Magnetic Resonance Imaging Features Research Articles

Comparative analysis of intraoperative and imaging features of invasive growth in pituitary adenomas.

Most pituitary adenomas, also termed pituitary neuroendocrine tumors (PitNETs), are benign in nature and can be treated effectively by surgical resection, medical treatment and in special cases by radiotherapy. However, invasive growth can be an important feature of a more aggressive behavior and adverse prognosis. Extension of pituitary adenomas into the cavernous sinus can be categorized according to the Knosp criteria on magnetic resonance imaging (MRI). Comparative analyses of MRI features and intraoperative findings of invasive growth regarding different clinical factors are still scarce. We performed a retrospective single-center analysis of 764 pituitary adenomas that were surgically treated between October 2004 and April 2018. Invasive growth was assessed according to the surgical reports and preoperative MR imaging (Knosp criteria). Clinical data such as patient age at diagnosis and gender, histopathological adenoma type as well as extent of resection were collected. Invasive features on MRI were seen in 24.4% (Knosp grade 3A - 4, 186/764) of cases. Intraoperatively, invasion was present in 42.4% (324/764). Complete resection was achieved in 80.0% of adenomas and subtotal resection in 20.1%. By multivariate analysis, invasion according to intraoperative findings was associated with the sparsely granulated corticotroph (SGCA, p=0.0026) and sparsely granulated somatotroph (SGSA, p=0.0103) adenoma type as well as age (p=0.0287). Radiographic invasion according to Knosp grades 3A-4 correlated with age (p=0.0098), SGCAs (p=0.0005), SGSAs (p=0.0351) and gonadotroph adenomas (p=0.0478).Both criteria of invasion correlated with subtotal resection (p=0.0001, respectively). Both intraoperative and radiographic signs of invasive growth are high-risk lesions for incomplete extent of resection and occur more frequently in older patients. A particularly high prevalence of invasion can be found in the sparsely granulated corticotroph and somatotroph adenoma types. Cavernous sinus invasion is also more common in gonadotroph adenomas. Usage of the Knosp classification is a valuable preoperative estimation tool.

The value of whole tumor apparent diffusion coefficient histogram parameters in predicting meningiomas progesterone receptor expression.

This study investigated the value of whole tumor apparent diffusion coefficient (ADC) histogram parameters and magnetic resonance imaging (MRI) semantic features in predicting meningioma progesterone receptor (PR) expression. The imaging, pathological, and clinical data of 53 patients with PR-negative meningiomas and 52 patients with PR-positive meningiomas were retrospectively reviewed. The whole tumor was outlined using Firevoxel software, and the ADC histogram parameters were calculated. The differences in ADC histogram parameters and MRI semantic features were compared between the two groups. The predictive values of parameters for PR expression were assessed using receiver operating characteristic curves. The correlation between whole-tumor ADC histogram parameters and PR expression in meningiomas was also analyzed. Grading was able to predict the PR expression in meningiomas (p = 0.012), though the semantic features of MRI were not (all p > 0.05). The mean, Perc.01, Perc.05, Perc.10, Perc.25, and Perc.50 histogram parameters were able to predict meningioma PR expression (all p < 0.05). The predictive performance of the combined histogram parameters improved, and the combination of grade and histogram parameters provided the optimal predictive value, with an area under the curve of 0.849 (95%CI: 0.766-0.911) and sensitivity, specificity, ACC, PPV, and NPV of 73.08%, 81.13%, 77.14%, 79.20%, and 75.40%, respectively. The mean, Perc.01, Perc.05, Perc.10, Perc.25, and Perc.50 histogram parameters were positively correlated with PR expression (all p < 0.05). Whole tumor ADC histogram parameters have additional clinical value in predicting PR expression in meningiomas.

Case report: Magnetic resonance imaging features with postoperative improvement of atypical cervical glioma characterized by predominant extramedullary distribution in a dog

Case report: Magnetic resonance imaging features with postoperative improvement of atypical cervical glioma characterized by predominant extramedullary distribution in a dog

Differentiating mixed epithelial and stromal tumor family from predominantly cystic renal cell carcinoma using magnetic resonance imaging-based Bosniak classification system version 2019.

