Postcontrast T1-weighted Magnetic Resonance Imaging Research Articles

Development and validation of a fully automatic tissue delineation model for brain metastasis using a deep neural network.

Stereotactic radiosurgery (SRS) treatment planning requires accurate delineation of brain metastases, a task that can be tedious and time-consuming. Although studies have explored the use of convolutional neural networks (CNNs) in magnetic resonance imaging (MRI) for automatic brain metastases delineation, none of these studies have performed clinical evaluation, raising concerns about clinical applicability. This study aimed to develop an artificial intelligence (AI) tool for the automatic delineation of single brain metastasis that could be integrated into clinical practice. Data from 426 patients with postcontrast T1-weighted MRIs who underwent SRS between March 2007 and August 2019 were retrospectively collected and divided into training, validation, and testing cohorts of 299, 42, and 85 patients, respectively. Two Gamma Knife (GK) surgeons contoured the brain metastases as the ground truth. A novel 2.5D CNN network was developed for single brain metastasis delineation. The mean Dice similarity coefficient (DSC) and average surface distance (ASD) were used to assess the performance of this method. The mean DSC and ASD values were 88.34%±5.00% and 0.35±0.21 mm, respectively, for the contours generated with the AI tool based on the testing set. The DSC measure of the AI tool's performance was dependent on metastatic shape, reinforcement shape, and the existence of peritumoral edema (all P values <0.05). The clinical experts' subjective assessments showed that 415 out of 572 slices (72.6%) in the testing cohort were acceptable for clinical usage without revision. The average time spent editing an AI-generated contour compared with time spent with manual contouring was 74 vs. 196 seconds, respectively (P<0.01). The contours delineated with the AI tool for single brain metastasis were in close agreement with the ground truth. The developed AI tool can effectively reduce contouring time and aid in GK treatment planning of single brain metastasis in clinical practice.

Microanatomical findings with relevance to trigeminal ganglion enhancement on post-contrast T1-weighted magnetic resonance images in dogs.

Trigeminal ganglion contrast enhancement (TGCE) is reported to be a normal and a common finding on magnetic resonance imaging studies of dogs, cats and humans. The intent of the present study was to describe the anatomical characteristics of the trigeminal ganglion, its surrounding structures, and histological features that are relevant to explain or hypothesize on the reason for TGCE on T1-weighted post-contrast MRI studies of the brain in dogs. Eight dog cadavers were dissected to study the anatomy of the trigeminal ganglion. The presence and anatomy of vessels was studied by dissection and by histological techniques. Two trigeminal ganglia were isolated and stained with hematoxylin-eosin (HE). Two other trigeminal ganglia included in the trigeminal canal and trigeminal cavity were decalcified with formic acid/formalin for 12 weeks and stained with HE to study the related vessels. Additionally, a corrosion cast was obtained from a separate canine specimen. Leptomeninges and a subarachnoid space were identified at the level of the trigeminal nerve roots and the trigeminal ganglion. No subarachnoid space was identified and leptomeninges were no longer present at the level of the three trigeminal nerve branches. Small arterial vessels ran to and supplied the trigeminal ganglion, passing through the dura mater. No venous plexus was visualized at the level of the trigeminal ganglion in the dissections. A complex arterial vascular network was identified within the leptomeningeal covering of the trigeminal ganglion and was best appreciated in the corrosion cast. Histological examination revealed small-to moderate-sized blood vessels located in the epineurium around the ganglion; from there a multitude of arterioles penetrated into the perineurium. Small endoneurial branches and capillaries penetrated the ganglion and the trigeminal nerve branches. Limitations to this study include the limited number of canine specimens included and the lack of electron microscopy to further support current hypotheses included in our discussion. In conclusion, this study provides further support to the theory that TGCE in dogs may be due an incomplete blood-nerve barrier or blood-ganglion barrier at the interface between the central nervous system and the peripheral nervous system.

Does sevoflurane sedation in pediatric patients lead to "pseudo" leptomeningeal enhancement in the brain on 3 Tesla magnetic resonance imaging?

