1
|
Poder J, Radvan S, Howie A, Kasraei F, Parker A, Bucci J, Haworth A. Viability of focal dose escalation to prostate cancer intraprostatic lesions using HDR prostate brachytherapy. Brachytherapy 2023; 22:800-807. [PMID: 37748989 DOI: 10.1016/j.brachy.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/27/2023]
Abstract
PURPOSE This study aimed to determine the viability of focal dose escalation to prostate cancer intraprostatic lesions (IPLs) from multiparametric magnetic resonance (mpMRI) and prostate-specific membrane antigen positron emission tomography (PSMA-PET) images using high-dose-rate (HDR) prostate brachytherapy (pBT). METHODS AND MATERIALS Retrospective data from 20 patients treated with HDR pBT was utilized. The interobserver contouring variability of 5 observers was quantified using the dice similarity coefficient (DSC) and mean distance to agreement (MDA). Uncertainty in propagating IPL contours to trans-rectal ultrasound (TRUS) was quantified using a tissue equivalent prostate phantom. Feasibility of incorporating IPLs into HDR pBT planning was tested on retrospective patient data. RESULTS The average observer DSC was 0.65 (PSMA-PET) and 0.52 (mpMRI). The uncertainty in propagating IPL contours was 0.6 mm (PSMA-PET), and 0.4 mm (mpMRI). Uncertainties could be accounted for by expanding IPL contours by 2 mm to create IPL PTVs. The mean D98% achieved using HDR pBT was 166% and 135% for the IPL and IPL PTV contours, respectively. CONCLUSIONS Focal dose escalation to IPLs identified on either PSMA-PET or mpMRI is viable using TRUS-based HDR pBT. Utilizing HDR pBT allows dose escalation of up to 166% of the prescribed dose to the prostate.
Collapse
Affiliation(s)
- Joel Poder
- Department of Radiation Oncology, St George Hospital Cancer Care Centre, Kogarah, NSW, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia; School of Physics, University of Sydney, Camperdown, NSW, Australia.
| | - Samantha Radvan
- School of Physics, University of Sydney, Camperdown, NSW, Australia
| | - Andrew Howie
- Department of Radiation Oncology, St George Hospital Cancer Care Centre, Kogarah, NSW, Australia
| | - Farshad Kasraei
- Department of Radiation Oncology, St George Hospital Cancer Care Centre, Kogarah, NSW, Australia
| | - Annaleise Parker
- Department of Radiation Oncology, St George Hospital Cancer Care Centre, Kogarah, NSW, Australia
| | - Joseph Bucci
- Department of Radiation Oncology, St George Hospital Cancer Care Centre, Kogarah, NSW, Australia
| | - Annette Haworth
- School of Physics, University of Sydney, Camperdown, NSW, Australia
| |
Collapse
|
2
|
Berger D, Van Dyk S, Beaulieu L, Major T, Kron T. Modern Tools for Modern Brachytherapy. Clin Oncol (R Coll Radiol) 2023:S0936-6555(23)00182-6. [PMID: 37217434 DOI: 10.1016/j.clon.2023.05.003] [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: 10/14/2022] [Revised: 03/28/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023]
Abstract
This review aims to showcase the brachytherapy tools and technologies that have emerged during the last 10 years. Soft-tissue contrast using magnetic resonance and ultrasound imaging has seen enormous growth in use to plan all forms of brachytherapy. The era of image-guided brachytherapy has encouraged the development of advanced applicators and given rise to the growth of individualised 3D printing to achieve reproducible and predictable implants. These advances increase the quality of implants to better direct radiation to target volumes while sparing normal tissue. Applicator reconstruction has moved beyond manual digitising, to drag and drop of three-dimensional applicator models with embedded pre-defined source pathways, ready for auto-recognition and automation. The simplified TG-43 dose calculation formalism directly linked to reference air kerma rate of high-energy sources in the medium water remains clinically robust. Model-based dose calculation algorithms accounting for tissue heterogeneity and applicator material will advance the field of brachytherapy dosimetry to become more clinically accurate. Improved dose-optimising toolkits contribute to the real-time and adaptive planning portfolio that harmonises and expedites the entire image-guided brachytherapy process. Traditional planning strategies remain relevant to validate emerging technologies and should continue to be incorporated in practice, particularly for cervical cancer. Overall, technological developments need commissioning and validation to make the best use of the advanced features by understanding their strengths and limitations. Brachytherapy has become high-tech and modern by respecting tradition and remaining accessible to all.
