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Wong LM, Sutherland T, Perry E, Tran V, Spelman T, Corcoran N, Lawrentschuk N, Woo H, Lenaghan D, Buchan N, Bax K, Symons J, Saeed Goolam A, Chalasani V, Hegarty J, Thomas L, Christov A, Ng M, Khanani H, Lee SF, Taubman K, Tarlinton L. Fluorine-18-labelled Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography or Magnetic Resonance Imaging to Diagnose and Localise Prostate Cancer. A Prospective Single-arm Paired Comparison (PEDAL). Eur Urol Oncol 2024:S2588-9311(24)00026-9. [PMID: 38281891 DOI: 10.1016/j.euo.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/03/2023] [Accepted: 01/05/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND AND OBJECTIVE Multiparametric magnetic resonance imaging (mpMRI) of the prostate is used for prostate cancer diagnosis. However, mpMRI has lower sensitivity for small tumours. Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT) offers increased sensitivity over conventional imaging. This study aims to determine whether the diagnostic accuracy of 18F-DCFPyL PSMA-PET/CT was superior to that of mpMRI for detecting prostate cancer (PCa) at biopsy. METHODS Between 2020 and 2021, a prospective multicentre single-arm phase 3 imaging trial enrolled patients with clinical suspicion for PCa to have both mpMRI and PSMA-PET/CT (thorax to thigh), with reviewers blinded to the results of other imaging. Multiparametric MRI was considered positive for Prostate Imaging Reporting and Data System (PIRADS) 3-5. PSMA-PET/CT was assessed quantitatively (positive maximum standardised uptake value [SUVmax] >7) and qualitatively (five-point lexicon of certainty). Patients underwent targeted and systematic biopsy, with the technique at the discretion of the treating urologist. Clinically significant PCa (csPCa) was defined as International Society of Urological Pathology grade group (GG) ≥2. The primary outcome was the diagnostic accuracy for detecting PCa, reported as sensitivity, specificity, negative predictive value (NPV), and area under the curve (AUC) of the receiver operating curve. The secondary endpoints included a comparison of the diagnostic accuracy for detecting csPCa, assessing gains in combining PMSA-PET/CT with mpMRI to mpMRI alone. KEY FINDINGS AND LIMITATIONS Of the 236 patients completing both mpMRI and PSMA-PET/CT, 184 (76.7%) had biopsy. Biopsy histology was benign (n = 73), GG 1 (n = 27), and GG ≥2 (n = 84). The diagnostic accuracy of mpMRI for detecting PCa (AUC 0.76; 95% confidence interval [CI] 0.69, 0.82) was higher than that of PSMA-PET/CT (AUC 0.63; 95% CI 0.56, 0.70, p = 0.03). The diagnostic accuracy of mpMRI for detecting csPCa (AUC 0.72; 95% CI 0.67, 0.78) was higher than that of PSMA-PET/CT (AUC 0.62; 95% CI 0.55, 0.69) but not statistically significant (p = 0.27). A combination of PSMA-PET/CT and mpMRI showed excellent sensitivity (98.8%, 95% CI 93.5%, 100%) and NPV (96%, 95% CI 79.6%, 99.9%) over mpMRI alone (86.9% and 80.7%, respectively, p = 0.01). Thirty-two patients (13.6%) had metastatic disease. They tended to be older (68.4 vs 65.1 yr, p = 0.023), and have higher prostate-specific antigen (PSA; median PSA 9.6 vs 6.2ng/ml, p < 0.001) and abnormal prostate on digital rectal examination (78.2% vs 44.1%, p < 0.001). CONCLUSIONS AND CLINICAL IMPLICATIONS Multiparametric MRI had superior diagnostic accuracy to PSMA-PET/CT for detecting PCa, though the difference is not significant in case of csPCa detection. A combination of mpMRI and PSMA-PET/CT showed improved sensitivity and NPV. PSMA-PET/CT could be considered for diagnostic use in patients unable to have mpMRI or those with concerning clinical features but negative mpMRI. PATIENT SUMMARY In this trial, we compared the ability of 18F-labelled prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT) with that of multiparametric magnetic resonance imaging (mpMRI) to diagnose prostate cancer by biopsy in a prostate-specific antigen screening population. We found that MRI was superior to PSMA to diagnose prostate cancer, though there was no difference in ability to diagnose clinically significant prostate cancer. PSMA-PET/CT could be considered for diagnostic use in patients unable to have mpMRI or those with concerning clinical features but negative mpMRI. Combining MRI with PSMA-PET increases the negative predictive value over MRI alone and may help men avoid invasive prostate biopsy.
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Affiliation(s)
- Lih-Ming Wong
- Department of Urology, St Vincent's Health, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia.
| | - Tom Sutherland
- Department of Medical Imaging, St Vincent's Health, Melbourne, Australia; Faculty of Medicine, University of Melbourne, Melbourne, Australia
| | - Elisa Perry
- Pacific Radiology, Christchurch, Canterbury, New Zealand
| | - Vy Tran
- Department of Urology, St Vincent's Health, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Tim Spelman
- Department of Surgery, University of Melbourne, Melbourne, Australia; Burnet Institute, Melbourne, Australia
| | - Niall Corcoran
- Department of Surgery, University of Melbourne, Melbourne, Australia; Department of Urology, Melbourne Health, Melbourne, Australia
| | - Nathan Lawrentschuk
- Department of Surgery, University of Melbourne, Melbourne, Australia; Department of Urology, Melbourne Health, Melbourne, Australia; EJ Whitten Prostate Cancer Research Centre at Epworth Healthcare, Melbourne, Australia
| | - Henry Woo
- Department of Urology, Sydney Adventist Hospital, New South Wales, Australia; Sydney Adventist Northshore Prostate Centre of Excellence, Sydney Adventist Hospital, New South Wales, Australia
| | - Daniel Lenaghan
- Department of Urology, St Vincent's Health, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Nicholas Buchan
- Christchurch Public Hospital, Urology Associates, Christchurch, New Zealand; Canterbury Urology Research Trust Board, Christchurch, New Zealand
| | - Kevin Bax
- Christchurch Public Hospital, Urology Associates, Christchurch, New Zealand; Canterbury Urology Research Trust Board, Christchurch, New Zealand
| | - James Symons
- Department of Urology, Sydney Adventist Hospital, New South Wales, Australia
| | - Ahmed Saeed Goolam
- Department of Urology, Sydney Adventist Hospital, New South Wales, Australia
| | - Venu Chalasani
- Department of Urology, Sydney Adventist Hospital, New South Wales, Australia
| | - Justin Hegarty
- Pacific Radiology, Christchurch, Canterbury, New Zealand
| | - Lauren Thomas
- Department of Medical Imaging, St Vincent's Health, Melbourne, Australia; Faculty of Medicine, University of Melbourne, Melbourne, Australia
| | - Alexandar Christov
- Department of Urology, St Vincent's Health, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Michael Ng
- GenesisCare, St Vincent's, Melbourne, Australia
| | - Hadia Khanani
- Sydney Adventist Northshore Prostate Centre of Excellence, Sydney Adventist Hospital, New South Wales, Australia
| | - Su-Faye Lee
- Department of Medical Imaging, St Vincent's Health, Melbourne, Australia; Faculty of Medicine, University of Melbourne, Melbourne, Australia
| | - Kim Taubman
- Department of Medical Imaging, St Vincent's Health, Melbourne, Australia; Faculty of Medicine, University of Melbourne, Melbourne, Australia
| | - Lisa Tarlinton
- Sydney Adventist Northshore Prostate Centre of Excellence, Sydney Adventist Hospital, New South Wales, Australia
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Hunter JG, Gad M, Gupta A. Improved Visualization of Lymphomatous Cardiac Involvement with Retrospective PET/MRI Fusion. Radiol Imaging Cancer 2023; 5:e230073. [PMID: 37830923 DOI: 10.1148/rycan.230073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Affiliation(s)
- Joshua G Hunter
- From the Case Western Reserve University School of Medicine, Health Education Campus, 9501 Euclid Ave, Cleveland, OH 44106 (J.G.H.); Section of Cardiovascular Medicine, Baylor College of Medicine, Houston, Tex (M.G.); and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (A.G.)
| | - Mohamed Gad
- From the Case Western Reserve University School of Medicine, Health Education Campus, 9501 Euclid Ave, Cleveland, OH 44106 (J.G.H.); Section of Cardiovascular Medicine, Baylor College of Medicine, Houston, Tex (M.G.); and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (A.G.)
| | - Amit Gupta
- From the Case Western Reserve University School of Medicine, Health Education Campus, 9501 Euclid Ave, Cleveland, OH 44106 (J.G.H.); Section of Cardiovascular Medicine, Baylor College of Medicine, Houston, Tex (M.G.); and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (A.G.)