Prominent leptomeningeal contrast enhancement (LMCE) in the brain is observed in some pediatric patients during sedation for imaging. However, based on clinical history and cerebrospinal fluid analysis, the patients are not acutely ill and do not exhibit meningeal signs. Our study determined whether sevoflurane inhalation in pediatric patients led to this pattern of 'pseudo' LMCE (pLMCE) on 3 Tesla magnetic resonance imaging (MRI). To highlight the significance of pLMCE in pediatric patients undergoing enhanced brain MRI under sedation to avoid misinterpretation in reports. A retrospective cross-sectional evaluation of pediatric patients between 0-8 years of age was conducted. The patients underwent enhanced brain MRI under inhaled sevoflurane. The LMCE grade was determined by two radiologists, and interobserver variability of the grade was calculated using Cohen's kappa. The LMCE grade was correlated with duration of sedation, age and weight using the Spearman rho rank correlation. A total of 63 patients were included. Fourteen (22.2%) cases showed mild LMCE, 48 (76.1%) cases showed moderate LMCE, and 1 case (1.6%) showed severe LMCE. We found substantial agreement between the two radiologists in detection of pLMCE on post-contrast T1 imaging (kappa value = 0.61; P < 0.001). Additionally, we found statistically significant inverse and moderate correlations between patient weight and age. There was no correlation between duration of sedation and pLMCE. pLMCE is relatively common on post-contrast spin echo T1-weighted MRI of pediatric patients sedated by sevoflurane due to their fragile and immature vasculature. It should not be misinterpreted for meningeal pathology. Knowing pertinent clinical history of the child is an essential prerequisite to avoid radiological overcalling and the subsequent burden of additional investigations.

Temporal radiographic and histological study of necrosis development in a mouse glioblastoma model.

Tumor necrosis is a poor prognostic marker in glioblastoma (GBM) and a variety of other solid cancers. Accumulating evidence supports that necrosis could facilitate tumor progression and resistance to therapeutics. GBM necrosis is typically first detected by magnetic resonance imaging (MRI), after prominent necrosis has already formed. Therefore, radiological appearances of early necrosis formation and the temporal-spatial development of necrosis alongside tumor progression remain poorly understood. This knowledge gap leads to a lack of reliable radiographic diagnostic/prognostic markers in early GBM progression to detect necrosis. Recently, we reported an orthotopic xenograft GBM murine model driven by hyperactivation of the Hippo pathway transcriptional coactivator with PDZ-binding motif (TAZ) which recapitulates the extent of GBM necrosis seen among patients. In this study, we utilized this model to perform a temporal radiographic and histological study of necrosis development. We observed tumor tissue actively undergoing necrosis first appears more brightly enhancing in the early stages of progression in comparison to the rest of the tumor tissue. Later stages of tumor progression lead to loss of enhancement and unenhancing signals in the necrotic central portion of tumors on T1-weighted post-contrast MRI. This central unenhancing portion coincides with the radiographic and clinical definition of necrosis among GBM patients. Moreover, as necrosis evolves, two relatively more contrast-enhancing rims are observed in relationship to the solid enhancing tumor surrounding the central necrosis in the later stages. The outer more prominently enhancing rim at the tumor border probably represents the infiltrating tumor edge, and the inner enhancing rim at the peri-necrotic region may represent locally infiltrating immune cells. The associated inflammation at the peri-necrotic region was further confirmed by immunohistochemical study of the temporal development of tumor necrosis. Neutrophils appear to be the predominant immune cell population in this region as necrosis evolves. This study shows central, brightly enhancing areas associated with inflammation in the tumor microenvironment may represent an early indication of necrosis development in GBM.

Automated Brain Metastases Segmentation With a Deep Dive Into False-positive Detection

PurposeThe clinical management of brain metastases after stereotactic radiosurgery (SRS) is difficult, because a physician must review follow-up magnetic resonance imaging (MRI) scans to determine treatment outcome, which is often labor intensive. The purpose of this study was to develop an automated framework to contour brain metastases in MRI to help treatment planning for SRS and understand its limitations. Methods and MaterialsTwo self-adaptive nnU-Net models trained on postcontrast 3-dimensional T1-weighted MRI scans from patients who underwent SRS were analyzed. Performance was evaluated by computing positive predictive value (PPV), sensitivity, and Dice similarity coefficient (DSC). The training and testing sets included 3482 metastases on 845 patient MRI scans and 930 metastases on 206 patient MRI scans, respectively. ResultsIn the per-patient analysis, PPV was 90.1% ± 17.7%, sensitivity 88.4% ± 18.0%, DSC 82.2% ± 9.5%, and false positive (FP) 0.4 ± 1.0. For large metastases (≥6 mm), the per-patient PPV was 95.6% ± 17.5%, sensitivity 94.5% ± 18.1%, DSC 86.8% ± 7.5%, and FP 0.1 ± 0.4. The quality of autosegmented true-positive (TP) contours was also assessed by 2 physicians using a 5-point scale for clinical acceptability. Seventy-five percent of contours were assigned scores of 4 or 5, which shows that contours could be used as-is in clinical application, and the remaining 25% were assigned a score of 3, which means they needed minor editing only. Notably, a deep dive into FPs indicated that 9% were TP metastases not identified on the original radiology review, but identified on subsequent follow-up imaging (early detection). Fifty-four percent were real metastases (TP) that were identified but purposefully not contoured for target treatment, mainly because the patient underwent whole-brain radiation therapy before/after SRS treatment. ConclusionsThese findings show that our tool can help radiologists and radiation oncologists detect and contour tumors from MRI, make precise decisions about suspicious lesions, and potentially find lesions at early stages.

