1
|
Martin OA, Sykes PJ, Lavin M, Engels E, Martin RF. What's Changed in 75 Years of RadRes? - An Australian Perspective on Selected Topics. Radiat Res 2024; 202:309-327. [PMID: 38966925 DOI: 10.1667/rade-24-00037.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/09/2024] [Indexed: 07/06/2024]
Abstract
Several scientific themes are reviewed in the context of the 75-year period relevant to this special platinum issue of Radiation Research. Two criteria have been considered in selecting the scientific themes. One is the exposure of the associated research activity in the annual meetings of the Radiation Research Society (RRS) and in the publications of the Society's Journal, thus reflecting the interest of members of RRS. The second criteria is a focus on contributions from Australian members of RRS. The first theme is the contribution of radiobiology to radiation oncology, featuring two prominent Australian radiation oncologists, the late Rod Withers and his younger colleague, Lester Peters. Two other themes are also linked to radiation oncology; preclinical research aimed at developing experimental radiotherapy modalities, namely microbeam radiotherapy (MRT) and Auger endoradiotherapy. The latter has a long history, in contrast to MRT, especially in Australia, given that the associated medical beamline at the Australian Synchrotron in Melbourne only opened in 2011. Another theme is DNA repair, which has a trajectory parallel to the 75-year period of interest, given the birth of molecular biology in the 1950s. The low-dose radiobiology theme has a similar timeline, predominantly prompted by the nuclear era, which is also connected to the radioprotector theme, although radioprotectors also have a long-established potential utility in cancer radiotherapy. Finally, two themes are associated with biodosimetry. One is the micronucleus assay, highlighting the pioneering contribution from Michael Fenech in Adelaide, South Australia, and the other is the γ-H2AX assay and its widespread clinical applications.
Collapse
Affiliation(s)
- Olga A Martin
- Centre of Medical Radiation Physics (CMRP), University of Wollongong, Wollongong, NSW, Australia
| | - Pamela J Sykes
- College of Medicine and Public Health, Flinders University and Medical Centre, Bedford Park, SA, Australia
| | - Martin Lavin
- Centre for Clinical Research, University of Queensland, QSL, Brisbane, Australia
| | - Elette Engels
- Centre of Medical Radiation Physics (CMRP), University of Wollongong, Wollongong, NSW, Australia
- Australian Synchrotron, Australian Nuclear Science and Technology Organisation (ANSTO), Clayton, VIC, Australia
| | - Roger F Martin
- School of Chemistry, University of Melbourne, Parkville, VIC, Australia
| |
Collapse
|
2
|
Mid-treatment adaptive planning during thoracic radiation using 68 Ventilation-Perfusion Positron emission tomography. Clin Transl Radiat Oncol 2023; 40:100599. [PMID: 36879654 PMCID: PMC9984948 DOI: 10.1016/j.ctro.2023.100599] [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: 08/21/2022] [Revised: 02/11/2023] [Accepted: 02/12/2023] [Indexed: 02/17/2023] Open
Abstract
Four-Dimensional Gallium 68 Ventilation-Perfusion Positron Emission Tomography (68Ga-4D-V/Q PET/CT) allows for dynamic imaging of lung function. To date there has been no assessment of the feasibility of adapting radiation therapy plans to changes in lung function imaged at mid-treatment function using 68Ga-4D-V/Q PET/CT. This study assessed the potential reductions of dose to the functional lung when radiation therapy plans were adapted to avoid functional lung at the mid-treatment timepoint using volumetric arc radiotherapy (VMAT). Methods A prospective clinical trial (U1111-1138-4421) was performed in patients undergoing conventionally fractionated radiation therapy for non-small cell lung cancer (NSCLC). A 68Ga-4D-V/Q PET/CT was acquired at baseline and in the 4th week of treatment. Functional lung target volumes using the ventilated and perfused lung were created. Baseline functional volumes were compared to the week 4 V/Q functional volumes to describe the change in function over time. For each patient, 3 VMAT plans were created and optimised to spare ventilated, perfused or anatomical lung. All key dosimetry metrics were then compared including dose to target volumes, dose to organs at risk and dose to the anatomical and functional sub-units of lung. Results 25 patients had both baseline and 4 week mid treatment 68Ga-4D-V/Q PET/CT imaging. This resulted in a total of 75 adapted VMAT plans. The HPLung volume decreased in 16/25 patients with a mean of the change in volume (cc) -28 ± 515 cc [±SD, range -996 cc to 1496 cc]. The HVLung volume increased in 13/25 patients with mean of the change in volume (cc) + 112 ± 590 cc. [±SD, range -1424 cc to 950 cc]. The functional lung sparing technique was found to be feasible with no significant differences in dose to anatomically defined organs at risk. Most patients did derive a benefit with a reduction in functional volume receiving 20 Gy (fV20) and/or functional mean lung dose (fMLD) in either perfusion and/or ventilation. Patients with the most reduction in fV20 and fMLD were those with stage III NSCLC. Conclusion Functional lung volumes change during treatment. Some patients benefit from using 68Ga-4D-V/Q PET/CT in the 4th week of radiation therapy to adapt radiation plans. In these patients, the role of mid-treatment adaptation requires further prospective investigation.