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Maddury S, Desai K. DeepAD: A deep learning application for predicting amyloid standardized uptake value ratio through PET for Alzheimer's prognosis. Front Artif Intell 2023; 6:1091506. [PMID: 36815006 PMCID: PMC9939778 DOI: 10.3389/frai.2023.1091506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/10/2023] [Indexed: 02/08/2023] Open
Abstract
Introduction Amyloid deposition is a vital biomarker in the process of Alzheimer's diagnosis. 18F-florbetapir PET scans can provide valuable imaging data to determine cortical amyloid quantities. However, the process is labor and doctor intensive, requiring extremely specialized education and resources that may not be accessible to everyone, making the amyloid calculation process inefficient. Deep learning is a rising tool in Alzheimer's research which could be used to determine amyloid deposition. Materials and methods Using data from the Alzheimer's Disease Neuroimaging Initiative, we identified 2,980 patients with PET imaging, clinical, and genetic data. We tested various ResNet, EfficientNet, and RegNet convolutional neural networks and later combined the best performing model with Gradient Boosting Decision Tree algorithms to predict standardized uptake value ratio (SUVR) of amyloid in each patient session. We tried several configurations to find the best model tuning for regression-to-SUVR. Results We found that the RegNet X064 architecture combined with a grid search-tuned Gradient Boosting Decision Tree with 3 axial input slices and clinical and genetic data achieved the lowest loss. Using the mean-absolute-error metric, the loss converged to an MAE of 0.0441, equating to 96.4% accuracy across the 596-patient test set. Discussion We showed that this method is more consistent and accessible in comparison to human readers from previous studies, with lower margins of error and substantially faster calculation times. We implemented our deep learning model on to a web application named DeepAD which allows our diagnostic tool to be accessible. DeepAD could be used in hospitals and clinics with resource limitations for amyloid deposition and shows promise for more imaging tasks as well.
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Prognostic Value of Hybrid PET/MR Imaging in Patients with Differentiated Thyroid Cancer. Cancers (Basel) 2022; 14:cancers14122958. [PMID: 35740623 PMCID: PMC9220891 DOI: 10.3390/cancers14122958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/13/2022] [Accepted: 06/15/2022] [Indexed: 02/01/2023] Open
Abstract
Background: Hybrid positron emission tomography (PET)/magnetic resonance (MR) is an emerging imaging modality with great potential to provide complementary data acquired at the same time, under the same physiological conditions. The aim of this study was to evaluate the prognostic value of hybrid 18F-fluorodeoxyglucose (FDG) PET/MR in patients with differentiated thyroid cancer (DTC) who underwent total thyroidectomy and radioactive iodine therapy for suspicion of disease relapse. Methods: Between November 2015 and February 2017, 55 patients underwent hybrid 18F-FDG PET/MR. Assessment of positive MR was made considering all sequences in terms of malignancy based on the morphological T2-weighted features and the presence of restricted diffusivity on diffusion-weighted imaging images and both needed to be positive on the same lesion. Both foci with abnormal 18F-FDG uptake, which corresponded to tissue abnormalities on the MR, and tracer accumulation, which did not correspond to normal morphological structures, were considered positive. Results: During follow-up (mean 42 ± 27 months), 29 patients (53%) had disease recurrence. In the Cox univariate regression analysis age, serum Tg level ≥ 2 ng/mL, positive short tau inversion recovery (STIR), and positive PET were significant predictors of DTC recurrence. Kaplan−Meier survival analyses showed that patients with Tg ≥ 2 ng/mL had poorer outcomes compared to those with serum Tg level < 2 ng/mL (p < 0.05). Similarly, patients with positive STIR and positive PET had a worst outcome compared to those with negative STIR (p < 0.05) and negative PET (p < 0.005). Survival analysis performed in the subgroup of 36 subjects with Tg level ≥ 2 ng/mL revealed that patients with positive PET had a worst outcome compared to those with negative PET (p < 0.05). Conclusions: Age, serum Tg level ≥ 2 ng/mL, positive STIR, and positive 18F-FDG PET were significant predictors of DTC recurrence. However, the serum Tg level was the only independent predictor of DTC. Hybrid PET/MR imaging may have the potential to improve the information content of one modality with the other and would offer new opportunities in patients with DTC. Thus, further studies in a larger patient population are needed to understand the additional value of 18F-FDG PET/MR in patients with DTC.
