Anatomical Variation and Clinical Diagnosis

In the anatomical sciences, it has long been recognized that the human body displays a range of morphological patterns and arrangements, often termed “anatomical variation”. Variations are relatively common throughout the body and may cause or contribute to significant medical conditions. An understanding of normal anatomical variation is vital for performing a broad range of surgical and other medical procedures and treatment modalities. However, despite their importance to effective diagnosis and treatment, such variations are often overlooked in medical school curricula and clinical practice. Recent advances in imaging techniques and a renewed interest in variation in dissection-based gross anatomy laboratories have facilitated the identification of many such variants. The aim of this Special Issue of Diagnostics is to highlight previously under-recognized anatomical variations and to discuss them in a clinical context. In particular, this Special Issue focuses on variants that have specific implications for diagnosis and treatment and explores their potential consequences. The scope of this Special Issue includes studies on gross anatomy, radiology, surgical anatomy, histology, and neuroanatomy

Inferring brain deformation during open neurosurgery using CBCT angiography

© 2016 IEEE. During neurosurgery the brain can deform, which is known as brain shift. The deformation can be as large as 20 mm and limits the accuracy of image-guided surgery. In this work we use pre- and intra-operative CBCT angiography to infer this deformation. We first segment cortex and vessels in both images and then perform surface registration between the pre- and intra-operative segmentations. The resulting deformation field is assumed to correspond to the brain deformation and can be used to update other pre-operative images. Since the intra-operative image quality is deteriorated by streak artifacts originating from the metallic stereotactic frame, our approach explores robust segmentation and registration methods that reduce the influence of these artifacts. Our method is tested on a clinical data set of 8 patients who underwent neurosurgery. We also compare with a recently published method and rigid registration as a baseline method, showing the improved accuracy of our approach.Verheyen N., Robben D., Ruijters D., Mendes Pereira V., Brina O., Maes F., Suetens P., ''Inferring brain deformation during open neurosurgery using CBCT angiography'', Proceedings 13th IEEE international symposium on biomedical imaging - ISBI 2016, pp. 111-114, April 13-16, 2016, Prague, Czech Republic.status: publishe