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FältnamnIndikatorerMetadata
00006767naa a2200517 4500
001oai:DiVA.org:oru-107501
003SwePub
008230810s2024 | |||||||||||000 ||eng|
009oai:prod.swepub.kib.ki.se:237552259
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-1075012 URI
0247 a https://doi.org/10.1007/s00330-023-09985-32 DOI
0247 a http://kipublications.ki.se/Default.aspx?queryparsed=id:2375522592 URI
040 a (SwePub)orud (SwePub)ki
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Lidén, Mats,d 1976-u Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Department of Radiology and Medical Physics4 aut0 (Swepub:oru)msld
2451 0a Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction
264 1b Springer,c 2024
338 a print2 rdacarrier
500 a Open access funding provided by Örebro University. This study has received funding from Nyckelfonden, Örebro, Sweden (OLL-881491), Analytic Imaging Diagnostics Arena (AIDA), Linköping, Sweden (2104_Lidén) and Region Örebro län, Sweden (OLL-959996).The main funding body of The Swedish CArdioPulmonary bio-Image Study (SCAPIS) is the Swedish Heart and Lung Foundation. SCAPIS is also funded by the Knut and Alice Wallenberg Foundation, the Swedish Research Council and VINNOVA (Sweden’s Innovation Agency). In addition, the SCAPIS pilot received support from the Sahlgrenska Academy at University of Gothenburg and Region Västra Götaland.
520 a OBJECTIVES: Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method.MATERIALS AND METHODS: Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis.RESULTS: SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r =  - 0.69 vs. r =  - 0.49/r =  - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r =  - 0.77 vs. r =  - 0.69/r =  - 0.65, p = 0.03/p = 0.002), and in the random sample (r =  - 0.39 vs. r =  - 0.26/r =  - 0.25, p = 0.001/p = 0.007).CONCLUSION: The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores.CLINICAL RELEVANCE STATEMENT: The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores.KEY POINTS: • A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Radiologi och bildbehandling0 (SwePub)302082 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Radiology, Nuclear Medicine and Medical Imaging0 (SwePub)302082 hsv//eng
653 a Deep learning
653 a Lung
653 a Pulmonary disease
653 a chronic obstructive
653 a Pulmonary emphysema
653 a Tomography
653 a X-ray computed
7001 a Spahr, Antoineu Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology School of Technology and Health, Stockholm, Sweden4 aut
7001 a Hjelmgren, Olau Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Clinical Physiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden4 aut
7001 a Bendazzoli, Simoneu Karolinska Institutet4 aut
7001 a Sundh, Josefin,d 1972-u Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Department of Respiratory Medicine4 aut0 (Swepub:oru)jnsh
7001 a Sköld, Magnusu Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden; Department of Respiratory Medicine and Allergy, Karolinska University Hospital, Stockholm, Sweden4 aut
7001 a Bergström, Göranu Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Clinical Physiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden4 aut
7001 a Wang, Chunliangu Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology School of Technology and Health, Stockholm, Sweden4 aut
7001 a Thunberg, Per,d 1968-u Örebro universitet,Institutionen för medicinska vetenskaper,Department of Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden4 aut0 (Swepub:oru)prtg
7102 a Örebro universitetb Institutionen för medicinska vetenskaper4 org
7730 t European Radiologyd : Springerg 34:1, s. 39-49q 34:1<39-49x 0938-7994x 1432-1084
8564 u https://doi.org/10.1007/s00330-023-09985-3y Fulltext
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-107501
8564 8u https://doi.org/10.1007/s00330-023-09985-3
8564 8u http://kipublications.ki.se/Default.aspx?queryparsed=id:237552259

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