Lobe-Wise Lung Function Estimation from CT

About

Contact email:

luuk.boulogne@radboudumc.nl

Image Version:

b2891d70-646e-465b-b7c7-4f283262e770

Last updated:

Aug. 18, 2021, 2:33 p.m.

Interfaces

This algorithm implements all of the following input-output combinations:

Inputs Outputs

	Inputs	Outputs
1	Generic Medical Image Description - Kind Image Read from `/input/<uuid>.mha` or `/input/<uuid>.tif` Generic Medical Image	Generic Overlay Description An overlay of unknown type. Legacy, please use alternative interfaces. Kind Heat Map Write to `/output/images/<uuid>.mha` or `/output/images/<uuid>.tif` Generic Overlay Results JSON File Description A collection of results of unknown type. Legacy, if possible please use alternative interfaces. Kind Anything Write to `/output/results.json` Example { "key": "value", "None": null } Results JSON File

Model Facts

Summary

Algorithm for (regional) lung function prediction developed using the COPDGene dataset. Not for clinical use.

Mechanism

This algorithm was developed to work for CT scans of COPD patients. The algorithm consists of an I3D model trained with patient level lung function measurements to predict patient and lobe level lung function. The algorithm expects a CT scan and produces DLCO and spirometry (FEV1 and FVC both pre- and post-bronchodilator) estimates.

Validation and Performance

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Uses and Directions

This algorithm was developed for research purposes only.

Warnings

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Common Error Messages

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Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3