Bilateral HOD can serve as a reliable radiological indicator in establishing the diagnosis of POPCMS particularly in equivocal cases. The strong association of signal change due to HOD in the left ION suggests that injury to the right proximal efferent cerebellar pathway plays an important role in the causation of POPCMS.

Abstract. Up to 25% of children who undergo brain tumor resection surgery in the posterior fossa develop posterior fossa syndrome (PFS). This syndrome is characterized by mutism and disturbance in speech. Our hypothesis is that there is a correlation between PFS and the occurrence of hypertrophic olivary degeneration (HOD) in structures within the posterior fossa, known as the inferior olivary nuclei (ION). HOD is exhibited as an increase in size and intensity of the ION on an MR image. Longitudinal MRI datasets of 28 patients were acquired consisting of pre-, intra-, and postoperative scans. A semiautomated segmentation process was used to segment the ION on each MR image. A full set of imaging features describing the first-and second-order statistics and size of the ION were extracted for each image. Feature selection techniques were used to identify the most relevant features among the MRI features, demographics, and data based on neuroradiological assessment. A support vector machine was used to analyze the discriminative features selected by a generative k-nearest neighbor algorithm. The results indicate the presence of hyperintensity in the left ION as the most diagnostically relevant feature, providing a statistically significant improvement in the classification of patients (p ¼ 0.01) when using this feature alone. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Background: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to diagnose. We propose a machine learning approach to characterize morphological changes in dogs that may or may not be apparent to human observers. This datadriven approach can remove potential bias (or blindness) that may be produced by a hypothesis-driven expert observer approach.Hypothesis/Objectives: To understand neuromorphological change and to identify image-based biomarkers in dogs with CM-P and symptomatic SM (SM-S) using a novel machine learning approach, with the aim of increasing the understanding of these disorders.Animals: Thirty-two client-owned Cavalier King Charles Spaniels (CKCSs; 11 controls, 10 CM-P, 11 SM-S).Methods: Retrospective study using T2-weighted midsagittal Digital Imaging and Communications in Medicine (DICOM) anonymized images, which then were mapped to images of an average clinically normal CKCS reference using Demons image registration. Key deformation features were automatically selected from the resulting deformation maps. A kernelized support vector machine was used for classifying characteristic localized changes in morphology.Results: Candidate biomarkers were identified with receiver operating characteristic curves with area under the curve (AUC) of 0.78 (sensitivity 82%; specificity 69%) for the CM-P biomarkers collectively and an AUC of 0.82 (sensitivity, 93%; specificity, 67%) for the SM-S biomarkers, collectively.Abbreviations: AUC, area under the curve; CKCS, Cavalier King Charles Spaniel; CM, Chiari-like malformation; CM-N, control dogs: no SM no CM pain; 4 years of age and older; CM-P, pain associated with Chiari-like malformation; CSF, cerebrospinal fluid; DICOM, Digital Imaging and Communications in Medicine; FPR, false-positive rate (also known as 1 − specificity); ICC, intraclass correlation coefficient; MRI, magnetic resonance imaging; PCA, principal component analysis; ROC, receiver operating characteristic; SFFS, sequential floating forward selection; SM, syringomyelia; SM-S, syringomyelia and associated clinical signs; SVM, support vector machine; TPR, true-positive rate (also known as sensitivity).

Background: Recent studies including an innovative machine learning technique indicated Chiari-like malformation (CM) is influenced by brachycephalic features. Objectives: Morphometric analysis of facial anatomy and dysmorphia in CMassociated pain (CM-P) and syringomyelia (SM) in the Cavalier King Charles Spaniel (CKCS). Animals: Sixty-six client-owned CKCS. Methods: Retrospective study of anonymized T2W sagittal magnetic resonance imaging of 3 clinical groups: (1) 11 without central canal dilation (ccd) or SM (CM-N), (2) 15 with CM-P with no SM or <2 mm ccd (CM-P), and (3) 40 with syrinx width ≥4 mm (SM-S). Morphometric analysis assessed rostral skull flattening and position of the hard and soft palate relative to the cranial base in each clinical group and compared CKCS with and without SM-S.Results: Sixteen of 28 measured variables were associated to SM-S compared to CM-N and CM-P. Of these 6 were common to both groups. Predictive variables determined by discriminant analysis were (1) the ratio of cranial height with cranial length (P < .001 between SM-S and CM-N) and (2) the distance between the cerebrum and the frontal bone (P < .001 between SM-S and CM-P). CM-P had the lowest mean height of the maxillary area. Conclusions and ClinicalImportance: CKCS with CM-P and SM-S have cranial brachycephaly with osseous insufficiency in the skull with rostral flattening and increased proximity of the hard and soft palate to the cranial base. Changes are greatest with CM-P. These findings have relevance for understanding disease pathogenesis and for selection of head conformation for breeding purposes. dogs without central canal dilation or syringomyelia with no clinical or behavioural signs of pain; CM-P, dogs with clinical and behavioral signs of pain with no syringomyelia or with a central canal dilation less than 2 mm wide; CSF, cerebrospinal fluid; DA, discriminant function analysis; DICOM, Digital Imaging and Communications in Medicine; FS, feature selection; ICC, intraclass correlation coefficient; ML, machine learning; MRI, magnetic resonance imaging; SM, syringomyelia; SM-S, dogs with syrinx width ≥4 mm and with SM specific signs of phantom scratching, scoliosis, paresis or proprioceptive deficits.

Abstract:Introduction: