Ignite Creation Date:
2025-12-24 @ 2:12 PM
Ignite Modification Date:
2025-12-28 @ 3:59 AM
Study NCT ID:
NCT05048095
Status:
COMPLETED
Last Update Posted:
2022-04-20
First Post:
2021-09-08
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Artificial Intelligence in Breast Cancer Screening in Region Östergötland Linkoping
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001943', 'term': 'Breast Neoplasms'}], 'ancestors': [{'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D001941', 'term': 'Breast Diseases'}, {'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 15500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2021-10-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-04', 'completionDateStruct': {'date': '2022-02-15', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-04-19', 'studyFirstSubmitDate': '2021-09-08', 'studyFirstSubmitQcDate': '2021-09-08', 'lastUpdatePostDateStruct': {'date': '2022-04-20', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-09-17', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-02-15', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Cancer Detection rate', 'timeFrame': 'After 4 months of inclusion', 'description': 'Proportion of women diagnosed with breast cancer among those recalled after consensus'}, {'measure': 'Recall or referral rate', 'timeFrame': 'After 4 months of inclusion', 'description': 'Proportion of women who are referred for further diagnostic workup after consensus'}, {'measure': 'Positive predictive value of referrals', 'timeFrame': 'After 4 months of inclusion', 'description': 'Proportion of women diagnosed with breast cancer among those referred'}], 'secondaryOutcomes': [{'measure': 'Positive predictive value of Transpara® scores', 'timeFrame': 'After 4 months of inclusion', 'description': 'Proportion of breast cancers diagnosed among women with a given AI score'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Artificial intelligence'], 'conditions': ['Breast Cancer']}, 'referencesModule': {'references': [{'pmid': '30834436', 'type': 'BACKGROUND', 'citation': 'Rodriguez-Ruiz A, Lang K, Gubern-Merida A, Broeders M, Gennaro G, Clauser P, Helbich TH, Chevalier M, Tan T, Mertelmeier T, Wallis MG, Andersson I, Zackrisson S, Mann RM, Sechopoulos I. Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists. J Natl Cancer Inst. 2019 Sep 1;111(9):916-922. doi: 10.1093/jnci/djy222.'}, {'pmid': '30457482', 'type': 'BACKGROUND', 'citation': 'Rodriguez-Ruiz A, Krupinski E, Mordang JJ, Schilling K, Heywang-Kobrunner SH, Sechopoulos I, Mann RM. Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System. Radiology. 2019 Feb;290(2):305-314. doi: 10.1148/radiol.2018181371. Epub 2018 Nov 20.'}, {'pmid': '33948701', 'type': 'BACKGROUND', 'citation': 'van Winkel SL, Rodriguez-Ruiz A, Appelman L, Gubern-Merida A, Karssemeijer N, Teuwen J, Wanders AJT, Sechopoulos I, Mann RM. Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study. Eur Radiol. 2021 Nov;31(11):8682-8691. doi: 10.1007/s00330-021-07992-w. Epub 2021 May 4.'}, {'pmid': '34227882', 'type': 'BACKGROUND', 'citation': 'Pinto MC, Rodriguez-Ruiz A, Pedersen K, Hofvind S, Wicklein J, Kappler S, Mann RM, Sechopoulos I. Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis. Radiology. 2021 Sep;300(3):529-536. doi: 10.1148/radiol.2021204432. Epub 2021 Jul 6.'}, {'pmid': '33944627', 'type': 'BACKGROUND', 'citation': 'Raya-Povedano JL, Romero-Martin S, Elias-Cabot E, Gubern-Merida A, Rodriguez-Ruiz A, Alvarez-Benito M. AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation. Radiology. 2021 Jul;300(1):57-65. doi: 10.1148/radiol.2021203555. Epub 2021 May 4.'}, {'pmid': '32876835', 'type': 'BACKGROUND', 'citation': 'Lang K, Dustler M, Dahlblom V, Akesson A, Andersson I, Zackrisson S. Identifying normal mammograms in a large screening population using artificial intelligence. Eur Radiol. 2021 Mar;31(3):1687-1692. doi: 10.1007/s00330-020-07165-1. Epub 2020 Sep 2.'}, {'pmid': '30993432', 'type': 'BACKGROUND', 'citation': 'Rodriguez-Ruiz A, Lang K, Gubern-Merida A, Teuwen J, Broeders M, Gennaro G, Clauser P, Helbich TH, Chevalier M, Mertelmeier T, Wallis MG, Andersson I, Zackrisson S, Sechopoulos I, Mann RM. Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study. Eur Radiol. 2019 Sep;29(9):4825-4832. doi: 10.1007/s00330-019-06186-9. Epub 2019 Apr 16.'}, {'pmid': '33486604', 'type': 'BACKGROUND', 'citation': 'Lang K, Hofvind S, Rodriguez-Ruiz A, Andersson I. Can artificial intelligence reduce the interval cancer rate in mammography screening? Eur Radiol. 2021 Aug;31(8):5940-5947. doi: 10.1007/s00330-021-07686-3. Epub 2021 Jan 23.'}, {'pmid': '32052311', 'type': 'BACKGROUND', 'citation': 'Sasaki M, Tozaki M, Rodriguez-Ruiz A, Yotsumoto D, Ichiki Y, Terawaki A, Oosako S, Sagara Y, Sagara Y. Artificial intelligence for breast cancer detection in mammography: experience of use of the ScreenPoint Medical Transpara system in 310 Japanese women. Breast Cancer. 2020 Jul;27(4):642-651. doi: 10.1007/s12282-020-01061-8. Epub 2020 Feb 12.'}, {'pmid': '34383147', 'type': 'BACKGROUND', 'citation': 'Kerschke L, Weigel S, Rodriguez-Ruiz A, Karssemeijer N, Heindel W. Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance. Eur Radiol. 2022 Feb;32(2):842-852. doi: 10.1007/s00330-021-08217-w. Epub 2021 Aug 12.'}]}, 'descriptionModule': {'briefSummary': 'The purpose of this observational study is to assess whether the use of AI (Transpara®) can lead to an improved quality of a double reading mammography screening program. This is investigated by performing AI as a third reader and as a decision support during the consensus meeting, compared with conventional mammography screening (double reading and consensus without AI).', 'detailedDescription': 'The AI cancer detection system will act as a 3rd reader and will recall additional cases to the consensus conference: the exams that were not recalled by double reading but are classified as the 3% most suspicious exams, based on AI derived cancer-risk scores. Secondly, AI is used as a decision support during consensus. AI risk scores and Computer-Aided Detection (CAD)-marks of suspicious calcifications and soft tissue lesions are provided to the reader(s).\n\nThe hypothesis of this study is that the use of AI has the potential to improve the quality of the screening program by increasing the cancer detection rate without affecting the recall rate.'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '74 Years', 'minimumAge': '40 Years', 'genderBased': True, 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Women eligible for population-based mammography screening', 'genderDescription': 'Female', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Women participating in the regular Breast Cancer Screening Program in Region Östergötland Linkoping\n\nExclusion Criteria:\n\n* Women with breast implants or other foreign implants in the mammogram\n* Women with symptoms or signs of suspected breast cancer'}, 'identificationModule': {'nctId': 'NCT05048095', 'acronym': 'AI-ROL', 'briefTitle': 'Artificial Intelligence in Breast Cancer Screening in Region Östergötland Linkoping', 'organization': {'class': 'OTHER', 'fullName': 'Ostergotland County Council, Sweden'}, 'officialTitle': 'The Use of AI as a Third Reader and During Consensus in a Double Reading Breast Cancer Screening Program in Sweden', 'orgStudyIdInfo': {'id': 'NCT20210157-AI-ROL'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Screened women in Region Östergötland Linkoping', 'interventionNames': ['Other: AI cancer detection system']}], 'interventions': [{'name': 'AI cancer detection system', 'type': 'OTHER', 'description': 'The use of AI as a third reader and as a decision support system during consensus meeting', 'armGroupLabels': ['Screened women in Region Östergötland Linkoping']}]}, 'contactsLocationsModule': {'locations': [{'zip': '58185', 'city': 'Linköping', 'state': 'Östergötland County', 'country': 'Sweden', 'facility': 'Region Östergötland', 'geoPoint': {'lat': 58.41086, 'lon': 15.62157}}], 'overallOfficials': [{'name': 'Håkan Gustafsson, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Linköping University - University Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Ostergotland County Council, Sweden', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Adjunct Senior Lecturer', 'investigatorFullName': 'Håkan Gustafsson', 'investigatorAffiliation': 'Ostergotland County Council, Sweden'}}}}