Contrast Enhancement Patterns in Pediatric Glioblastomas.

Brain tumors are the most common cause of cancer-related deaths among the pediatric population. Among these, pediatric glioblastomas (GBMs) comprise 2.9% of all central nervous system tumors and have a poor prognosis. The purpose of this study is to determine whether the imaging findings can be a prognostic factor for survival in children with GBMs. The imaging studies and clinical data from 64 pediatric patients with pathology-proven GBMs were evaluated. Contrast enhancement patterns were classified into focal, ring-like, and diffuse, based on preoperative postcontrast T1-weighted magnetic resonance images. We used the Kaplan-Meier method and Cox proportional hazard regression to evaluate the prognostic value of imaging findings. Patients with ring-enhanced GBMs who underwent gross total resection or subtotal resection were found to have a significantly shorter progression-free survival ( P = 0.03) comparing with other enhancing and nonenhancing glioblastomas. In this study, we analyzed survival factors in children with pediatric glioblastomas. In the group of patients who underwent gross total resection or subtotal resection, those patients with focal-enhanced GBMs had significantly longer progression-free survival ( P = 0.03) than did those with other types of enhancing GBMs (diffuse and ring-like).

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

Simple SummaryGlioblastoma (GBM), the most common malignant adult primary brain tumour, has a prognosis of ~12–15 months. Poor prognosis is partly due to the inability to accurately define the extent of tumour infiltration; currently demarcated using magnetic resonance imaging (MRI) sequences (e.g., post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced (DCE-MRI)). Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) may depict GBM better than MRI. This prospective pilot study aimed to explore the relationship of 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients with GBM undergoing standard-of-care adjuvant chemoradiotherapy. A parallel mouse glioma model was used to investigate the relationship between 18F-fluciclovine PET, MRI and tumour biology. Clinical results showed that GBM volume on 18F-fluciclovine PET tended to be larger than Gd-T1 and DCE-MRI in patients with shorter overall survival (OS) but smaller in patients with longer OS. The preclinical study confirmed that 18F-fluciclovine uptake reflected biologically active tumour. Results suggest that 18F-fluciclovine PET may better define GBM infiltration than MRI.Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1–6) and grouped according to overall survival (OS)—short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Radiomic features quantifying pixel-level characteristics of breast tumors from magnetic resonance imaging predict risk factors in triple-negative breast cancer.

e12612 Background: Computationally derived quantitative imaging (radiomic) features that describe tumor phenotypes at the pixel level have demonstrated associations with clinical characteristics in early investigations of other cancers. This implies that molecular differences among tumors may be reflected in their structure on the scales probed by 3D magnetic resonance imaging (MRI). We investigated whether radiomic features computed over tumor volumes from pre-treatment breast MRI could predict risk factors in triple-negative breast cancer (TNBC). Methods: We evaluated breast tumors on pre-treatment, post-contrast T1-weighted MRI from 156 patients with non-metastatic TNBC who underwent neoadjuvant chemotherapy. Tumor regions of interest were segmented by a convolutional neural network algorithm, with validation by breast radiologists. Features quantifying tumor shape and texture were extracted for the largest tumor present in each patient. We identified 23 principal components (PCs) describing these data within the original 364-dimensional feature space for further analysis. Tumor volume was also extracted for comparison with the shape and texture PCs, clinical variables and outcomes, but was kept separate from other radiomic features, since it directly correlates with clinical stage. We compiled for the cohort clinical variables including demographics, stage, grade, and, where available, absolute lymphocyte count (ALC) and Ki-67, a cellular proliferation index routinely used in clinical practice. We then performed a series of univariate and multivariate regression analyses to identify radiomic PCs and clinical variables that significantly predict patient outcomes, and radiomic PCs that predict established risk factors. Our multivariate analyses utilized 5-fold cross-validation and Monte-Carlo determination of p-values (based on 3000 random samplings from the null hypothesis), to ensure statistical rigor in identifying predictive relationships while correcting for multiple hypothesis testing. Results: Our univariate analyses confirmed expected correlations between: overall survival and pre-treatment tumor volume (p = 0.010); survival and ALC (p = 0.002); and clinical stage and tumor volume (p = 1.2⨉10-7). From our multivariate analysis, shape and texture radiomic features were predictive of: tumor volume (p &lt; 0.001); clinical stage (p &lt; 0.001); and Ki-67 (p = 0.02). We confirmed that Ki-67 was predictive of post-treatment residual cancer (p = 0.014), as has been previously reported. Conclusions: Radiomic features predict breast cancer risk factors that are significant for determining outcomes for TNBC patients. Combinations of radiomic shape and texture features track closely with tumor volumes, stage, and proliferative activity, potentially reflecting underlying molecular evolution.

