Sökning: WFRF:(Polymeri Erini)
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Artificial intellig...
Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients
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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,University of Gothenburg,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,Sahlgrenska Academy
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- Kjölhede, Henrik, 1981 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för urologi,Institute of Clinical Sciences, Department of Urology,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,University of Gothenburg,Sahlgrenska Academy
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- Enqvist, Olof, 1981 (författare)
- Chalmers University of Technology
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- Ulen, J. (författare)
- Eigenvision AB
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- Poulsen, M. H. (författare)
- Odense University Hospital
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- Simonsen, J. A. (författare)
- Odense University Hospital
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- Borrelli, P. (författare)
- Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
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- Trägårdh, Elin (författare)
- Lund University,Lunds universitet,Nuklearmedicin, Malmö,Forskargrupper vid Lunds universitet,Klinisk fysiologi och nuklearmedicin, Malmö,WCMM- Wallenberg center för molekylär medicinsk forskning,Medicinska fakulteten,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Nuclear medicine, Malmö,Lund University Research Groups,Clinical Physiology and Nuclear Medicine, Malmö,WCMM-Wallenberg Centre for Molecular Medicine,Faculty of Medicine,LUCC: Lund University Cancer Centre,Other Strong Research Environments,Skåne University Hospital
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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,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,University of Gothenburg,Sahlgrenska Academy
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- Hoilund-Carlsen, P. F. (författare)
- Odense 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,University of Gothenburg,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,Sahlgrenska Academy
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(creator_code:org_t)
- 2021-09-25
- 2021
- Engelska.
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Ingår i: Scandinavian Journal of Urology. - : Medical Journals Sweden AB. - 2168-1805 .- 2168-1813. ; 55:6, s. 427-433
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Abstract
Ämnesord
Stäng
- Objective Artificial intelligence (AI) offers new opportunities for objective quantitative measurements of imaging biomarkers from positron-emission tomography/computed tomography (PET/CT). Clinical image reporting relies predominantly on observer-dependent visual assessment and easily accessible measures like SUVmax, representing lesion uptake in a relatively small amount of tissue. Our hypothesis is that measurements of total volume and lesion uptake of the entire tumour would better reflect the disease`s activity with prognostic significance, compared with conventional measurements. Methods An AI-based algorithm was trained to automatically measure the prostate and its tumour content in PET/CT of 145 patients. The algorithm was then tested retrospectively on 285 high-risk patients, who were examined using F-18-choline PET/CT for primary staging between April 2008 and July 2015. Prostate tumour volume, tumour fraction of the prostate gland, lesion uptake of the entire tumour, and SUVmax were obtained automatically. Associations between these measurements, age, PSA, Gleason score and prostate cancer-specific survival were studied, using a Cox proportional-hazards regression model. Results Twenty-three patients died of prostate cancer during follow-up (median survival 3.8 years). Total tumour volume of the prostate (p = 0.008), tumour fraction of the gland (p = 0.005), total lesion uptake of the prostate (p = 0.02), and age (p = 0.01) were significantly associated with disease-specific survival, whereas SUVmax (p = 0.2), PSA (p = 0.2), and Gleason score (p = 0.8) were not. Conclusion AI-based assessments of total tumour volume and lesion uptake were significantly associated with disease-specific survival in this patient cohort, whereas SUVmax and Gleason scores were not. The AI-based approach appears well-suited for clinically relevant patient stratification and monitoring of individual therapy.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Urologi och njurmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Urology and Nephrology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (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)
Nyckelord
- Artificial intelligence
- prostate cancer
- F-18-choline-PET
- CT
- imaging
- biomarkers
- disease-specific survival
- positron-emission-tomography
- ct
- Urology & Nephrology
- prostate cancer
- F-choline-PET/CT
- imaging biomarkers
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- ref (ämneskategori)
- art (ämneskategori)
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Polymeri, Erini
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Kjölhede, Henrik ...
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Enqvist, Olof, 1 ...
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Ulen, J.
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Poulsen, M. H.
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Simonsen, J. A.
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visa fler...
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Borrelli, P.
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Trägårdh, Elin
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Johnsson, Åse (A ...
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Hoilund-Carlsen, ...
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Edenbrandt, Lars ...
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