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Papp L, Spielvogel CP, Grubmüller B, Grahovac M, Krajnc D, Ecsedi B, Sareshgi RAM, Mohamad D, Hamboeck M, Rausch I, Mitterhauser M, Wadsak W, Haug AR, Kenner L, Mazal P, Susani M, Hartenbach S, Baltzer P, Helbich TH, Kramer G, Shariat SF, Beyer T, Hartenbach M, Hacker M. Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [ 68Ga]Ga-PSMA-11 PET/MRI. Eur J Nucl Med Mol Imaging 2021; 48:1795-1805. [PMID: 33341915 PMCID: PMC8113201 DOI: 10.1007/s00259-020-05140-y] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 11/29/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning. METHODS Fifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses. RESULTS The area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively. CONCLUSION Our results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.
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Affiliation(s)
- L Papp
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - C P Spielvogel
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Christian Doppler Laboratory for Applied Metabolomics, Vienna, Austria
| | - B Grubmüller
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - M Grahovac
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - D Krajnc
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - B Ecsedi
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - R A M Sareshgi
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - D Mohamad
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - M Hamboeck
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - I Rausch
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - M Mitterhauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Ludwig Boltzmann Institute Applied Diagnostics, Vienna, Austria
| | - W Wadsak
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - A R Haug
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Christian Doppler Laboratory for Applied Metabolomics, Vienna, Austria
| | - L Kenner
- Christian Doppler Laboratory for Applied Metabolomics, Vienna, Austria
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | - P Mazal
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | - M Susani
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | | | - P Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Common General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - T H Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of Common General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - G Kramer
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - S F Shariat
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - T Beyer
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - M Hartenbach
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - M Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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Geist BK, Baltzer P, Fueger B, Hamboeck M, Nakuz T, Papp L, Rasul S, Sundar LKS, Hacker M, Staudenherz A. Assessment of the kidney function parameters split function, mean transit time, and outflow efficiency using dynamic FDG-PET/MRI in healthy subjects. Eur J Hybrid Imaging 2019; 3:3. [PMID: 34191174 PMCID: PMC8212313 DOI: 10.1186/s41824-019-0051-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 01/17/2019] [Indexed: 11/29/2022] Open
Abstract
Background Traditionally, isotope nephrography is considered as the method of choice to assess kidney function parameters in nuclear medicine. We propose a novel approach to determine the split function (SF), mean transit time (MTT), and outflow efficiency (OE) with 2-deoxy-2-[18F]fluoro-D-glucose (FDG) dynamic positron emission tomography (PET). Materials and methods Healthy adult subjects underwent dynamic simultaneous FDG-PET and magnetic resonance imaging (PET/MRI). Time-activity curves (TACs) of total kidneys, renal cortices, and the aorta were prospectively obtained from dynamic PET series. MRI images were used for anatomical correlation. The same individuals were subjected to dynamic renal Technetium-99 m-mercaptoacetyltriglycine (MAG3) scintigraphy and TACs of kidneys; the perirenal background and the left ventricle were determined. SF was calculated on the basis of integrals over the TACs, MTT was determined from renal retention functions after deconvolution analysis, and OE was determined from MTT. Values obtained from PET series were compared with scintigraphic parameters, which served as the reference. Results Twenty-four subjects underwent both examinations. Total kidney SF, MTT, and OE as estimated by dynamic PET/MRI correlated to their reference values by r = 0.75, r = 0.74 and r = 0.81, respectively, with significant difference (p < 0.0001) between the means of MTT and OE. No correlations were found for cortex FDG values. Conclusions The study proofs the concept that SF, MTT, and OE can be estimated with dynamic FDG PET/MRI scans in healthy kidneys. This has advantages for patients receiving a routine PET/MRI scan, as kidney parameters can be estimated simultaneously to functional and morphological imaging with high accuracy.