Pituitary Stalk Germ Cell Tumors: Retrospective Case Series and Literature Review.

Objective Intracranial germ cell tumors with isolated pituitary stalk involvement are rare. Early recognition and long-term monitoring deserve further exploration. Methods A retrospective study reviewing eleven intracranial germ cell tumor patients with isolated pituitary stalk involvement was performed. Results Seven boys and four girls who presented with a hyperintense pituitary stalk on postcontrast T1-weighted magnetic resonance imaging without a posterior pituitary signal were included. The average maximum width of the pituitary stalk was 5.2 ± 1.6 mm. Polydipsia and polyuria occurred in all patients, followed by growth retardation, fatigue, and amenorrhoea. Eight patients (72%) had concomitant partial anterior pituitary hormone deficiency. Seven patients initially had elevated human chorionic gonadotropin levels. After chemoradiotherapy, ten patients attended follow-up. Central diabetes insipidus remained in all survivors, and four (40%) of them had concomitant partial anterior pituitary hormone deficiency, primarily of growth hormone and insulin-like growth factor-1. The causes of the delayed diagnosis of previous studies were mainly negative tumor markers and the initial pathological diagnosis of autoimmune diseases. Conclusion Isolated pituitary stalk lesions could be a signal of intracranial germ cell tumors, especially coexisting with diabetes insipidus, hypopituitarism, and a worse response to glucocorticoid therapy. Negative results of tumor markers and pathology could not exclude the diagnosis. Chemoradiotherapy is an effective therapy, leaving mild-t-moderate hypothalamus-pituitary dysfunction. This rare neuroimaging feature may be used as a factor to predict long-term neuroendocrine outcomes.

Radiomics Profiling Identifies the Incremental Value of MRI Features beyond Key Molecular Biomarkers for the Risk Stratification of High-Grade Gliomas.

Objective To identify the incremental value of magnetic resonance imaging (MRI) features beyond key molecular biomarkers for the risk stratification of high-grade gliomas (HGGs). Methods A total of 241 patients with preoperative magnetic resonance (MR) images and clinical and genetic data were retrospectively collected from our institution and The Cancer Genome Atlas/The Cancer Imaging Archive (TCGA/TCIA) dataset. Radiomic features (n = 1702) were extracted from both postcontrast T1-weighted (CE-T1) and T2-weighted fluid attenuation inversion recovery (T2FLAIR) MR images. The least absolute shrinkage and selection operator (LASSO) method was used to select effective features. A multivariate Cox proportional risk regression model was established to explore the prognostic value of clinical features, molecular biomarkers, and radiomic features. Kaplan–Meier survival analysis and the log-rank test were used to evaluate the prognostic model, and a stratified analysis was conducted to demonstrate the incremental value of the radiomics signature. A nomogram was developed to predict the 1-year, 2-year, and 3-year overall survival (OS) probabilities of the patients with HGGs. Results The radiomics signature provided significant prognostic value for the risk stratification of patients with HGGs. The combined model integrating the radiomics signature with clinical data (age) and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status had the best prognostic value, with C-index values of 0.752 and 0.792 in the training set and external validation set, respectively. Stratified Kaplan–Meier survival analysis showed that the radiomics signature could identify the risk subgroups in different clinical and molecular subgroups. Conclusion This radiomics signature can be used for the risk stratification of patients with HGGs and has incremental value beyond key molecular biomarkers, providing a preoperative basis for individualized diagnosis and treatment decision-making.

