SWITCH2023: Stroke Workshop on Imaging and Treatment CHallenges

Recent Updates

  • Aug 2023: We are teaming up with the BrainLes Workshop to create a joint LNCS proceedings volume this year.
  • July 2023: Notification of paper decision sent. Camera-ready deadline: July 31, 2023
  • July 2023: Notification of paper decision postponed till July 18, 2023.
  • Jun 2023: Deadline extended to July 6, 2023 (Thursday), 23:59 pm (PST)! Submit your paper here
  • Jun 2023: The workshop will be hybrid, with onsite attendance recommended!
  • May 2023: We are open for submissions!
  • Mar 2023: Website Up!
  • Mar 2023: SWITCH 2018 website archived.

Overview

SWITCH is a hybrid half-day workshop focused on imaging related to stroke diagnosis and treatment. The main goals of the workshop are 1) to introduce the clinical background of challenges/opportunities related to imaging for stroke that are relevant for researchers working in the MICCAI field, and 2) to stimulate discussion and ideas exchange. To this end, there will be keynotes by clinical experts in stroke imaging and treatment, as well as presentations by researchers of on-going work.

Call for papers

SWITCH is soliciting full paper manuscripts to be presented at the workshop. Accepted manuscripts will get a poster or oral presentation during the workshop at MICCAI and will be published in Springer Lecture Notes in Computer Science (LNCS) together with the proceedings of the MICCAI workshop. The following themes are encouraged, but not exhaustive:

  • Novel image processing approaches for lesion detection and quantification
  • Imaging based approaches to treatment decision making
  • Image guidance during interventions
  • Imaging based quantification of treatment

We encourage work involving, among others, the following imaging modalities:

  • CT-variants (CT, CTA, CTP, multi-phase CTA)
  • MR (DWI)
  • X-ray

Full paper manuscripts should follow the LNCS guidelines for formatting, and have a length of at most eight pages. All submitted manuscripts will be reviewed on applicability to the workshop topic, scientific quality and clinical relevance. Note that we value novel methodology as well as thorough evaluation. Accepted manuscripts will get a poster or oral presentation during the workshop at MICCAI.

Supplementary material is allowed, but will not be included in the proceedings. All papers will go through peer review with at least two blinded reviewers per paper from the organising committee.


Submit your paper here

Important Dates

  • Mar 22, 2023 Website up
  • May 24, 2023 Open for submissions
  • June 25, 2023 Paper Submission Deadline
  • July 6, 2023, 23:59 (PST) Extended Paper Submission Deadline
  • July 16, 2023 Notification of Paper Decision
  • July 18, 2023 Notification of Paper Decision
  • July 31, 2023 Camera-ready Deadline
  • July 31, 2023 Full Program Available
  • Oct 12, 2023 Workshop!

Program

The following is a tentative program:

Location: Vancouver Convention Center East Building Level 1

Room: Meeting Room 15

  • 08:00 - 08:10 Introduction
  • 08:10 - 08:55 Keynote: Prof. Menon Bijoy,
    Professor of Neurology, Radiology and Community Health Sciences, Cumming School of Medicine, University of Calgary.
    Why use computer aided diagnosis in patients with acute ischemic stroke? ·
  • 08:55 - 09:20 Presentations by authors of accepted papers
  • The Detection and Segmentation of Blush in the Lenticulostriate Territory,
    Sjir Schielen (TU Eindhoven)

    An Automatic Cascaded Model for Hemorrhagic Stroke segmentation and Hemorrhagic Volume Estimation,
    Weijin Xu (Beijing University of Posts and Telecommunications)
  • 09:20 - 10:05 Keynote: Dr. Pascal Mosimann ,
    Associate Professor, Neuroradiology, University of Toronto
    Remote neurovascular interventions: myth or reality?
  • 10:05 - 10:30 Coffee Break

  • 10:30 - 11:10 Presentations by authors of accepted papers
  • Functional outcome prediction in acute ischemic stroke,
    Ewout Heylen (KU Leuven)