Collapse
|
3
|
Xue P, Fu Y, Zhang J, Ma L, Ren M, Zhang Z, Dong E. Effective lung ventilation estimation based on 4D CT image registration and supervoxels. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
|
4
|
Thomas HMT, Hippe DS, Forouzannezhad P, Sasidharan BK, Kinahan PE, Miyaoka RS, Vesselle HJ, Rengan R, Zeng J, Bowen SR. Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics? Discov Oncol 2022; 13:85. [PMID: 36048266 PMCID: PMC9437196 DOI: 10.1007/s12672-022-00548-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/23/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Patients undergoing chemoradiation and immune checkpoint inhibitor (ICI) therapy for locally advanced non-small cell lung cancer (NSCLC) experience pulmonary toxicity at higher rates than historical reports. Identifying biomarkers beyond conventional clinical factors and radiation dosimetry is especially relevant in the modern cancer immunotherapy era. We investigated the role of novel functional lung radiomics, relative to functional lung dosimetry and clinical characteristics, for pneumonitis risk stratification in locally advanced NSCLC. METHODS Patients with locally advanced NSCLC were prospectively enrolled on the FLARE-RT trial (NCT02773238). All received concurrent chemoradiation using functional lung avoidance planning, while approximately half received consolidation durvalumab ICI. Within tumour-subtracted lung regions, 110 radiomics features (size, shape, intensity, texture) were extracted on pre-treatment [99mTc]MAA SPECT/CT perfusion images using fixed-bin-width discretization. The performance of functional lung radiomics for pneumonitis (CTCAE v4 grade 2 or higher) risk stratification was benchmarked against previously reported lung dosimetric parameters and clinical risk factors. Multivariate least absolute shrinkage and selection operator Cox models of time-varying pneumonitis risk were constructed, and prediction performance was evaluated using optimism-adjusted concordance index (c-index) with 95% confidence interval reporting throughout. RESULTS Thirty-nine patients were included in the study and pneumonitis occurred in 16/39 (41%) patients. Among clinical characteristics and anatomic/functional lung dosimetry variables, only the presence of baseline chronic obstructive pulmonary disease (COPD) was significantly associated with the development of pneumonitis (HR 4.59 [1.69-12.49]) and served as the primary prediction benchmark model (c-index 0.69 [0.59-0.80]). Discrimination of time-varying pneumonitis risk was numerically higher when combining COPD with perfused lung radiomics size (c-index 0.77 [0.65-0.88]) or shape feature classes (c-index 0.79 [0.66-0.91]) but did not reach statistical significance compared to benchmark models (p > 0.26). COPD was associated with perfused lung radiomics size features, including patients with larger lung volumes (AUC 0.75 [0.59-0.91]). Perfused lung radiomic texture features were correlated with lung volume (adj R2 = 0.84-1.00), representing surrogates rather than independent predictors of pneumonitis risk. CONCLUSIONS In patients undergoing chemoradiation with functional lung avoidance therapy and optional consolidative immune checkpoint inhibitor therapy for locally advanced NSCLC, the strongest predictor of pneumonitis was the presence of baseline chronic obstructive pulmonary disease. Results from this novel functional lung radiomics exploratory study can inform future validation studies to refine pneumonitis risk models following combinations of radiation and immunotherapy. Our results support functional lung radiomics as surrogates of COPD for non-invasive monitoring during and after treatment. Further study of clinical, dosimetric, and radiomic feature combinations for radiation and immune-mediated pneumonitis risk stratification in a larger patient population is warranted.
