An 8-yr-old French Bulldog was presented with a non-ambulatory tetraparesis. Magnetic resonance showed an intradurally located mass at the level of the right second cervical nerve root. The mass was surgically removed and the dog was ambulatory within 4 d. A 10-mo post-surgical imaging follow-up revealed a recurrence of the primary mass and another intradural/intramedullary mass at the level of the first thoracic vertebral body. Overall histological features were suggestive of malignant peripheral nerve sheath tumor (MPNST) for both masses. Immunohistochemistry was found weak but diffusely positive for S-100 and neurono-specific enolase for both masses. A diagnosis of primary MPNST for the cervical mass and of metastasis for the thoracic mass was made, possibly disseminated via the subarachnoidal space. To our knowledge, the central nervous system metastasis of MPNSTs has not previously been reported in dogs. The clinician should be aware that these tumors, albeit rarely, can metastasize to the central nervous system.
Rationale and Aim
This study is aimed at identifying possible patterns of vascular wall disarray and remodeling in radial arteries of patients with fibromuscular dysplasia (FMD), by means of ultrahigh frequency ultrasound (UHFUS).
Methods
UHFUS scans of the radial arteries and of 30 FMD patients and 30 healthy controls were obtained by VevoMD (70 MHz probe, FUJIFILM, VisualSonics, Toronto, Canada). 10 end-diastolic frames for each subject were analyzed. 74 radiomic features and 4 engineered parameters were extracted: intima-media thickness (IMT) and adventitia thickness (AT), an adjunctive acoustic interface for each layer (IMT and AT triple signal). The extracted parameters were used to train classification models, using Support Vector Machine Linear (SVM), K-Nearest Neighbors (KNN), Logistic Regression, Linear Discriminant Analysis (LDA). The models were then tested on an independent validation population (38 FMD patients and 28 healthy subjects).
Results
IMT (185 ± 46 vs 168 ± 37, p =) and AT (104 ± 34 vs 96 ± 35, p = 0.004) were significantly higher in FMD than in controls. IMT and AT triple signal were also more frequent in FMD than in control images (p < for both). The most accurate classification models were LDA (sensitivity = 0.67, specificity = 0.76, accuracy = 0.71, AUC = 0.71) and Logistic Regression (sensitivity = 0.71, specificity = 0.72, accuracy = 0.71, AUC = 0.71). The models showed and accuracy of about 70% when tested on the validation population.
Conclusions
Wall ultrastructure of radial arteries of FMD patients is extensively altered: IMT and AT are thickened and the first and/or second layer of the arterial wall is splitted, showing a triple signal feature. Radiomic descriptors combined with engineered parameters allow to distinguish between radial images from FMD patients and controls with a 70% accuracy.
Objective:
Systemic sclerosis (SSc) is a disorder characterized by a massive vascular involvement. Imaging biomarkers of vascular involvement in SSc may have potential clinical implications for prediction of the pathogenesis of vascular complications. This study is aimed at identifying possible patterns of vascular wall disarray and remodeling in radial arteries of SSc patients, by means of ultrahigh frequency ultrasound (UHFUS).
Design and method:
5 end-diastolic frames of the right radial arteries of 41 patients with SSc and 41 healthy controls were obtained by VevoMD (70 MHz probe, FUJIFILM, VisualSonics, Toronto, Canada). 74 radiomic features and 4 engineered parameters were extracted: inner and outer layer thickness, and presence of adjunctive acoustic interfaces (triple signal). A feature selection algorithm was applied to reduce the number of features. The selected features were used to train classification model, using Linear Support Vector Machine (SVM).
Results:
The SVM classification model showed good performance (sensitivity = 0.63, specificity = 0.88, accuracy = 0.75, AUC = 0.75) to discriminate SSc patients from controls using fifteen selected features. Inner layer (208±61 vs 179±47 μm, p = 0.04) and outer layer thickness (104±22 vs 120±36 μm, p = 0.03) were significantly higher in SSc than in controls, triple signal pattern more frequent in patients (p = 0.002).
Conclusions:
Wall ultrastructure of radial arteries of SSc patients is altered: inner and outer layer thickened, showing frequently a triple signal pattern. Radiomic approach allow to distinguish between radial images from SSc patients and controls with a 75% accuracy.
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