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Agaronyan A, Syed R, Kim R, Hsu CH, Love SA, Hooker JM, Reid AE, Wang PC, Ishibashi N, Kang Y, Tu TW. A Baboon Brain Atlas for Magnetic Resonance Imaging and Positron Emission Tomography Image Analysis. Front Neuroanat 2022; 15:778769. [PMID: 35095430 PMCID: PMC8795914 DOI: 10.3389/fnana.2021.778769] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/17/2021] [Indexed: 12/14/2022] Open
Abstract
The olive baboon (Papio anubis) is phylogenetically proximal to humans. Investigation into the baboon brain has shed light on the function and organization of the human brain, as well as on the mechanistic insights of neurological disorders such as Alzheimer's and Parkinson's. Non-invasive brain imaging, including positron emission tomography (PET) and magnetic resonance imaging (MRI), are the primary outcome measures frequently used in baboon studies. PET functional imaging has long been used to study cerebral metabolic processes, though it lacks clear and reliable anatomical information. In contrast, MRI provides a clear definition of soft tissue with high resolution and contrast to distinguish brain pathology and anatomy, but lacks specific markers of neuroreceptors and/or neurometabolites. There is a need to create a brain atlas that combines the anatomical and functional/neurochemical data independently available from MRI and PET. For this purpose, a three-dimensional atlas of the olive baboon brain was developed to enable multimodal imaging analysis. The atlas was created on a population-representative template encompassing 89 baboon brains. The atlas defines 24 brain regions, including the thalamus, cerebral cortex, putamen, corpus callosum, and insula. The atlas was evaluated with four MRI images and 20 PET images employing the radiotracers for [11C]benzamide, [11C]metergoline, [18F]FAHA, and [11C]rolipram, with and without structural aids like [18F]flurodeoxyglycose images. The atlas-based analysis pipeline includes automated segmentation, registration, quantification of region volume, the volume of distribution, and standardized uptake value. Results showed that, in comparison to PET analysis utilizing the "gold standard" manual quantification by neuroscientists, the performance of the atlas-based analysis was at >80 and >70% agreement for MRI and PET, respectively. The atlas can serve as a foundation for further refinement, and incorporation into a high-throughput workflow of baboon PET and MRI data. The new atlas is freely available on the Figshare online repository (https://doi.org/10.6084/m9.figshare.16663339), and the template images are available from neuroImaging tools & resources collaboratory (NITRC) (https://www.nitrc.org/projects/haiko89/).
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Affiliation(s)
- Artur Agaronyan
- Center for Neuroscience Research, Children’s National Hospital, Washington, DC, United States
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
| | - Raeyan Syed
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
| | - Ryan Kim
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
| | - Chao-Hsiung Hsu
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
| | - Scott A. Love
- CNRS, IFCE, INRAE, Université de Tours, PRC, Nouzilly, France
| | - Jacob M. Hooker
- Department of Radiology, Martinos Center, Boston, MA, United States
| | - Alicia E. Reid
- Department of Chemistry, Medgar Evers College, Brooklyn, NY, United States
| | - Paul C. Wang
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
- Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Nobuyuki Ishibashi
- Center for Neuroscience Research, Children’s National Hospital, Washington, DC, United States
| | - Yeona Kang
- Department of Mathematics, Howard University, Washington, DC, United States
| | - Tsang-Wei Tu
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, United States
- Department of Pediatrics, School of Medicine and Health Sciences, George Washington University, Washington, DC, United States
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Khosropanah P, Ho ETW, Lim KS, Fong SL, Thuy Le MA, Narayanan V. EEG Source Imaging (ESI) utility in clinical practice. BIOMED ENG-BIOMED TE 2020; 65:/j/bmte.ahead-of-print/bmt-2019-0128/bmt-2019-0128.xml. [PMID: 32623371 DOI: 10.1515/bmt-2019-0128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 02/21/2020] [Indexed: 11/15/2022]
Abstract
Epilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73-91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.
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Affiliation(s)
- Pegah Khosropanah
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric Tatt-Wei Ho
- Center for Intelligent Signal & Imaging Research, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
- Department of Electrical & Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Kheng-Seang Lim
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Si-Lei Fong
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Minh-An Thuy Le
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Neurology, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Vairavan Narayanan
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Abstract
PURPOSE To review how PET/MR technology could add value for pediatric cancer patients. RECENT FINDINGS Since many primary tumors in children are evaluated with MRI and metastases are detected with PET/CT, integrated PET/MR can be a time-efficient and convenient solution for pediatric cancer staging. 18F-FDG PET/MR can assess primary tumors and the whole body in one imaging session, avoid repetitive anesthesia and reduce radiation exposure compared to 18F-FDG PET/CT. This article lists 10 action points, which might improve the clinical value of PET/MR for children with cancer. However, even if PET/MR proves valuable, it cannot enter mainstream applications if it is not accessible to the majority of pediatric cancer patients. Therefore, innovations are needed to make PET/MR scanners affordable and increase patient throughput. SUMMARY PET/MR offers opportunities for more efficient, accurate and safe diagnoses of pediatric cancer patients. The impact on patient management and outcomes has to be substantiated by large-scale prospective clinical trials.
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Affiliation(s)
- Heike Daldrup-Link
- Department of Radiology, Lucile Packard Children's Hospital, and Pediatric Molecular Imaging Program (@PedsMIPS) in the Molecular Imaging Program at Stanford (MIPS), Stanford University
- Department of Pediatrics, Stanford University
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