To differentiate mixed epithelial and stromal tumor family (MESTF) of the kidney from predominantly cystic renal cell carcinoma (RCC) using the magnetic resonance imaging (MRI)-based Bosniak classification system version 2019 (v2019). The study included 36 consecutive patients with MESTF and 77 with predominantly cystic RCC who underwent preoperative renal MRI. One radiologist evaluated and documented the clinical and MRI characteristics (age, sex, laterality, R.E.N.A.L. Nephrometry Score [RNS], surgical approach, the signal intensity on T2-weighted imaging, restricted diffusion and enhancement features in corticomedullary phase). Blinded to clinical and pathological information, another two radiologists independently evaluated Bosniak category of all masses. Interobserver agreement based on Bosniak classification system v2019 was measured by the weighted Cohen/Conger's Kappa coefficient. Furthermore, predominantly cystic RCCs and MESTFs were divided into low (categories I, II, and IIF) and high-class (categories III, and IV) tumors. The independent sample t test (Mann-Whitney U test) or Pearson Chi-square test (Fisher's exact probability test) was utilized to compare clinical and imaging characteristics between MESTFs and predominantly cystic RCCs. The performance of the Bosniak classification system v2019 in distinguishing MESTF from predominantly cystic RCC was investigated via receiver operating characteristic curve analysis. MESTF and predominantly cystic RCC groups significantly differed in terms of age, lesion size, RNS, restricted diffusion, and obvious enhancement in corticomedullary phase, but not sex, laterality, surgical approach, and the signal intensity on T2WI. Interobserver agreement was substantially based on the Bosniak classification system v2019. There were 24 low-class tumors and 12 high-class tumors in the MESTF group. Meanwhile, 13 low-class tumors and 64 high-class tumors were observed in the predominantly cystic RCC group. The distribution of low- or high-class tumors significantly differed between the MESTF and predominantly cystic RCC groups. Bosniak classification system v2019 had excellent discrimination (cutoff value = category III), and an area under curve value was 0.81; accuracy, 80.5%; sensitivity, 87.0%; and specificity, 66.7%. The MRI-based Bosniak classification system v2019 can effectively distinguish MESTF from predominantly cystic RCC if category III was used as a cutoff reference.

Distinct features of ANCA-associated hypertrophic pachymeningitis compared to other etiologies: findings from a study of 74 patients.

We aimed to characterize the clinical and radiological features, and outcomes, of a large cohort of hypertrophic pachymeningitis (HP) patients from a single center. We conducted a retrospective study at a tertiary referral center, encompassing patients diagnosed with HP between 2003 and 2022. The diagnosis of HP relied on the identification of thickening of the dura mater via magnetic resonance imaging (MRI) of the brain or spine. We included 74 patients with a mean age of 43.6 ± 14.2 years, of whom 37 (50%) were male. Among them, 32 (43.2%) had an immune-mediated origin, including 21 with granulomatosis with polyangiitis (GPA) (predominantly PR3-ANCA positive), four with systemic lupus erythematosus, three with IgG4-related disease, three with idiopathic HP, and one with rheumatoid arthritis. Non-immune-mediated HP accounted for 45 cases (56.8%). Within this category, 21 (28.4%) were infectious cases, with 14 being Mycobacterium tuberculosis infection (TB-HP), and 21 (28.4%) were malignancy-associated HP. Clinical and MRI characteristics exhibited variations among the four etiological groups. Hypoglycorrhachia was primarily observed in infectious and malignancy-associated HP. Immune-mediated HP was associated with a peripheral pattern of contrast enhancement and the Eiffel-by-night sign. MRI features strongly indicative of TB-HP included leptomeningeal involvement, brain parenchymal lesions, and arterial stroke. MPO-ANCA GPA was associated with a higher prevalence of spinal HP. Within our cohort, GPA and Mycobacterium tuberculosis emerged as the predominant causes of HP. We identified significant disparities in clinical and radiological features among different etiologies, which could have implications for diagnosis.