Bi-directional Synthesis of Pre- and Post-contrast MRI via Guided Feature Disentanglement.

Magnetic resonance imaging (MRI) with gadolinium contrast is widely used for tissue enhancement and better identification of active lesions and tumors. Recent studies have shown that gadolinium deposition can accumulate in tissues including the brain, which raises safety concerns. Prior works have tried to synthesize post-contrast T1-weighted MRIs from pre-contrast MRIs to avoid the use of gadolinium. However, contrast and image representations are often entangled during the synthesis process, resulting in synthetic post-contrast MRIs with undesirable contrast enhancements. Moreover, the synthesis of pre-contrast MRIs from post-contrast MRIs which can be useful for volumetric analysis is rarely investigated in the literature. To tackle pre- and post- contrast MRI synthesis, we propose a BI-directional Contrast Enhancement Prediction and Synthesis (BICEPS) network that enables disentanglement of contrast and image representations via a bi-directional image-to-image translation(I2I)model. Our proposed model can perform both pre-to-post and post-to-pre contrast synthesis, and provides an interpretable synthesis process by predicting contrast enhancement maps from the learned contrast embedding. Extensive experiments on a multiple sclerosis dataset demonstrate the feasibility of applying our bidirectional synthesis and show that BICEPS outperforms current methods.

Aggressive Angiomyxoma of the Pelvis and Perineum: A Case Report with Radiologic-Pathologic Correlation

Aggressive angiomyxoma is a rare mesenchymal tumor mostly observed in women of childbearing age. Although it is often located in the vulva, it can also be observed in the paravaginal, perirectal areas, perineum and pelvis. It appears as a locally aggressive, large, infiltrative mass. Complete surgical excision is often difficult and has high recurrence rates. Magnetic resonance imaging (MRI) plays an important role in preoperative diagnosis of aggressive angiomyxoma. The typical swirling appearance on T2-weighted and post-contrast T1-weighted MRI series is diagnostic for aggressive angiomyxoma. Here, we present a 51-year-old female patient with pelvic-perineal aggressive angiomyxoma, accompanied by radiological and pathological findings.

Role of contrast-enhanced FLAIR MRI in diagnosis of intracranial lesions

BackgroundMR imaging plays a significant role in detection and characterization of different brain diseases. The role of the post-contrast T1-weighted image magnetic resonance imaging (T1W MRI) sequence has been widely established in previous studies and clinical practice. In this study, we aim to share our experience as regards the added value of contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) sequence in the diagnosis of various intracranial pathological conditions and evaluate its usefulness in comparison with post-contrast T1W images.ResultsBased on the final radiological diagnosis, the total cases were subdivided into three categories, and the majority of our cases were tumors (81.2%), followed by multiple sclerosis (11.8%), and the least was central nervous system infection (7.1%). CE-FLAIR showed superior enhancement in 35 cases (50.7) and equal enhancement in 25 cases (36.3%). However, it showed less enhancement than post-contrast T1W images in 9 cases (13%). Excellent inter-observer agreement (97.65%) was noted. Regarding lesion conspicuity, good delineation was found in the majority of cases (64.7%), fair delineation in 12.9%, and no delineation in 22.4%. A statistically significant difference was found in signal intensity of lesion between pre- and post-contrast FLAIR sequences. Contrast to background ratio was statistically significant in CE FLAIR images in comparison to CE T1 images.ConclusionCE-FLAIR imaging should be used as a routine or adjunctive sequence to CE-T1WI to enhance early detection and increase the diagnostic confidence in MRI examination of different brain pathological conditions.