Collapse
Affiliation(s)
- D Berger
- International Atomic Energy Agency, Vienna International Centre, Vienna, Austria.
| | - S Van Dyk
- Radiation Therapy Services, Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - L Beaulieu
- Service de Physique Médicale et Radioprotection, et Axe Oncologie du Centre de Recherche du CHU de Québec, CHU de Québec, Québec, Canada; Département de Physique, de Génie Physique et d'Optique et Centre de Recherche sur le Cancer, Université Laval, Québec, Canada
| | - T Major
- Radiotherapy Centre, National Institute of Oncology, Budapest, Hungary; Department of Oncology, Semmelweis University, Budapest, Hungary
| | - T Kron
- Peter MacCallum Cancer Centre and Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| |
Collapse
|
3
|
Orlando N, Edirisinghe C, Gyacskov I, Vickress J, Sachdeva R, Gomez JA, D'Souza D, Velker V, Mendez LC, Bauman G, Fenster A, Hoover DA. Validation of a surface-based deformable MRI-3D ultrasound image registration algorithm toward clinical implementation for interstitial prostate brachytherapy. Brachytherapy 2023; 22:199-209. [PMID: 36641305 DOI: 10.1016/j.brachy.2022.11.011] [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: 06/21/2022] [Revised: 11/05/2022] [Accepted: 11/28/2022] [Indexed: 01/13/2023]
Abstract
PURPOSE The purpose of this study was to evaluate and clinically implement a deformable surface-based magnetic resonance imaging (MRI) to three-dimensional ultrasound (US) image registration algorithm for prostate brachytherapy (BT) with the aim to reduce operator dependence and facilitate dose escalation to an MRI-defined target. METHODS AND MATERIALS Our surface-based deformable image registration (DIR) algorithm first translates and scales to align the US- and MR-defined prostate surfaces, followed by deformation of the MR-defined prostate surface to match the US-defined prostate surface. The algorithm performance was assessed in a phantom using three deformation levels, followed by validation in three retrospective high-dose-rate BT clinical cases. For comparison, manual rigid registration and cognitive fusion by physician were also employed. Registration accuracy was assessed using the Dice similarity coefficient (DSC) and target registration error (TRE) for embedded spherical landmarks. The algorithm was then implemented intraoperatively in a prospective clinical case. RESULTS In the phantom, our DIR algorithm demonstrated a mean DSC and TRE of 0.74 ± 0.08 and 0.94 ± 0.49 mm, respectively, significantly improving the performance compared to manual rigid registration with 0.64 ± 0.16 and 1.88 ± 1.24 mm, respectively. Clinical results demonstrated reduced variability compared to the current standard of cognitive fusion by physicians. CONCLUSIONS We successfully validated a DIR algorithm allowing for translation of MR-defined target and organ-at-risk contours into the intraoperative environment. Prospective clinical implementation demonstrated the intraoperative feasibility of our algorithm, facilitating targeted biopsies and dose escalation to the MR-defined lesion. This method provides the potential to standardize the registration procedure between physicians, reducing operator dependence.
Collapse
Affiliation(s)
- Nathan Orlando
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Robarts Research Institute, Western University, London, Ontario, Canada.