Characteristic MR Imaging Findings of Cerebral Air Embolism Infarcts: A Case Series.

Infarcts from cerebral air embolism (CAE) are rare events with potentially catastrophic clinical consequences. The imaging features of CAE are not well defined in the literature. We report a novel constellation of MR imaging findings of cerebral arterial air emboli induced infarcts in a series of 6 patients. Awareness of the more distinguishing MR-imaging patterns of CAE may help establish this diagnosis and facilitate implementation of timely treatment.ABBREVIATIONS: CAE = cerebral air embolism.

MR Imaging Features of Critical Spinal Demyelinating Lesions Associated with Progressive Motor Impairment.

Progressive MS is typically heralded by a myelopathic pattern of asymmetric progressive motor weakness. Focal individual "critical" demyelinating spinal cord lesions anatomically associated with progressive motor impairment may be a compelling explanation for this clinical presentation as described in progressive solitary sclerosis (single CNS demyelinating lesion), progressive demyelination with highly restricted MR imaging lesion burden (2-5 total CNS demyelinating lesions; progressive paucisclerotic MS), and progressive, exclusively unilateral hemi- or monoparetic MS (>5 CNS demyelinating progressive unilateral hemi- or monoparetic MS [PUHMS] lesions). Critical demyelinating lesions appear strikingly similar across these cohorts, and we describe their specific spinal cord MR imaging characteristics. We performed a retrospective, observational MR imaging study comparing spinal cord critical demyelinating lesions anatomically associated with progressive motor impairment with any additional "noncritical" (not anatomically associated with progressive motor impairment) spinal cord demyelinating lesions. All spinal cord MR images (302 cervical and 91 thoracic) were reviewed by an experienced neuroradiologist with final radiologic assessment on the most recent MR imaging. Anatomic association with clinical progressive motor impairment was confirmed independently by MS subspecialists. Ninety-one individuals (PUHMS, 37 [41%], progressive paucisclerosis 35 [38%], progressive solitary sclerosis 19 [21%]) with 91 critical and 98 noncritical spinal cord MR imaging demyelinating lesions were evaluated. MR imaging characteristics that favored critical spinal cord demyelinating lesions over noncritical lesions included moderate-to-severe, focal, lesion-associated spinal cord atrophy: 41/91 (45%) versus 0/98 (0%) (OR, 161.91; 9.43 to >999.9); lateral column axial location (OR, 10.43; 3.88-28.07); central region (OR, 3.23; 1.78-5.88); ventral column (OR, 2.98; 1.55-5.72); and larger lesion size of the axial width (OR, 2.01;1.49-2.72), transverse axial size (OR, 1.66; 1.36-2.01), or lesion area (OR, 1.14; 1.08-1.2). Multiple regression analysis revealed focal atrophy and lateral axial location as having the strongest association with critical demyelinating lesions. Focal, lesion-associated atrophy, lateral column axial location, and larger lesion size are spinal cord MR imaging characteristics of critical demyelinating lesions. The presence of critical demyelinating lesions should be sought as these features may be associated with the development of progressive motor impairment in MS.

Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer.

Lymph node (LN) staging in rectal cancer (RC) affects treatment decisions and patient prognosis. For radiologists, the traditional preoperative assessment of LN metastasis (LNM) using magnetic resonance imaging (MRI) poses a challenge. To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs. In this retrospective study, 270 LNs (158 nonmetastatic, 112 metastatic) were randomly split into training (n = 189) and validation sets (n = 81). LNs were classified based on pathology-MRI matching. Conventional MRI features [size, shape, margin, T2-weighted imaging (T2WI) appearance, and CE-T1-weighted imaging (T1WI) enhancement] were evaluated. Three radiomics models used 3D features from T1WI and T2WI images. Additionally, a nomogram model combining conventional MRI and radiomics features was developed. The model used univariate analysis and multivariable logistic regression. Evaluation employed the receiver operating characteristic curve, with DeLong test for comparing diagnostic performance. Nomogram performance was assessed using calibration and decision curve analysis. The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM. In the training set, the nomogram model achieved an area under the curve (AUC) of 0.92, which was significantly higher than the AUCs of 0.82 (P < 0.001) and 0.89 (P < 0.001) of the conventional MRI and radiomics models, respectively. In the validation set, the nomogram model achieved an AUC of 0.91, significantly surpassing 0.80 (P < 0.001) and 0.86 (P < 0.001), respectively. The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Arnold-Chiari Syndrome – a review

