no otological symptoms. On the whole, a significant relationship was found between the existence of vestibular or cochlear EH and the SIR in the ED.ConclusionThe MRI finding of high SI in the ED may indicate the mechanism of inner ear disturbances in ears with otological disorders, especially in those with LVAS, and it may suggest an underlying disorder in some ears in which otological symptoms are not apparent.

Differentiating glioblastoma multiforme from cerebral lymphoma: application of advanced texture analysis of quantitative apparent diffusion coefficients.

The purpose of this study was to differentiate glioblastoma multiforme from primary central nervous system lymphoma using the customised first and second-order histogram features derived from apparent diffusion coefficients.Methods and materials: A total of 82 patients (57 with glioblastoma multiforme and 25 with primary central nervous system lymphoma) were included in this study. The axial T1 post-contrast and fluid-attenuated inversion recovery magnetic resonance images were used to delineate regions of interest for the tumour and peritumoral oedema. The regions of interest were then co-registered with the apparent diffusion coefficient maps, and the first and second-order histogram features were extracted and compared between glioblastoma multiforme and primary central nervous system lymphoma groups. Receiver operating characteristic curve analysis was performed to calculate a cut-off value and its sensitivity and specificity to differentiate glioblastoma multiforme from primary central nervous system lymphoma. Based on the tumour regions of interest, apparent diffusion coefficient mean, maximum, median, uniformity and entropy were higher in the glioblastoma multiforme group than the primary central nervous system lymphoma group (P ≤ 0.001). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the maximum of 2.026 or less (95% confidence interval (CI) 75.1-99.9%), and the most specific first and second-order histogram feature was smoothness of 1.28 or greater (84.0% CI 70.9-92.8%). Based on the oedema regions of interest, most of the first and second-order histogram features were higher in the glioblastoma multiforme group compared to the primary central nervous system lymphoma group (P ≤ 0.015). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the 25th percentile of 0.675 or less (100% CI 83.2-100%) and the most specific first and second-order histogram feature was the median of 1.28 or less (85.9% CI 66.3-95.8%). Texture analysis using first and second-order histogram features derived from apparent diffusion coefficient maps may be helpful in differentiating glioblastoma multiforme from primary central nervous system lymphoma.

Computed tomography and magnetic resonance imaging of adenoid cystic carcinoma in the maxillary sinus: a retrospective study with radiologic-histopathologic correlations

The aim of this study was to investigate computed tomography (CT) and magnetic resonance imaging (MRI) findings in adenoid cystic carcinoma (ACC) in the maxillary sinus and their correlations with the tubular, cribriform, and solid histopathologic types of ACC. Twenty cases of histopathologically proven ACC in the maxillary sinus were retrospectively reviewed. CT and MRI findings were correlated with histopathologic results. On CT, significant differences were discovered among the 3 histopathologic ACC types in range, size, shape, margins, type of bone destruction, and time intensity curve (TIC) (P ≤ .018). Tubular lesions were limited in range, were smaller than the other types, produced small cystic patterns with well-defined margins, and caused a cribriform pattern of bone destruction. All tumors demonstrated heterogeneous intensity signal on T1- and T2-weighted images (T1WI and T2WI) and appeared as hypo- or isointense small cystic lesions on T1WI and hyperintense on T2WI (n=6). Postcontrast MRI revealed marked heterogeneous enhancement for all lesions. The TIC showed a rapidly enhancing and slow washout pattern in all tubular lesions and a rapidly enhancing and rapid washout pattern in solid tumors. Different histologic patterns of ACCs have distinctive radiologic features, which can facilitate accurate preoperative diagnosis.

SAT-LB19 Is There a Need to Use Gadolinium Contrast for Pituitary MRI in the Evaluation of Pediatric Short Stature and Growth Hormone Deficiency?

SAT-LB19 Is There a Need to Use Gadolinium Contrast for Pituitary MRI in the Evaluation of Pediatric Short Stature and Growth Hormone Deficiency?