Collapse
Affiliation(s)
- Hannah M T Thomas
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
- Department of Radiation Oncology, Christian Medical College Vellore, Vellore, Tamil Nadu, India
| | - Daniel S Hippe
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Parisa Forouzannezhad
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Balu Krishna Sasidharan
- Department of Radiation Oncology, Christian Medical College Vellore, Vellore, Tamil Nadu, India
| | - Paul E Kinahan
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Robert S Miyaoka
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Hubert J Vesselle
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Ramesh Rengan
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Jing Zeng
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Stephen R Bowen
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA.
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
| |
Collapse
|
5
|
Amarasinghe KC, Lopes J, Beraldo J, Kiss N, Bucknell N, Everitt S, Jackson P, Litchfield C, Denehy L, Blyth BJ, Siva S, MacManus M, Ball D, Li J, Hardcastle N. A Deep Learning Model to Automate Skeletal Muscle Area Measurement on Computed Tomography Images. Front Oncol 2021; 11:580806. [PMID: 34026597 PMCID: PMC8138051 DOI: 10.3389/fonc.2021.580806] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 03/22/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Muscle wasting (Sarcopenia) is associated with poor outcomes in cancer patients. Early identification of sarcopenia can facilitate nutritional and exercise intervention. Cross-sectional skeletal muscle (SM) area at the third lumbar vertebra (L3) slice of a computed tomography (CT) image is increasingly used to assess body composition and calculate SM index (SMI), a validated surrogate marker for sarcopenia in cancer. Manual segmentation of SM requires multiple steps, which limits use in routine clinical practice. This project aims to develop an automatic method to segment L3 muscle in CT scans. METHODS Attenuation correction CTs from full body PET-CT scans from patients enrolled in two prospective trials were used. The training set consisted of 66 non-small cell lung cancer (NSCLC) patients who underwent curative intent radiotherapy. An additional 42 NSCLC patients prescribed curative intent chemo-radiotherapy from a second trial were used for testing. Each patient had multiple CT scans taken at different time points prior to and post- treatment (147 CTs in the training and validation set and 116 CTs in the independent testing set). Skeletal muscle at L3 vertebra was manually segmented by two observers, according to the Alberta protocol to serve as ground truth labels. This included 40 images segmented by both observers to measure inter-observer variation. An ensemble of 2.5D fully convolutional neural networks (U-Nets) was used to perform the segmentation. The final layer of U-Net produced the binary classification of the pixels into muscle and non-muscle area. The model performance was calculated using Dice score and absolute percentage error (APE) in skeletal muscle area between manual and automated contours. RESULTS We trained five 2.5D U-Nets using 5-fold cross validation and used them to predict the contours in the testing set. The model achieved a mean Dice score of 0.92 and an APE of 3.1% on the independent testing set. This was similar to inter-observer variation of 0.96 and 2.9% for mean Dice and APE respectively. We further quantified the performance of sarcopenia classification using computer generated skeletal muscle area. To meet a clinical diagnosis of sarcopenia based on Alberta protocol the model achieved a sensitivity of 84% and a specificity of 95%. CONCLUSIONS This work demonstrates an automated method for accurate and reproducible segmentation of skeletal muscle area at L3. This is an efficient tool for large scale or routine computation of skeletal muscle area in cancer patients which may have applications on low quality CTs acquired as part of PET/CT studies for staging and surveillance of patients with cancer.