Arnold Chiari syndrome, also known as Chiari malformation, is a group of deformations of the posterior cranial fossa and hindbrain, consisting in the lowering of the cerebellum or its tonsils towards the occipital foramen. This leads to a reduction in the volume reserve within the foramen magnum, pressure on surrounding structures and obstruction of the flow of cerebrospinal fluid. The process is most often asymptomatic. Symptoms include headaches, neck pain, but also fainting, sinus bradycardia, coordination disorders and many others. Chiari malformation is often diagnosed incidentally. The basis of diagnosis is the detection of characteristic morphological features in magnetic resonance imaging. Surgical treatment is successfully used among patients with severe Arnold-Chiari syndrome and progression of clinical symptoms. Materials and methods Literature included in the PubMed, BioMed Central and Polish Medical Platform databases searched by means of the words such as Gamma Knife, CyberKnife, radiosurgery, stereotactic radiotherapy. Sources quoted in selected works were also used. Summary Arnold-Chiari malformation is often discovered incidentally. If the features observed on MRI suggest the above diagnosis, the patient should be referred to a neurologist. After excluding other possible causes of the imaged morphological features and performing a dedicated magnetic resonance imaging examination, the neurosurgeon decides whether to qualify for the procedure. In a selected group of patients, significant improvement can be expected after surgical treatment.

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment

ObjectivesAccurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI.MethodsWe recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-β (Aβ) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network.ResultsThe proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aβ (+) than with Aβ (−).ConclusionThe proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

CADASIL-A RARE PRESENTATION OF STROKE

Objective: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a hereditary syndrome caused by heterozygous mutations in the NOTCH3 gene that manifests in adulthood and is characterized by recurrent transient ischemic attacks and strokes, migraine-like headaches, psychiatric disturbance, and progressive dementia. Methods: This is a case report. Results: Current case presented with complain of dizziness and vomiting. The diagnosis was suspected mainly because of the typical brain magnetic resonance imaging (MRI). This shows the importance of brain MRI in the diagnosis of CADASIL. Conclusion: Increased awareness of neurologists and neuroradiologists about the typical MRI features of CADASIL is of vital importance to reach the diagnosis in a timely manner.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity

BackgroundEarly prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients.MethodsThe DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways.ResultsA 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635–0.741 and AUC = 0.650, 95%CI: 0.595–0.705) and tested (AUC = 0.686, 95%CI: 0.594–0.778 and AUC = 0.626, 95%CI: 0.529–0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722–0.816 and test: 0.762, 95%CI: 0.679–0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665–0.767 and test AUC = 0.695, 95%CI: 0.656–0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system.ConclusionDynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Sonographic Appearance of the Ischiocondylar Origin of the Adductor Magnus.

The adductor magnus ischiocondylar origin (AM-IO) tendon has often been described as a third proximal hamstring tendon due to its common origin on the ischial tuberosity as well as similar function. Prior studies have described the magnetic resonance imaging characteristics of the AM-IO; however, its appearance on ultrasound has not been well-detailed. The purpose of our study is to describe the sonographic appearance of the AM-IO and provide a structured scanning protocol for complete evaluation of the tendon.

Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma

BackgroundTo develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression.MethodsWe retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis.ResultsFor the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was − 0.03 and cumulative risk rates were calculated.Data conclusionTo assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.

(What's the story) morning glory? MRI findings in morning glory disc anomaly.

