The still under-investigated role of cognitive deficits in PML diagnosis

Background: Despite cognitive deficits frequently represent the first clinical manifestations of Progressive Multifocal Leukoencephalopathy (PML) in Natalizumab-treated MS patients, the importance of cognitive deficits in PML diagnosis is still under-investigated. The aim of the current study is to investigate the cognitive deficits at PML diagnosis in a group of Italian patients with PML. Methods: Thirty-four PML patients were included in the study. The demographic and clinical data, the lesion load and localization, and the longitudinal clinical course was compared between patients with (n = 13) and without (n = 15) cognitive deficit upon PML suspicion (the remaining six patients were asymptomatic). Clinical presentation of cognitive symptoms was described in detail. Result: After symptoms detection, the time to diagnosis resulted to be shorter for patients presenting with cognitive than for patients with non cognitive onset (p = 0.03). Within patients with cognitive onset, six patients were presenting with language and/or reading difficulties (46.15%); five patients with memory difficulties (38.4%); three patients with apraxia (23.1%); two patients with disorientation (15.3%); two patients with neglect (15.3%); one patients with object agnosia (7.7%), one patient with perseveration (7.7%) and one patient with dementia (7.7%). Frontal lesions were less frequent (p = 0.03), whereas temporal lesions were slightly more frequent (p = 0.06) in patients with cognitive deficits. The longitudinal PML course seemed to be more severe in cognitive than in non cognitive patients (F = 2.73, p = 0.03), but differences disappeared (F = 1.24, p = 0.29) when balancing for the incidence of immune reconstitution syndrome and for other treatments for PML (steroids, plasma exchange (PLEX) and other therapies (Mefloquine, Mirtazapine, Maraviroc). Conclusion: Cognitive deficits at PML onset manifest with symptoms which are absolutely rare in MS. Their appearance in MS patients should strongly suggest PML. Clinicians should be sensitive to the importance of formal neuropsychological evaluation, with particular focus on executive function, which are not easily detected without a formal assessment

A Survey on Deep Learning in Medical Image Analysis

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area. Open challenges and directions for future research are discussed.Comment: Revised survey includes expanded discussion section and reworked introductory section on common deep architectures. Added missed papers from before Feb 1st 201

Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the image level without any lesion delineation). Our proposed post-hoc method automatically diagnosis the whole volume and, for positive cases, it localizes the malignant lesions that led to such diagnosis. Conversely, traditional approaches follow a pre-hoc approach that initially localises suspicious areas that are subsequently classified to establish the breast malignancy -- this approach is trained using strongly annotated data (i.e., it needs a delineation and classification of all lesions in an image). Another goal of this paper is to establish the advantages and disadvantages of both approaches when applied to breast screening from DCE-MRI. Relying on experiments on a breast DCE-MRI dataset that contains scans of 117 patients, our results show that the post-hoc method is more accurate for diagnosing the whole volume per patient, achieving an AUC of 0.91, while the pre-hoc method achieves an AUC of 0.81. However, the performance for localising the malignant lesions remains challenging for the post-hoc method due to the weakly labelled dataset employed during training.Comment: Submitted to Medical Image Analysi

Fokus auf der Untersuchung des Einflusses biometrischer Faktoren auf das Ergebnis der nTMS Messung sprachrelevanter Areale neurochirurgischer Patienten

