Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Carole H. Sudre; Kimberlin Van Wijnen; Florian Dubost; Hieab Adams; David Atkinson; Frederik Barkhof; Mahlet A. Birhanu; Esther E. Bron; Robin Camarasa; Nish Chaturvedi; Yuan Chen; Zihao Chen; Shuai Chen; Qi Dou; Tavia Evans; Ivan Ezhov; Haojun Gao; Marta Girones Sanguesa; Juan Domingo Gispert; Beatriz Gomez Anson; Alun D. Hughes; M. Arfan Ikram; Silvia Ingala; H. Rolf Jaeger; Florian Kofler; Hugo J. Kuijf; Denis Kutnar; Minho Lee; Bo Li; Luigi Lorenzini; Bjoern Menze; Jose Luis Molinuevo; Yiwei Pan; Elodie Puybareau; Rafael Rehwald; Ruisheng Su; Pengcheng Shi; Lorna Smith; Therese Tillin; Guillaume Tochon; Helene Urien; Bas H. M. van der Velden; Isabelle F. van der Velpen; Benedikt Wiestler; Frank J. Wolters; Pinar Yilmaz; Marius de Groot; Meike W. Vernooij; Marleen de Bruijne

doi:10.48550/ARXIV.2208.07167

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Carole H. Sudre
, Kimberlin Van Wijnen
, Florian Dubost
, Hieab Adams
, David Atkinson
, Frederik Barkhof
, Mahlet A. Birhanu
, Esther E. Bron
, Robin Camarasa
, Nish Chaturvedi
, Yuan Chen
, Zihao Chen
, Shuai Chen
, Qi Dou
, Tavia Evans
, Ivan Ezhov
, Haojun Gao
, Marta Girones Sanguesa
, Juan Domingo Gispert
, Beatriz Gomez Anson

Alun D. Hughes, M. Arfan Ikram, Silvia Ingala, H. Rolf Jaeger, Florian Kofler, Hugo J. Kuijf, Denis Kutnar, Minho Lee, Bo Li, Luigi Lorenzini, Bjoern Menze, Jose Luis Molinuevo, Yiwei Pan, Elodie Puybareau, Rafael Rehwald, Ruisheng Su, Pengcheng Shi, Lorna Smith, Therese Tillin, Guillaume Tochon, Helene Urien, Bas H. M. van der Velden, Isabelle F. van der Velpen, Benedikt Wiestler, Frank J. Wolters, Pinar Yilmaz, Marius de Groot, Meike W. Vernooij, Marleen de Bruijne

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Imaging markers of cerebral small vessel disease provide valuable information on brain health,
but their manual assessment is time-consuming and hampered by substantial intra- and interrater
variability. Automated rating may benet biomedical research, as well as clinical assessment, but
diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular
Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event
at the international conference on Medical Image Computing and Computer Aided Intervention
(MICCAI) 2021. This challenge aimed to promote the development of methods for automated
detection and segmentation of small and sparse imaging markers of cerebral small vessel disease,
namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes
of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams
participated in the challenge proposing solutions for one or more tasks (4 for Task 1 - EPVS, 9 for
Task 2 - Microbleeds and 6 for Task 3 - Lacunes). Multi-cohort data was used in both training and
evaluation. Results showed a large variability in performance both across teams and across tasks,
with promising results notably for Task 1 - EPVS and Task 2 - Microbleeds and not practically
useful results yet for Task 3 - Lacunes. It also highlighted the performance inconsistency across
cases that may deter use at an individual level, while still proving useful at a population level.
Keywords: CSVD, brain, MRI, microbleeds, enlarged perivascular spaces, lacunes, automated,
segmentation, detection, challenge

Original language	English
Journal	Advances in Computer Vision and Pattern Recognition
DOIs	https://doi.org/10.48550/ARXIV.2208.07167
Publication status	Published - 15 Aug 2022

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10.48550/ARXIV.2208.07167Licence: CC BY-SA

Where is VALDOSubmitted manuscript, 2.23 MBLicence: CC BY-SA

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Sudre, C. H., Van Wijnen, K., Dubost, F., Adams, H., Atkinson, D., Barkhof, F., Birhanu, M. A., Bron, E. E., Camarasa, R., Chaturvedi, N., Chen, Y., Chen, Z., Chen, S., Dou, Q., Evans, T., Ezhov, I., Gao, H., Sanguesa, M. G., Gispert, J. D., ... de Bruijne, M. (2022). Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021. Advances in Computer Vision and Pattern Recognition. https://doi.org/10.48550/ARXIV.2208.07167

