Sökning: WFRF:(Polymeri Erini)
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Deep learning-based...
Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
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- Polymeri, Erini (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för radiologi,Institute of Clinical Sciences, Department of Radiology,Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden,Sahlgrenska University Hospital
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- Sadik, M. (författare)
- Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
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- Kaboteh, R. (författare)
- Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
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- Borrelli, P. (författare)
- Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
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- Enqvist, Olof, 1981 (författare)
- Chalmers University of Technology
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- Ulén, Johannes (författare)
- Eigenvision AB, Malmö, Sweden
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- Ohlsson, Mattias, 1967- (författare)
- Halmstad University,Lund University,Lunds universitet,Högskolan i Halmstad,CAISR Centrum för tillämpade intelligenta system (IS-lab),Högskolan i Halmstad (HH),Halmstad University (HH)
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- Trägårdh, Elin (författare)
- Lund University,Lunds universitet,Nuklearmedicin, Malmö,Forskargrupper vid Lunds universitet,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Nuclear medicine, Malmö,Lund University Research Groups,LUCC: Lund University Cancer Centre,Other Strong Research Environments
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- Poulsen, M. H. (författare)
- Department of Urology, Odense University Hospital, Odense, Denmark
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- Simonsen, J. A. (författare)
- Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark
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- Hoilund-Carlsen, P. F. (författare)
- Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark
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- Johnsson, Åse (Allansdotter), 1966 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för radiologi,Institute of Clinical Sciences, Department of Radiology,Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden,Sahlgrenska University Hospital
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- Edenbrandt, Lars, 1957 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine,Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden,Sahlgrenska Academy
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(creator_code:org_t)
- 2019-12-20
- 2020
- Engelska.
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Ingår i: Clinical Physiology and Functional Imaging. - Chichester : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 40:2, s. 106-113
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https://doi.org/10.1...
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https://research.cha... (primary) (free)
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http://dx.doi.org/10... (free)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-naïve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2·65, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by Sørensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0·78 and 0·79, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P = 0·02), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival. © 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk laboratorie- och mätteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Laboratory and Measurements Technologies (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Urologi och njurmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Urology and Nephrology (hsv//eng)
Nyckelord
- artificial intelligence
- convolutional neural network
- objective quantification
- prostatic neoplasms
- artificial intelligence
- convolutional neural network
- objective quantification
- prostatic neoplasms
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Polymeri, Erini
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Sadik, M.
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Kaboteh, R.
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Borrelli, P.
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Enqvist, Olof, 1 ...
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Ulén, Johannes
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visa fler...
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Ohlsson, Mattias ...
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Trägårdh, Elin
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Poulsen, M. H.
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Simonsen, J. A.
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Hoilund-Carlsen, ...
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Johnsson, Åse (A ...
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Edenbrandt, Lars ...
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- Om ämnet
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- TEKNIK OCH TEKNOLOGIER
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TEKNIK OCH TEKNO ...
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och Medicinteknik
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och Medicinsk bildbe ...
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Radiologi och bi ...
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- TEKNIK OCH TEKNOLOGIER
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TEKNIK OCH TEKNO ...
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och Medicinteknik
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och Medicinsk labora ...
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Kardiologi
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Urologi och njur ...
- Artiklar i publikationen
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Clinical Physiol ...
- Av lärosätet
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Högskolan i Halmstad
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Chalmers tekniska högskola
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Göteborgs universitet
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Lunds universitet