The Effect of Radiation on Meningioma Volume Change

Radiation therapy is a common treatment for meningiomas. Volume changes of meningiomas in response to radiation are not well characterized. This study seeks to quantify the volume change of meningiomas following radiation. Data were collected from a retrospective single-institution database of cases from 2005-2015. Tumors were measured using T1-weighted post-contrast magnetic resonance imaging. Volumes were calculated using the ABC/2 ellipsoidal approximation. A total of 63 patients fit the inclusion criteria; 37 patients (59%) received radiation following resection, 19 (30%) received radiation alone, 4 (6%) received radiation following a biopsy, and 3 (5%) had unknown surgical status. A total of 39 patients (62%) had skull base meningiomas; 43 tumors were World Health Organization (WHO) grade I, and 12 tumors were WHO grade II. Thirteen patients received radiosurgery, 43 received radiotherapy, and 7 received an unknown number of treatments. Eight patients did not attain local control and were excluded from volume analyses. WHO grade I meningiomas saw an average of 33% ± 19% decrease in tumor volume; WHO grade II tumor volumes decreased by an average 30% ± 23%. Radiosurgery saw an average volume decrease of 34% ± 13%, while radiotherapy resulted in volume decrease of 31% ± 21%. For those who achieved local control, there was an average decrease in tumor size of 30% ± 19%, 30% ± 22%, and 41% ± 19% over 0.5-1.5, 2.5-3.5, and >5 years, respectively. Meningiomas treated with radiation exhibit nonlinear decrease in size over time. The greatest decrease in tumor volume occurs within the first year and begins to plateau 5 years post-radiation treatment.

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.

Atypical infectious spondylitis with reduced bone marrow enhancement: "black vertebra sign".

A few patients suspected of having infectious spondylitis exhibited a reduced enhancement pattern on postcontrast T1-weighted (T1W) magnetic resonance imaging (MRI). To investigate the characteristics of infectious spondylitis patients who exhibited reduced vertebral enhancement. From January 2010 to November 2017, 456 patients with findings suspicious for infectious spondylitis on 706 postcontrast T1W imaging were retrospectively evaluated. When an affected vertebra exhibited markedly reduced enhancement compared to normal bone marrow (BM), the vertebra was termed a "black vertebra." MRI and computed tomography (CT) imaging findings within two-week intervals and the patients' clinical characteristics were reviewed. Ten patients (5 men, 5 women; mean age 66.4 years) whose MRI scans revealed the black vertebra sign were included. Among the 10 patients with black vertebrae, six patients exhibited signal voids in or around the affected vertebral bodies on T2-weighted (T2W) images. Eight patients showed air bubbles on CT images, suggestive of emphysematous infection. However, the typical image findings of infectious spondylitis were uncommon, namely, low BM signal intensity (SI) on T1W images (n=1) and intradiscal fluid-equivalent SI on T2W images (n=5) at an early stage. On follow-up MRI (average interval 7.2 weeks from initial MRI), available for five patients, marked progression of infection was evidenced by increased numbers of affected segments (n=3), low T1 SIs of the affected vertebrae (n=5), and increased contrast enhancement (n=3). Five patients underwent surgery to treat infections not controlled by antibiotics. A black vertebra sign on postcontrast T1W imaging seems to reflect an early emphysematous infection.

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.

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.

Cranial Nerve Enhancement in Multiple Sclerosis Is Associated With Younger Age at Onset and More Severe Disease.

Background: The overall frequency of cranial nerve pathology, including cranial nerves other than the trigeminal nerve, as well as its relation to brainstem lesion formation on magnetic resonance imaging (MRI) and clinical correlates in multiple sclerosis (MS) is unknown.Objective: We aimed to determine the frequency of cranial nerve enhancement on MRI, and its association with brainstem lesion formation and clinical outcomes.Methods: We retrospectively analyzed, in 183 patients, (RRMS: 156, SPMS: 15, PPMS: 6, CIS: 6) 651 MRIs (76.5% on the identical scanner Siemens Trio Tim, 3T with identical MRI protocols). Frequencies of cranial nerve enhancement on post contrast T1-weighted MRIs were compared to lesion counts and the MS-severity-score.Results: Cranial nerve enhancement was present in 8.2% of the analyzed MS patients (oculomotor-nerve: 1.1%, trigeminal-nerve: 2.7%, abducens-nerve: 2.2%, facial-/vestibulocochlear nerve: 1.6%, vagal-nerve: 0.5%). Of those, 13% suffered from repeated episodes and 27% exhibited a cranial nerve enhancement duration of >12 months. Age at MS onset was lower in patients with cranial nerve enhancement, 23 vs. 28 years, p = 0.049. The MS-severity-score, 5.15 vs. 0.88 (p = 0.019), the T2 brainstem-, 1 vs. 0 (p = 0.041), and the total intracranial contrast-enhancing lesion counts, 2 vs. 0 (p = 0.000), were higher in patients with cranial nerve enhancement, compared to age-, disease duration-, and gender- matched MS patients.Conclusions: Cranial nerve enhancement, present in 8.2% of our patients, was associated with a younger age at MS onset, brainstem lesions, and a more severe disease course.