The diagnostic value of MR spectroscopy versus DWI-MRI in therapeutic planning of suspicious multi-centric cerebral lesions

BackgroundA broad spectrum of non-neoplastic lesions can radiologically mimic cerebral neoplasms. Magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and diffusion-weighted imaging (DWI) are the most extensively used for enabling lesional characterization of different brain disorders. We aimed to assess the diagnostic value of MRS versus DWI in the diagnosis and therapeutic planning of multicentric cerebral focal lesions and in our retrospective study, we enrolled 64 patients with 100 brain lesions who underwent pre- and post-contrast MRI, MRS, and DWI. Diagnoses supplied by the histopathology and follow up clinical results as a gold standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were calculated.ResultsConventional MRI poorly differentiates multiple cerebral lesions with 89.33% sensitivity, 44.4% specificity, and 78% accuracy. MRS results revealed statistical significance for differentiating neoplastic from non-neoplastic lesions as regards Cho/Cr, Cho/NAA, and NAA/Cr ratios (M ± SD) with P < 0.001 (significant), and there is statistical significance for neoplastic lesion differentiation when Cho/NAA and Ch/Cr ratios measured in the pre-lesional areas outside the tumor margin. DWI showed mixed diffusion changes in most of the studied lesions and the measured ADC values ranges showed overlap in neoplastic and non-neoplastic lesions, P value = 0.236* (insignificant).ConclusionMRS was found to be a more accurate diagnostic tool than DWI with ADC measurements in the differentiation and therapeutic planning of multicentric cerebral focal lesions.

Three-dimensional intra- and extracranial arterial vessel wall joint imaging in patients with cerebrovascular disease

PurposeTo evaluate the clinical performance of a newly developed three-dimensional (3D) intra- and extracranial arterial vessel wall joint imaging technique at 3T using T1-weighted 3D variable-flip-angle turbo spin-echo sequence with improved cerebrospinal fluid suppression in patients with cerebrovascular disease. Materials and methods122 consecutive patients (mean age 45.96 ± 12.16 years) with clinically confirmed cerebrovascular symptoms were imaged using a 3D intra- and extracranial arterial vessel wall joint imaging sequence with and without contrast enhancement on a 3 T MR system. The number of plaques and culprit plaques were evaluated. The image quality score, percent stenosis, remodeling ratio, and plaque burden were measured and compared between intracranial and carotid arterial plaques, and between non-culprit and culprit plaques. ResultsExcept for 23 patients, there were 322 plaques (111 culprit plaques) detected in 96 patients with large artery atherosclerosis. Of the plaques, 278 (96 culprit plaques) and 44 (15 culprit plaques) plaques were identified in intracranial and extracranial arteries, respectively. Image quality did not differ significantly between pre- and post-contrast vessel wall magnetic resonance images. There were also no significant differences in the percent stenosis, remodeling ratio, and plaque burden between intracranial and carotid arteries, and between non-culprit and culprit plaques. The enhancement rate of culprit plaques was significantly higher than that of non-culprit plaques. ConclusionsThe described joint imaging is a promising vessel wall magnetic resonance imaging method for comprehensive diagnosis of cerebrovascular symptoms and investigation of etiology. The imaging technique is a potentially valuable means to optimize treatment.

Additional Diagnostic Value of Unenhanced Computed Tomography plus Diffusion-Weighted Imaging Combined with Routine Magnetic Resonance Imaging Findings of Early-Stage Gliblastoma.

Purpose This study was performed to determine whether diffusion-weighted imaging (DWI) plus unenhanced computed tomography (CT) of the brain increases the diagnostic value of routine magnetic resonance (MR) imaging findings of early-stage glioblastoma. Methods Postcontrast MR images of eight unenhanced lesions that had been pathologically diagnosed as glioblastoma were retrospectively examined. The location, margin, signal intensity, and attenuation on MR imaging and CT were assessed. Results On MR imaging, all lesions were ill-defined, small, and isointense to hypointense on T1-weighted images and hyperintense on T2-weighted images. Four patients had perilesional edema. In seven patients, DWI showed an inhomogeneous hyperintense lesion (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (n = 1) or isointense lesion with a hyperintense region (Conclusions MR imaging was the most sensitive imaging method for depicting early-stage glioblastoma. The CT finding of a hyperattenuated or isoattenuated region combined with the DWI finding of the same region containing an inhomogeneous hyperintense lesion or isointense lesion with a hyperintense region may be a specific diagnostic sign for early-stage glioblastoma. DWI plus unenhanced CT added diagnostic value to the routine MR imaging findings of early-stage glioblastoma.