@article{b9abb335e50c44d69d3cf309c4189cb2,

title = "Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021",

abstract = "Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benet biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1 - EPVS, 9 for Task 2 - Microbleeds and 6 for Task 3 - Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1 - EPVS and Task 2 - Microbleeds and not practically useful results yet for Task 3 - Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level. Keywords: CSVD, brain, MRI, microbleeds, enlarged perivascular spaces, lacunes, automated, segmentation, detection, challenge",

author = "Sudre, \{Carole H.\} and \{Van Wijnen\}, Kimberlin and Florian Dubost and Hieab Adams and David Atkinson and Frederik Barkhof and Birhanu, \{Mahlet A.\} and Bron, \{Esther E.\} and Robin Camarasa and Nish Chaturvedi and Yuan Chen and Zihao Chen and Shuai Chen and Qi Dou and Tavia Evans and Ivan Ezhov and Haojun Gao and Sanguesa, \{Marta Girones\} and Gispert, \{Juan Domingo\} and Anson, \{Beatriz Gomez\} and Hughes, \{Alun D.\} and Ikram, \{M. Arfan\} and Silvia Ingala and Jaeger, \{H. Rolf\} and Florian Kofler and Kuijf, \{Hugo J.\} and Denis Kutnar and Minho Lee and Bo Li and Luigi Lorenzini and Bjoern Menze and Molinuevo, \{Jose Luis\} and Yiwei Pan and Elodie Puybareau and Rafael Rehwald and Ruisheng Su and Pengcheng Shi and Lorna Smith and Therese Tillin and Guillaume Tochon and Helene Urien and \{van der Velden\}, \{Bas H. M.\} and \{van der Velpen\}, \{Isabelle F.\} and Benedikt Wiestler and Wolters, \{Frank J.\} and Pinar Yilmaz and \{de Groot\}, Marius and Vernooij, \{Meike W.\} and \{de Bruijne\}, Marleen",

year = "2022",

month = aug,

day = "15",

doi = "10.48550/ARXIV.2208.07167",

language = "English",

journal = "Advances in Computer Vision and Pattern Recognition",

issn = "2191-6586",

publisher = "Springer Science+Business Media",

}

Sudre, CH, Van Wijnen, K, Dubost, F, Adams, H, Atkinson, D, Barkhof, F, Birhanu, MA , Bron, EE, Camarasa, R, Chaturvedi, N, Chen, Y, Chen, Z, Chen, S, Dou, Q, Evans, T, Ezhov, I, Gao, H, Sanguesa, MG, Gispert, JD, Anson, BG, Hughes, AD, Ikram, MA, Ingala, S, Jaeger, HR, Kofler, F, Kuijf, HJ, Kutnar, D, Lee, M, Li, B, Lorenzini, L, Menze, B, Molinuevo, JL, Pan, Y, Puybareau, E, Rehwald, R, Su, R, Shi, P, Smith, L, Tillin, T, Tochon, G, Urien, H, van der Velden, BHM, van der Velpen, IF, Wiestler, B, Wolters, FJ, Yilmaz, P, de Groot, M, Vernooij, MW & de Bruijne, M 2022, 'Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021', Advances in Computer Vision and Pattern Recognition. https://doi.org/10.48550/ARXIV.2208.07167

TY - JOUR

T1 - Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

AU - Sudre, Carole H.

AU - Van Wijnen, Kimberlin

AU - Dubost, Florian

AU - Adams, Hieab

AU - Atkinson, David

AU - Barkhof, Frederik

AU - Birhanu, Mahlet A.

AU - Bron, Esther E.

AU - Camarasa, Robin

AU - Chaturvedi, Nish

AU - Chen, Yuan

AU - Chen, Zihao

AU - Chen, Shuai

AU - Dou, Qi

AU - Evans, Tavia

AU - Ezhov, Ivan

AU - Gao, Haojun

AU - Sanguesa, Marta Girones

AU - Gispert, Juan Domingo

AU - Anson, Beatriz Gomez

AU - Hughes, Alun D.

AU - Ikram, M. Arfan

AU - Ingala, Silvia

AU - Jaeger, H. Rolf

AU - Kofler, Florian

AU - Kuijf, Hugo J.

AU - Kutnar, Denis

AU - Lee, Minho

AU - Li, Bo

AU - Lorenzini, Luigi

AU - Menze, Bjoern

AU - Molinuevo, Jose Luis

AU - Pan, Yiwei

AU - Puybareau, Elodie

AU - Rehwald, Rafael

AU - Su, Ruisheng

AU - Shi, Pengcheng

AU - Smith, Lorna

AU - Tillin, Therese

AU - Tochon, Guillaume

AU - Urien, Helene

AU - van der Velden, Bas H. M.

AU - van der Velpen, Isabelle F.

AU - Wiestler, Benedikt

AU - Wolters, Frank J.

AU - Yilmaz, Pinar

AU - de Groot, Marius

AU - Vernooij, Meike W.

AU - de Bruijne, Marleen

PY - 2022/8/15

Y1 - 2022/8/15

N2 - Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benet biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1 - EPVS, 9 for Task 2 - Microbleeds and 6 for Task 3 - Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1 - EPVS and Task 2 - Microbleeds and not practically useful results yet for Task 3 - Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level. Keywords: CSVD, brain, MRI, microbleeds, enlarged perivascular spaces, lacunes, automated, segmentation, detection, challenge

AB - Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benet biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1 - EPVS, 9 for Task 2 - Microbleeds and 6 for Task 3 - Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1 - EPVS and Task 2 - Microbleeds and not practically useful results yet for Task 3 - Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level. Keywords: CSVD, brain, MRI, microbleeds, enlarged perivascular spaces, lacunes, automated, segmentation, detection, challenge

U2 - 10.48550/ARXIV.2208.07167

DO - 10.48550/ARXIV.2208.07167

M3 - Article

SN - 2191-6586

JO - Advances in Computer Vision and Pattern Recognition

JF - Advances in Computer Vision and Pattern Recognition

ER -

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

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