Morning glory disc anomaly (MGDA) is a rare congenital ophthalmologic disorder. Historically it has been diagnosed fundoscopically, with little in the literature regarding its imaging findings. The purpose of this study is to further characterize the orbital and associated intracranial magnetic resonance imaging (MRI) findings of MGDA in our tertiary pediatric center. A retrospective review was performed of fundoscopically-diagnosed cases of MGDA, that had been referred for MRI. All MRI studies were scrutinized for orbital and other intracranial abnormalities known to occur in association with MGDA. 18 of 19 cases of MGDA showed three characteristic MRI findings: funnel-shaped morphology of the posterior optic disc, abnormal soft tissue associated with the retrobulbar optic nerve, and effacement of adjacent subarachnoid spaces. The ipsilateral (intraorbital) optic nerve was larger in one patient and smaller in six. The ipsilateral optic chiasm was larger in two patients and smaller in one. This study represents a comprehensive radiological-led investigation into MGDA. It describes the most frequently-encountered MRI findings in MGDA and emphasizes the importance of MRI in this cohort, i.e., in distinguishing MGDA from other posterior globe abnormalities, in assessing the visual pathway, and in screening for associated intracranial abnormalities - skull base/cerebral, vascular, and facial. It hypothesizes neurocristopathy as an underlying cause of MGDA and its associations. Caliber abnormalities of the ipsilateral optic nerve and chiasm are a frequent finding in MGDA. Optic pathway enlargement should not be labeled "glioma". (239/250).

Magnetic resonance imaging characteristics of Graves orbitopathy with elevated IgG4 serum concentration

Magnetic resonance imaging characteristics of Graves orbitopathy with elevated IgG4 serum concentration

Radiological Features for Predicting the Status of CD8-Positive Lymphocytes in HER2 Positive Breast Cancer.

The level of tumor-infiltrating lymphocytes (TILs) in human epidermal growth factor receptor type 2 (HER2)-positive breast cancer (BC) is positively correlated with pathological complete response. To investigate the relationship between ultrasound (US) and magnetic resonance imaging (MRI) features and the level of CD8-positive TILs (CD8+-TILs) in patients with HER2-positive BC. Retrospective cohort study. This retrospective study included 155 consecutive women with HER2-positive BC. Patients were divided into two groups: CD8+-TILlow (< 35%) and CD8+-TILhigh (≥ 35%) groups. US and MRI features were evaluated using the BI-RADS lexicon, and the apparent diffusion coefficient (ADC) value was calculated using RadiAnt software. Univariate and multivariate analyses revealed the optimal US and MRI features for predicting CD8+-TIL levels. Receiver operating characteristic analysis and the Delong test were used to compare the diagnostic performance of US and MRI features. Furthermore, implementing a nomogram will increase clinical utility. Univariate analysis of US features showed significant differences in shape, orientation, and posterior echo between the two groups; however, there were no significant differences in margins, internal echo, and microcalcification. Multifactorial analysis revealed that shape, orientation, and posterior echo were independent risk factors, with odds ratios of 11.62, 2.70, and 0.16, respectively. In terms of MRI features, ADC was an independent predictor of CD8+-TIL levels. These three US features and the ADC performed well, with area under the curve (AUC) values of 0.802 and 0.705, respectively. The combination of US and ADC values had higher predictive efficacy (AUC = 0.888) than either US or ADC alone (p = 0.009, US_ADC vs. US; p < 0.001, US_ADC vs. ADC). US features (shape, orientation, and posterior echo) and ADC value may be a valuable tool for estimating CD8+-TIL levels in HER2-positive BC. The nomogram may help clinicians in making decisions.

Corticosteroid monotherapy versus combined cytarabine continuous rate infusion and corticosteroid therapy in dogs with meningoencephalitis of unknown origin: A blinded, randomized, controlled trial.