High Resolution MR Imaging guidelines in retinoblastoma: prospective study correlated with histopathological results

BackgroundRetinoblastoma is the commonest intraocular pediatric neoplasm. With the recent scope of shifting to eye preserving therapies, preoperative MRI is becoming the primary noninvasive diagnostic method to confirm the diagnosis, assess the ocular coats and optic nerve, and detect extraocular tumor extension and intracranial primitive neuroectodermal tumor associated with retinoblastoma as funduscopy and ultrasound have limitations. Diffusion-weighted images (DWIs) detect abnormalities based on differences in tissue cellularity. Echoplanar-based (EP) DWI results in susceptibility artifacts and geometric distortions, which make DWI of the orbit a challenging technique. The purpose of our study is to evaluate preoperative magnetic resonance (MR) imaging diagnostic merits and indices in patients with retinoblastoma.ResultsFifty-eight eyes were prospectively reviewed in 30 girls and 27 boys (mean age at diagnosis was 23 months ± 18.9) with retinoblastoma by two radiologists on T1-weighted images, fat saturated T2-weighted images, DWIs, ADC, and postcontrast T1-weighted MR images with and without fat suppression. All patients included were primarily treated by surgical enucleation; one girl had bilateral enucleation. MRI shows accuracy, sensitivity, specificity, NPV, and PPV; 86.2%, 95.3%, 60%, 81.8%, and 87.2% respectively for choroidal invasion; 75.8%, 58.8%, 82.9%, 83%, and 58.8% in prelaminar optic nerve invasion; and 86.2%, 85.2%, 87%, 87%, and 85% in postlaminar optic nerve invasion (PLONI) respectively. For sclera and extrascleral tumor invasion, MRI show accuracy, sensitivity, specificity, NPV, and PPV of 93%, 55.6%, 100%, 92.5%, 100%, and 98.3%, 100%, 98%,100%, 80% respectively. On DWIs, the vital solid tumor shows hyperintense signal compared to the vitreous. The difference between the mean ADC value of the solid enhancing tumor (0.3[0.12–0.8] × 10−3 s/mm2) and nonenhancing necrotic parts (1.4[1.0–1.8] × 10−3 s/mm2) was statistically significant (p < 0.001). No correlation was found between the ADC values and high risk features for metastasis. Abnormal anterior chamber enhancement shows no statistically significant correlation with main MRI and histopathology findings. Maximum tumor diameter in mm show statistically significant correlation with postlaminar optic nerve invasion (ρ = .002) and choroidal invasion (ρ = .007). Sensitivity and specificity of different tumor size cutoff values are calculated using the ROC analysis.ConclusionHigh-resolution ocular MR imaging can reliably detect postlaminar optic nerve invasion, choroid, and extrascleral invasion; meanwhile, it shows low sensitivity in prelaminar optic nerve, ciliary body, and sclera invasion. Significantly lower ADC values in viable tumor than necrotic parts are recorded.

Regional differences in temporomandibular joint inflammation in patients with juvenile idiopathic arthritis: a dynamic post-contrast magnetic resonance imaging study

The purpose was to determine whether there are regional differences in temporomandibular joint (TMJ) inflammation in patients with juvenile idiopathic arthritis (JIA). This was a retrospective study of all patients with dynamic, contrast-enhanced magnetic resonance imaging through the TMJs at Massachusetts General Hospital between January 2015 and July 2016. The patient cohort included those with a history of JIA and control patients who underwent MRI for other routine clinical purposes. TMJ inflammation was quantified as the difference between post-gadolinium and pre-gadolinium articular T1 signal intensity normalized to post-gadolinium signal intensity of the longus capitis muscle. TMJ enhancement profiles were generated for the lateral, central, and medial portions of the TMJ. Regional differences in TMJ enhancement were investigated using basic descriptive statistics. Medial edge enhancement of the TMJs was highest in symptomatic JIA joints, followed by asymptomatic JIA, then control joints. Medial edge enhancement was a significant discriminator between symptomatic JIA TMJs and control joints (P = 0.0001), between symptomatic and asymptomatic JIA TMJs (P = 0.0003), and between asymptomatic JIA TMJs and controls (P = 0.0019). A shift in distribution of TMJ enhancement towards the medial edge that was seen uniquely in both asymptomatic and symptomatic JIA TMJs compared to control joints was found. This suggests a pattern of worsening medial edge inflammation with disease.