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Geist BK, Baltzer P, Fueger B, Hamboeck M, Nakuz T, Papp L, Rasul S, Sundar LKS, Hacker M, Staudenherz A. Assessing the kidney function parameters glomerular filtration rate and effective renal plasma flow with dynamic FDG-PET/MRI in healthy subjects. EJNMMI Res 2018; 8:37. [PMID: 29744748 PMCID: PMC5943199 DOI: 10.1186/s13550-018-0389-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 04/17/2018] [Indexed: 11/16/2022] Open
Abstract
Background A method was developed to assess the kidney parameters glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) from 2-deoxy-2-[18F]fluoro-d-glucose (FDG) concentration behavior in kidneys, measured with positron emission tomography (PET) scans. Twenty-four healthy adult subjects prospectively underwent dynamic simultaneous PET/magnetic resonance imaging (MRI) examination. Time activity curves (TACs) were obtained from the dynamic PET series, with the guidance of MR information. Patlak analysis was performed to determine the GFR, and based on integrals, ERPF was calculated. Results were compared to intra-individually obtained reference values determined from venous blood samples. Results Total kidney GFR and ERPF as estimated by dynamic PET/MRI were highly correlated to their reference values (r = 0.88/p < 0.0001 and r = 0.82/p < 0.0001, respectively) with no significant difference between their means. Conclusions The study is a proof of concept that GFR and ERPF can be assessed with dynamic FDG PET/MRI scans in healthy kidneys. This has advantages for patients getting a routine scan, where additional examinations for kidney function estimation could be avoided. Further studies are required for transferring this PET/MRI method to PET/CT applications. Electronic supplementary material The online version of this article (10.1186/s13550-018-0389-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Barbara K Geist
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Pascal Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - Barbara Fueger
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - Martina Hamboeck
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Thomas Nakuz
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Laszlo Papp
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Sazan Rasul
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | | | - Marcus Hacker
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - Anton Staudenherz
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
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Widhalm HK, Seemann R, Hamboeck M, Mittlboeck M, Neuhold A, Friedrich K, Hajdu S, Widhalm K. Osteoarthritis in morbidly obese children and adolescents, an age-matched controlled study. Knee Surg Sports Traumatol Arthrosc 2016; 24:644-52. [PMID: 24841943 DOI: 10.1007/s00167-014-3068-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 05/05/2014] [Indexed: 02/02/2023]
Abstract
PURPOSE Main objective of this study was to investigate the association of pain and early cartilage lesions in morbidly obese children and adolescents. METHODS A total of 57 subjects were included in the study. Morbidly obese patients (n = 39) were subdivided into two groups: Group A: (11 males and 9 females, 14.2 ± 2.7 years) with permanent knee pain; and Group B: (10 males and 9 females, 14.4 ± 2.2 years) without permanent or without any knee pain. Group C (8 males and 10 females, 15.0 ± 2.9 years) included age-matched children and adolescents of normal weight. MRI examinations were performed in all subjects, and an extensive analysis of the images was conducted according to the condition of the cartilage surface and the meniscus. Patients' subjective health was assessed by means of four well-known knee scores (IKDC, KOOS, Tegner/Lysholm, and VAS). Nonparametric Jonckheere-Terpstra test was used to test the trend of the natural order between the three groups. RESULTS In 38 of 39 morbidly obese children and adolescents, in at least one region of the knee, a marked cartilage lesion could be shown by MRI. Group A showed significantly (p < 0.001) more cartilage lesions (mean 3.7) compared to Group B (mean 2.8) and Group C (mean 0.8). IKDC, and all the KOOS subunits, showed significantly (p < 0.001, p Bonferroni < 0.001) increasing scores from Group A to B to C, in addition to KOOS symptoms. CONCLUSIONS Morbid obesity causes early lesions of the knee cartilage, even in young patients. Significantly, more patients with reported pain show more severe damages.
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Affiliation(s)
- H K Widhalm
- Department of Trauma Surgery, Center for Joints and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - R Seemann
- Department of Maxillofacial Surgery, Medical University of Vienna, Vienna, Austria.
| | - M Hamboeck
- Department of Trauma Surgery, Center for Joints and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - M Mittlboeck
- Department of Medical Statistics, Medical University of Vienna, Vienna, Austria.
| | - A Neuhold
- Department of Radiology, Private Hospital Rudolfinerhaus, Vienna, Austria.
| | - K Friedrich
- Department of Radiology, Medical University of Vienna, Vienna, Austria.
| | - S Hajdu
- Department of Trauma Surgery, Center for Joints and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - K Widhalm
- Department of Pediatrics, Paracelsus Private Medical University, Salzburg, Austria.
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