    Multimodal deep learning for functional outcome prediction in endovascular therapy,
    Frank G te Nijenhuis (Erasmus MC)

    From brain tissue infarction at 24 hours to patient functional outcome at 90 days using deep learning,
    Marie Ulens (KU Leuven)
  • 11:10 - 11:55 Keynote: Dr. Jonas Richiardi,
    PI and senior lecturer in Radiology, Lausanne University Hospital and University of Lausanne.
    MRI in stroke: from acquisition to postprocessing using classical and modern techniques ·
  • 11:55 - 12:20 Presentations by authors of accepted papers
  • Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study,
    Chayanin Tangwiriyasakul (King's College London)

    Deep learning for ischemic penumbra segmentation from MR perfusion maps: robustness to the deconvolution algorithm,
    Theo Leuliet (Inselspital, Bern University Hospital)
  • 12:20 - 12:30 Concluding Remarks

Details: About SWITCH

Stroke

Stroke, as a result of insufficient blood supply to the brain, is the second most frequent cause of death and disability world-wide. The causes of stroke are either a bleeding (hemorrhage) in the brain, or an occlusion of a vessel feeding (part of) the brain. In the latter case, the occlusion may originate from a brain vessel itself, or be a thrombus that originates from a more proximal location (heart, carotid artery).

Imaging

In acute stroke management, immediate and accurate diagnosis is key to fast treatment. Dependent on the local settings, most frequently patients undergo non-contrast CT imaging, as well as a subsequent examination with iodine contrast application: single phase CTA, multiphase CTA, and optionally also CT Perfusion. Selected stroke centers also prioritize MR imaging with DWI and MRA. During endovascular thrombectomy (EVT), DSA imaging is typically used for guidance and perioperative assistance. From these images, information such as lesion and lesion size, composition of the thrombus, collateral flow and perfusion of brain tissue may be obtained. Although a couple of predictive tools (e.g., MR PREDICTS, Venema et al., BMJ, 2017) and quantitative imaging biomarkers (e.g., Broocks et al, Stroke, 2022) have been developed, few have been clinically validated. In current practice, subjective and at best semi-quantitative measures (e.g., ASPECT score for ischemic stroke) based on the CT images are typically used by clinicians to select patients and to decide on treatment strategy. While deep learning-based image analysis algorithms have been increasingly proposed in the last few years for diagnosis (Bertels et al, 2022), treatment assessment (e.g., autoTICI, Su et al, 2021), and outcome prediction (Hilbert et al., 2019), new opportunities and challenges appear along the way.

Goals

Therefore, the main purposes of this Workshop are

  1. To introduce the challenges/opportunities related to imaging for stroke (assessment and diagnosis, therapy decision making, therapy guidance, therapy assessment, outcome prediction) that are relevant for researchers working in the “MICCAI” field. This will be done via clinical keynote speakers.
  2. To get informed on current work in this field. This will be done via presentations of the submitted contributions.
  3. To bring together researchers in this field, and stimulate further ideas exchange: via the discussions and interaction during the whole workshop.

Thus, we intend to compose a program with presentations by researchers of on-going work, based on submitted manuscripts as well as key-note presentations by clinical experts in stroke management, modern imaging for stroke.

Photos 2023




Photos 2018


Photos 2017


SWITCH2023 Organizing Committee

Ruisheng Su

Biomedical Imaging Group Rotterdam, Erasmus MC

Theo van Walsum

Biomedical Imaging Group Rotterdam, Erasmus MC

Roland Wiest

Support Center of Advanced Neuroimaging, Inselspital Bern

Jeroen Bertels

Medical Imaging Research Center, KU Leuven

Anke Wouters

Medical Imaging Research Center, KU Leuven

Danny Ruijters

Electrical Engineering, TU Eindhoven

Adrian Dalca

CSAIL, MIT and
MGH, Harvard Medical School

Contact

Please contact us for further questions and comments via email at miccai.switch@gmail.com

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