Propionibacterium acnes-associated chronic hypertrophic pachymeningitis followed by refractory otitis media: a case report

BackgroundHypertrophic pachymeningitis (HP) is a rare disorder that involves localized or diffuse thickening of the dura mater. HP is associated with various inflammatory, infectious, and malignant diseases, such as rheumatic arthritis, sarcoidosis, anti-neutrophil cytoplasmic antibody-associated vasculitis, IgG4-related disorders, syphilis, tuberculosis, bacterial and fungal infections, cancer, and idiopathic diseases, when evaluation fails to reveal a cause. Among them, chronic infection with Propionibacterium acnes is a rare etiology of HP, and its pathology remains unclear.Case presentationAn 80-year-old man having refractory otitis media with effusion of the right ear presented with progressive right-sided headache and nausea. Post-contrast brain magnetic resonance imaging revealed right mastoiditis and remarkable thickening of the dura mater and enhancement of pia mater extending from the right middle cranial fossa to the temporal lobe.HP secondary to middle ear infection was suspected, and a biopsy of the right mastoid was performed. An anaerobic culture of the biopsied right mastoid showed the growth of P. acnes, and histopathological examination using P. acnes-specific monoclonal antibody (PAB antibody) revealed the infiltration of inflammatory cells with P. acnes. Moreover, using PAB antibody, P. acnes was detected in the biopsy specimen of the thickening dura mater. No granulomas were identified in either specimen. HP was resolved with long-term administration of antibiotics and steroids.ConclusionThis is the first documentation of pathologically demonstrated chronic HP associated with P. acnes infection followed by refractory otitis media. This report showed that chronic latent P. acnes infection induces chronic inflammation.

Role of diffusion-weighted imaging in evaluation of intracranial infections

Objective: The objective is to evaluate the role of diffusion weighted imaging (DWI) in evaluation of intracranial infections. Methods: The present study was conducted in the Department of Radiology, Jawaharlal Nehru Medical College, Sawangi, Maharashtra, India. Participants after understanding the study protocol and procedure were asked to give their written consent for the study. DWI was performed on 24 patients having ring-enhancing lesions on their post-contrast brain magnetic resonance imaging scans with infective etiology. Commonly found lesions were tuberculomas, cysticercosis, pyogenic abscess, and fungal infections. Correlation of all these findings was done with histopathology obtained in all these patients. DWI and mean apparent diffusion coefficient (ADC) value were calculated. Results: Tuberculomas showed heterogeneous areas of restricted diffusion on DWI were as pyogenic abscess showed homogenous restricted diffusion, the mean ADC values from of these lesions were 0.74 × 10−3 and 0.5 × 10−3 mm2/s, respectively. Fungal abscesses were also ring enhancing. They had restricted diffusion in the central nonenhancing portions. Mean ADC for all fungal lesions was 0.33 ± 0.06 × 10−3 mm2/s, with an average ADC ratio of 0.43. However, there was no significant difference between ADC values of pyogenic abscess and fungal abscess. The vesicular cysts of NCC showed ring enhancement but no significant restriction on DWI, the ADC values from the vesicular cysticercus cysts core measured (1.66 ± 0.29) ×10 − 3 mm2/s, which was highest among the infective intracranial infection. Conclusion: DWI is noninvasive method with high sensitivity and specificity which can help in differentiation of infective ring-enhancing lesions. Fungal cerebral abscesses may have central restricted diffusion similar to that of bacterial abscesses but with histologic features of acute or chronic inflammation and necrosis rather than suppuration. Altered water diffusion in these lesions likely reflects highly proteinaceous fluid and cellular infiltration. The tuberculoma and NCC lesions showed heterogeneous and no restriction on DWI respectively with significant change in the ADC values which helped in differentiating these lesions. This modality should be read in conjunction with conventional imaging.

MRI evaluation of soft tissue vascular malformations.

Background:Soft tissue vascular malformations are not uncommonly encountered in clinical practice and are often mistaken for other pathologies. Vascular anomalies are divided into vascular tumors and malformations. Vascular malformations progressively increase in size with increasing age and are classified into low-flow (venous, lymphatic, veno-lymphatic, capillary and capillary venous) and high-flow malformations (arteriovenous malformations (AVM) and arteriovenous fistula (AVF)) depending on the presence or absence of arterial flow. Aim:Aim of this study is to evaluate the Magnetic resonance imaging (MRI) features of the soft tissue vascular malformations and to classify the lesions depending on flow pattern. Materials and Methods:A total of 52 patients of soft tissue vascular malformations were included in this study over a period of 3 years. All patients underwent detailed clinical examination and dynamic post contrast MRI evaluation. Doppler and ultrasound were done as an adjunct. Results:There were 31 females and 21 male patients with age ranging from 9 to 34 years. In total 33 venous, 11 lymphatic, 8 veno-lymphatic malformations were seen. No case of high-flow malformation was seen. Majority of the lesions involved the head and neck region and the extremities. Fat saturated T2WI, STIR, and 3D dynamic post contrast sequences were found to be the most useful MRI sequences. Conclusion:MRI is the modality of choice for evaluating the soft tissue vascular malformations. It depicts the extent of the lesion, classifies the lesions into low or high flow and helps in treatment planning.