| | | | - Igor Gyacskov
- Robarts Research Institute, Western University, London, Ontario, Canada
| | - Jason Vickress
- Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| | - Robin Sachdeva
- Lawson Health Research Institute, London, Ontario, Canada
| | - Jose A Gomez
- London Health Sciences Centre, London, Ontario, Canada; Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - David D'Souza
- Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| | - Vikram Velker
- Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| | - Lucas C Mendez
- Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| | - Glenn Bauman
- Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| | - Aaron Fenster
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Robarts Research Institute, Western University, London, Ontario, Canada; Department of Oncology, Western University, London, Ontario, Canada
| | - Douglas A Hoover
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Oncology, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada
| |
Collapse
|
4
|
Grajales D, Picot F, Shams R, Dallaire F, Sheehy G, Alley S, Barkati M, Delouya G, Carrier JF, Birlea M, Trudel D, Leblond F, Ménard C, Kadoury S. Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-220064GR. [PMID: 36085571 PMCID: PMC9459023 DOI: 10.1117/1.jbo.27.9.095004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 08/12/2022] [Indexed: 06/01/2023]
Abstract
SIGNIFICANCE The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and efficacy of radiotherapy. AIM To evaluate the performance of multimodal PCa detection using biomolecular features from in-situ Raman spectroscopy (RS) combined with image-based (radiomics) features from multiparametric magnetic resonance images (mpMRI). APPROACH In a prospective pilot clinical study, 18 patients were recruited and underwent high-dose-rate brachytherapy. Multimodality image fusion (preoperative mpMRI with intraoperative transrectal ultrasound) combined with electromagnetic tracking was used to navigate an RS needle in the prostate prior to brachytherapy. This resulting dataset consisted of Raman spectra and co-located radiomics features from mpMRI. Feature selection was performed with the constraint that no more than 10 features were retained overall from a combination of inelastic scattering spectra and radiomics. These features were used to train support vector machine classifiers for PCa detection based on leave-one-patient-out cross-validation. RESULTS RS along with biopsy samples were acquired from 47 sites along the insertion trajectory of the fiber-optics needle: 26 were confirmed as benign or grade group = 1, and 21 as grade group >1, according to histopathological reports. The combination of the fingerprint region of the RS and radiomics showed an accuracy of 83% (sensitivity = 81 % and a specificity = 85 % ), outperforming by more than 9% models trained with either spectroscopic or mpMRI data alone. An optimal number of features was identified between 6 and 8 features, which have good potential for discriminating grade group ≥1 / grade group <1 (accuracy = 87 % ) or grade group >1 / grade group ≤1 (accuracy = 91 % ). CONCLUSIONS In-situ Raman spectroscopy combined with mpMRI radiomics features can lead to highly accurate PCa detection for improved in-vivo targeting of biopsy sample collection and radiotherapy seed placement.
Collapse
Affiliation(s)
- David Grajales
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Fabien Picot
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Roozbeh Shams
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Frédérick Dallaire
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Guillaume Sheehy
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Stephanie Alley
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Maroie Barkati
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Guila Delouya
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Jean-Francois Carrier
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Mirela Birlea
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Dominique Trudel
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
- Institut du Cancer de Montréal, Montreal, Québec, Canada
| | - Cynthia Ménard
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| | - Samuel Kadoury
- Polytechnique Montréal, Montreal, Québec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
| |
Collapse
|
5
|
Dossun C, Niederst C, Noel G, Meyer P. Evaluation of DIR algorithm performance in real patients for radiotherapy treatments: A systematic review of operator-dependent strategies. Phys Med 2022; 101:137-157. [PMID: 36007403 DOI: 10.1016/j.ejmp.2022.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 07/21/2022] [Accepted: 08/16/2022] [Indexed: 11/15/2022] Open
Abstract
PURPOSE The performance of deformable medical image registration (DIR) algorithms has become a major concern. METHODS We aimed to obtain updated information on DIR algorithm performance quantification through a literature review of articles published between 2010 and 2022. We focused only on studies using operator-based methods to treat real patients. The PubMed, Google Scholar and Embase databases were searched following PRISMA guidelines. RESULTS One hundred and seven articles were identified. The mean number of patients and registrations per publication was 20 and 63, respectively. We found 23 different geometric metrics appearing at least twice, and the dosimetric impact of DIR was quantified in 32 articles. Forty-eight different at-risk organs were described, and target volumes were studied in 43 publications. Prostate, head-and-neck and thoracic locations represented more than ¾ of the studied locations. We summarized the type of DIR and the images used, and other key elements. Intra/interobserver variability, threshold values and the correlation between metrics were also discussed. CONCLUSIONS This literature review covers the past decade and should facilitate the implementation of DIR algorithms in clinical practice by providing practical and pertinent information to quantify their performance on real patients.
Collapse
Affiliation(s)
- C Dossun
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - C Niederst
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - G Noel
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - P Meyer
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France; ICUBE, CNRS UMR 7357, Team IMAGES, Strasbourg, France.
| |
Collapse
|