Objective: Navigated transcranial magnetic stimulation (nTMS) is a non-invasive mapping tool to locate functional areas of the brain, gaining importance as a preoperative diagnostic device. This is a summary of three studies, Schwarzer et al., Rosenstock et al. and Zdunczyk et al., whose aim it is to increase the accuracy and usability of nTMS in different neurosurgical patient groups. They intend to describe neurophysiological data gained through nTMS as a supportive measure for surgical planning to increase patient safety and improve outcome. Methods: All patients and healthy subjects were examined via bihemispheric nTMS. Schwarzer et al. ascertained a baseline picture naming performance and used repetitive nTMS (rnTMS) to induce speech disruptions to identify individual language areas in patients with language eloquent lesions. Nine biometric factors were analyzed for correlation with elevated error occurrence. Rosenstock et al. concentrated on the primary motor cortex of patients with motor-eloquent glioma and performed correlation analyses to test the association of nTMS-related variables and postoperative motor outcome. Zdunczyk et al. examined patients with degenerative cervical myelopathy (DCM) and healthy volunteers to see differences in neurophysiological nTMS data due to disease severity. Results: Schwarzer et al. showed a significant increase in error occurrence with increased severity of cognitive impairment (p8mm (p=0.014). New postoperative deficits could be seen in patients with pathological excitability of the motor cortex (resting motor threshold ratio 110%, p=0.031). Patients with DCM had a reduced corticospinal excitability estimated by the recruitment curve (p=0.022), and patients with mild symptoms showed an increased activation on non- primary motor areas (p<0.005). Patients with severe symptoms showed a higher cortical inhibition (p<0.05) and a reduced motor area (p<0.05). Conclusion: Most patients are eligible for rnTMS language mapping. A new protocol for language mapping is proposed for secure identification of patients eligible for reliable rnTMS in Schwarzer et al. Rosenstock et al. introduce a new risk stratification model, based on objective functional-anatomical and neurophysiological measures, which enables physicians to counsel patients about the risk of functional deterioration or the potential for recovery and supports surgical planning. Zdunczyk et al. propose a new concept for functional compensation for DCM on the cortical and spinal level: the corticospinal reserve capacity. nTMS is a viable diagnostic tool to characterize this and its parameters serve as valuable prognostic factors.Fragestellung: Navigierte transkranielle Magnetstimulation (nTMS) ist eine nicht-invasive Untersuchungsmethode, um kortikale Funktionsareale zu identifizieren, welche zunehmend an Bedeutung als präoperatives diagnostisches Mittel gewinnt. Dies ist eine Zusammenfassung dreier Studien, Schwarzer et al., Rosenstock et al. und Zdunczyk et al. Die Studien haben als Ziel, die Benutzerfreundlichkeit und Genauigkeit von nTMS für unterschiedliche neurochirurgische Patientengruppen zu verbessern. Neurophysiologische Parameter wurden mittels nTMS erhoben, um die operative Planung zu unterstützen und das individuelle Patientenrisiko korrekt einzuschätzen und zu verbessern. Methodik: Alle Patienten und Probanden wurden bihemisphärisch mittels nTMS untersucht. Schwarzer et al. erhoben vorher die individuelle Fähigkeit zur Objektbenennung (baseline) und nutzten repetitive nTMS (rnTMS), um Sprachunterbrechungen hervorzurufen und somit Kortexareale bei Patienten mit sprachrelevanten Hirnläsionen zu identifizieren. Neun biometrische Patienteneigenschaften wurden in ein Verhältnis mit der Fehleranfälligkeit gesetzt. Rosenstock et al. untersuchten den primär motorischen Kortex bei Gliompatienten und analysierten den Zusammenhang von nTMS-ermittelten Parametern mit dem postoperativen Patientenzustand. Zdunczyk et al. betrachteten Patienten mit degenerativer zervikaler Myelopathie (DCM), sowie gesunde Probanden und ermittelten die unterschiedlichen nTMS-Parameter in Abhängigkeit von der Symptomschwere. Ergebnisse: Die meisten biometrischen Faktoren zeigten keinen statistischen Zusammenhang mit dem Stimulationsergebnis bei Schwarzer et al. Je schwerer der Aphasiegrad und die kognitiven Einschränkungen waren, desto mehr Sprachfehler wurden in der rnTMS Untersuchung gemacht (je p8mm zwischen Tumor und kortikospinalem Trakt keine neuen permanenten postoperativen Defizite auftraten (p=0.014). Neue postoperative Defizite traten bei Patienten mit präoperativ pathologischer Kortexerregbarkeit (Ruhemotorschwellenverhältnis RMT 110%, p=0.031) auf. DCM Patienten wiesen eine reduzierte kortikospinale Erregbarkeit, gekennzeichnet durch ein Abflachen der recruitment curve, auf (p=0.022). Ein vergrößertes motorisch relevantes Kortexareal mit Aktivierung sekundärer Motorareale zeigte sich bei Patienten mit milder Symptomatik (p<0.005), während bei schwer betroffenen Patienten eine erhöhte kortikale Hemmung (CSP, p<0.05) und reduzierte motorische Kortexfläche auffiel (p<0.05). Schlussfolgerung: Schwarzer et al. stellen ein neues Prüfungsprotokoll für die Eignung von Patienten für ein reliables rnTMS Ergebnis vor, wobei die statistische Analyse ergab, dass die meisten Patienten für eine reliable rnTMS Sprachuntersuchung geeignet sind. Rosenstock et al. präsentieren ein neues Risikostratifikationsmodell für Patienten mit motorisch relevanten Gliomen, wodurch der Operateur anhand von funktionell-anatomischen und neurophysiologischen Parametern das individuelle Patientenrisiko für den postoperativen Verlauf einschätzen kann. Zdunczyk et al. beschreiben einen möglichen funktionellen Kompensationsmechanismus bei DCM Patienten auf kortikaler und spinaler Ebene: die kortikospinale Reservekapazität. Die durch nTMS ermittelten Parameter lassen damit objektivierbare prognostische Aussagen zu

Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks

Lesions characterized by computed tomography (CT) scans, are arguably often elliptical objects. However, current lesion detection systems are predominantly adopted from the popular Region Proposal Networks (RPNs) that only propose bounding boxes without fully leveraging the elliptical geometry of lesions. In this paper, we present Gaussian Proposal Networks (GPNs), a novel extension to RPNs, to detect lesion bounding ellipses. Instead of directly regressing the rotation angle of the ellipse as the common practice, GPN represents bounding ellipses as 2D Gaussian distributions on the image plain and minimizes the Kullback-Leibler (KL) divergence between the proposed Gaussian and the ground truth Gaussian for object localization. We show the KL divergence loss approximately incarnates the regression loss in the RPN framework when the rotation angle is 0. Experiments on the DeepLesion dataset show that GPN significantly outperforms RPN for lesion bounding ellipse detection thanks to lower localization error. GPN is open sourced at https://github.com/baidu-research/GP

Damage to fronto-parietal networks impairs motor imagery ability after stroke : a voxel-based lesion symptom mapping study

Background: mental practice with motor imagery has been shown to promote motor skill acquisition in healthy subjects and patients. Although lesions of the common motor imagery and motor execution neural network are expected to impair motor imagery ability, functional equivalence appears to be at least partially preserved in stroke patients.Aim: to identify brain regions that are mandatory for preserved motor imagery ability after stroke.Method: thirty-seven patients with hemiplegia after a first time stroke participated. Motor imagery ability was measured using a Motor Imagery questionnaire and temporal congruence test. A voxelwise lesion symptom mapping approach was used to identify neural correlates of motor imagery in this cohort within the first year post-stroke.Results: poor motor imagery vividness was associated with lesions in the left putamen, left ventral premotor cortex and long association fibres linking parieto-occipital regions with the dorsolateral premotor and prefrontal areas. Poor temporal congruence was otherwise linked to lesions in the more rostrally located white matter of the superior corona radiata. Conclusion: This voxel-based lesion symptom mapping study confirms the association between white matter tract lesions and impaired motor imagery ability, thus emphasizing the importance of an intact fronto-parietal network for motor imagery. Our results further highlight the crucial role of the basal ganglia and premotor cortex when performing motor imagery tasks