Tumor width on T1-weighted MRI images of glioblastoma as a prognostic biomarker: a mathematical model

We construct a minimal macroscopic model of glioblastoma growth including necrosis to explain the recently observed correlation between MRI-observed features and tumor growth speed. A theoretical study of the modified model was carried out. In particular, we obtained an expression for the minimal wave speed of the traveling wave solutions. We also solved numerically the model using a set of realistic parameter values and used these numerical solutions to compare the model dynamics against patient’s imaging and clinical data. The mathematical model provides theoretical support to the observation that tumors with broad contrast enhancing areas as observed in T1-weighted pretreatment postcontrast magnetic resonance images have worse survival than those with thinner areas.

Communicating spinal epidural thoracic arachnoid cyst en-bloc resection

Background: Spinal extradural arachnoid cyst is an uncommon, expanding lesion which may communicate with the subarachnoid space, The etiology still remains unclear, but the most accepted explanation is the existence of areas of weakness in the spinal dura , Spinal arachnoid cysts are usually in the thoracic spine, and they may cause symptoms due to spinal cord compression.&#x0D; Case Presentation: Patient is a 54-years-old female who presented with progressive back pain and motor deficit, Magnetic resonance imaging (MRI) study revealed an extradural cyst extending from T2 to T4 isointense with the cerebrospinal fluid (CSF) on all sequences and did not enhance on T1-weighted post-contrast MRI. Patient underwent T2-T4 laminectomy, en-bloc resection of the lesion was achieved and the histopathological examination objectified an arachnoid cyst.&#x0D; Conclusion: Spinal extradural arachnoid cyst can cause neurologic deficit and the mainstay of treatment in patients with neurological symptoms is surgical removal of the cyst together with ligation of the communicating pedicle and closure of the dural defect.

TMOD-34. A RADIOMIC SIGNATURE OF INFILTRATION IN PERITUMORAL EDEMA PREDICTS SUBSEQUENT RECURRENCE IN GLIOBLASTOMA

Abstract BACKGROUND The malignant parenchyma in glioblastoma extends beyond the enhancing borders of tumor on postcontrast T1-weighted magnetic resonance imaging (MRI), which is the primary target of treatment. Such non-enhancing tumor invasion into the peri-tumoral edema (PED) is, however, not usually distinguishable on conventional MRI. The aim of this study was to evaluate pre-operative MRI in the PED to assess whether areas of tumor infiltration and early recurrence can be detected. METHODS A cohort of 90 de novo glioblastoma patients from a single institution (Penn) was selected. All included patients had preoperative multi-parametric MRI (mpMRI;T1,T1Gd,T2,T2-FLAIR,ADC), underwent initial gross-total-resection followed by standard chemoradiation, and had pathologically-confirmed recurrence. An extensive panel of handcrafted features, including shape, volume, intensity distributions, texture, was extracted from mpMRI scans. Predictive modeling for estimation of PED infiltration was performed using sequential feature selection approach designed with a support vector machine classifier and through a Leave-one-out cross-validation approach in the Penn cohort. Generalizability of the model was evaluated by applying it on a cohort of 20 patients from a second institution (Case), and predicted probability distributions in PED were compared in both the cohorts. RESULTS Spatial probability maps, representing the likelihood of tumor infiltration and eventual recurrence, were binarized at 50% cutoff, and compared with actual recurrence on post-recurrence scans. The cross-validated accuracy of our model within Penn cohort was 81.35% (odds-ratio=3.62, sensitivity/specificity=78.26/81.35). The model trained on the Penn cohort, when applied on the Case cohort, produced almost similar intensity distribution in the PED, suggesting that the method has potential for robust performance across institutions. The comparison of intensity distributions revealed higher ADC and T2-FLAIR in non-recurrent regions compared to recurrent ones. CONCLUSION Multi-parametric pattern analysis of mpMRI across multiple institutions generates similar, accurate estimates of spatial extent and patterns of recurrence in PED, which may guide strategies for treatment intensification in glioblastoma.