Treatment options available for meningoencephalitis of unknown origin (MUO) in dogs are suboptimal, and currently, no single treatment protocol appears to be superior. Compare neurological deterioration rates at 7 days between dogs with MUO treated with corticosteroids alone or combined with cytosine arabinoside (CA) continuous rate infusion (CRI) and compare clinical deterioration and survival at 30 and 100 days. Sixty-nine dogs with magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) features or both compatible with MUO. Parallel, blinded, randomized controlled trial. Simple randomization into 2 treatment groups: 4 mg/kg/day prednisolone (or dexamethasone equivalent) for 2 days or 200 mg/m2 CA CRI over 8 hours plus 2 mg/kg/day prednisolone. Blinding of the treatment protocol was carried out using reversible redaction of clinical records, and treatment failure was defined as deterioration of neurological assessment or death. Using intention-to-treat analysis, proportions failing treatment at 7, 30, and 100 days were compared using Fisher's exact test. All-cause mortality at 100 days was compared using Kaplan-Meier survival curves. Thirty-five dogs were allocated to corticosteroid only, and 34 dogs were allocated to combined CA CRI and corticosteroid. Proportions failing treatment at 7, 30, and 100 days were 7/35 (20%), 9/35 (26%), and 15/35 (43%) in the corticosteroid-only group and 8/34 (24%), 11/34 (32%), and 23/34 (68%) in the corticosteroid and CA CRI group. All-cause mortality at 100 days was not significantly different between groups (P = .62). Clinically relevant treatment-related adverse effects were not observed. We foundno difference in outcome between corticosteroid monotherapy and combined cytarabine CRI and corticosteroid therapy at 7, 30, and 100 days after diagnosis in dogs with MUO.

Ectopic Pituitary Neuroendocrine Tumors/Adenomas Around the Sella Turcica

Functional or non-secretory ectopic pituitary neuroendocrine tumors (PitNET) can form around the sella turcica during the development of the adenohypophysis by differentiating and detaching from the pharyngeal roof. These tumors usually appear in the sphenoid sinus, clivus, cavernous sinus, infundibulum, and suprasellar cistern. Ectopic PitNETs typically display the characteristic magnetic resonance imaging findings of pituitary adenomas. However, preoperative diagnosis of PitNETs is usually challenging because of the variety of clinical and imaging presentations, locations, and sizes. Ectopic suprasellar PitNETs resemble mass lesions in the pituitary stalk. Ectopic cavernous sinus of PitNETs are typically microadenomas in the medial wall. Ectopic sphenoclival tumors are characterized by more aggressive tumor activity than the other ectopic PitNETs. Although ectopic PitNETs are exceedingly rare, they should be considered as a differential diagnosis for masses around the sella turcica. Treatment of the disease should be individualized and may include medical care, surgical resection, gamma-knife radiosurgery, and radiotherapy.

Brainstem Chipmunk Sign: A Diagnostic Imaging Clue across All Subtypes of Alexander Disease.

While classic brain MR imaging features of Alexander disease have been well-documented, lesional patterns can overlap with other leukodystrophies, especially in the early stages of the disease or in milder phenotypes. We aimed to assess the utility of a new neuroimaging sign to help increase the diagnostic specificity of Alexander disease. A peculiar bilateral symmetric hyperintense signal on T2-weighted images affecting the medulla oblongata was identified in an index patient with type I Alexander disease. Subsequently, 5 observers performed a systematic MR imaging review for this pattern by examining 55 subjects with Alexander disease and 74 subjects with other leukodystrophies. Interobserver agreement was assessed by the κ index. Sensitivity, specificity, and receiver operating characteristic curves were determined. The identified pattern was present in 87% of subjects with Alexander disease and 14% of those without Alexander disease leukodystrophy (P < .001), 3 with vanishing white matter, 4 with adult polyglucosan body disease, and 3 others. It was found equally in both type I and type II Alexander disease (28/32, 88% versus 18/21, 86%; P = .851) and in subjects with unusual disease features (2/2). Sensitivity (87.3%; 95% CI, 76.0%-93.7%), specificity (86.5%; 95% CI, 76.9%-92.5%), and interobserver agreement (κ index = 0.82) were high. The identified pattern in the medulla oblongata, called the chipmunk sign due to its resemblance to the face of this rodent, is extremely common in subjects with Alexander disease and represents a diagnostic tool that can aid in early diagnosis, especially in subjects with otherwise atypical MR imaging findings and/or clinical features.