Collapse
Affiliation(s)
- Kaushalya C. Amarasinghe
- Bioinformatics Core Facility, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
| | - Jamie Lopes
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Julian Beraldo
- Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Nicole Kiss
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, VIC, Australia
- Allied Health Department, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Nicholas Bucknell
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Sarah Everitt
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Price Jackson
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Cassandra Litchfield
- Bioinformatics Core Facility, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Linda Denehy
- Allied Health Department, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Melbourne School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Benjamin J. Blyth
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Shankar Siva
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Michael MacManus
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - David Ball
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
- Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Jason Li
- Bioinformatics Core Facility, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
| | - Nicholas Hardcastle
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| |
Collapse
|
6
|
McIntosh L, Jackson P, Hardcastle N, Bressel M, Kron T, Callahan JW, Steinfort D, Bucknell N, Hofman MS, Siva S. Automated assessment of functional lung imaging with 68Ga-ventilation/perfusion PET/CT using iterative histogram analysis. EJNMMI Phys 2021; 8:23. [PMID: 33677692 PMCID: PMC7937580 DOI: 10.1186/s40658-021-00375-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 02/25/2021] [Indexed: 12/28/2022] Open
Abstract
PURPOSE Functional lung mapping from Ga68-ventilation/perfusion (V/Q) PET/CT, which has been shown to correlate with pulmonary function tests (PFTs), may be beneficial in a number of clinical applications where sparing regions of high lung function is of interest. Regions of clumping in the proximal airways in patients with airways disease can result in areas of focal intense activity and artefact in ventilation imaging. These artefacts may even shine through to subsequent perfusion images and create a challenge for quantitative analysis of PET imaging. We aimed to develop an automated algorithm that interprets the uptake histogram of PET images to calculate a peak uptake value more representative of the global lung volume. METHODS Sixty-six patients recruited from a prospective clinical trial underwent both V/Q PET/CT imaging and PFT analysis before treatment. PET images were normalised using an iterative histogram analysis technique to account for tracer hotspots prior to the threshold-based delineation of varying values. Pearson's correlation between fractional lung function and PFT score was calculated for ventilation, perfusion, and matched imaging volumes at varying threshold values. RESULTS For all functional imaging thresholds, only FEV1/FVC PFT yielded reasonable correlations to image-based functional volume. For ventilation, a range of 10-30% of adapted peak uptake value provided a reasonable threshold to define a volume that correlated with FEV1/FVC (r = 0.54-0.61). For perfusion imaging, a similar correlation was observed (r = 0.51-0.56) in the range of 20-60% adapted peak threshold. Matched volumes were closely linked to ventilation with a threshold range of 15-35% yielding a similar correlation (r = 0.55-0.58). CONCLUSIONS Histogram normalisation may be implemented to determine the presence of tracer clumping hotspots in Ga-68 V/Q PET imaging allowing for automated delineation of functional lung and standardisation of functional volume reporting.
Collapse
Affiliation(s)
- Lachlan McIntosh
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia.
| | - Price Jackson
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia.,Department of Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, 3010, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales, 2522, Australia
| | - Mathias Bressel
- Centre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Tomas Kron
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, 3010, Australia
| | - Jason W Callahan
- Department of Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia
| | - Daniel Steinfort
- Respiratory Medicine, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, Australia
| | - Nicholas Bucknell
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, 3010, Australia.,Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia
| | - Michael S Hofman
- Department of Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, 3010, Australia
| | - Shankar Siva
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, 3010, Australia.,Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, 3000, Australia
| |
Collapse
|
7
|
Le Pennec R, Iravani A, Woon B, Dissaux B, Gest B, Le Floch PY, Salaün PY, Le Gal G, Hofman MS, Hicks RJ, Le Roux PY. Gallium-68 Ventilation/Perfusion PET-CT and CT Pulmonary Angiography for Pulmonary Embolism Diagnosis: An Interobserver Agreement Study. Front Med (Lausanne) 2021; 7:599901. [PMID: 33665194 PMCID: PMC7921798 DOI: 10.3389/fmed.2020.599901] [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: 08/28/2020] [Accepted: 10/06/2020] [Indexed: 11/22/2022] Open
Abstract
Objectives:68Ga Ventilation/Perfusion V/Q PET-CT is a promising imaging tool for pulmonary embolism diagnosis. However, no study has verified whether the interpretation is reproducible between different observers. The aim of this study was to assess the interobserver agreement in the interpretation of V/Q PET-CT for the diagnosis of acute PE, and to compare it to the interobserver agreement of CTPA interpretation. Methods: Twenty-four cancer patients with suspected acute PE underwent V/Q PET-CT and CTPA within 24 h as part of a prospective pilot study evaluating V/Q PET-CT for the management of patients with suspected PE. V/Q PET-CT and CTPA scans were reassessed independently by four nuclear medicine physicians and four radiologists, respectively. Physicians had different levels of expertise in reading V/Q scintigraphy and CTPA. Interpretation was blinded to the initial interpretation and any clinical information or imaging test result. For each modality, results were reported on a binary fashion. V/Q PET/CT scans were read as positive if there was at least one segmental or two subsegmental mismatched perfusion defects. CTPA scans were interpreted as positive if there was a constant intraluminal filling defect. Interobserver agreement was assessed by calculating kappa (κ) coefficients. Results: Out of the 24 V/Q PET-CT scans, the diagnostic conclusion was concordantly negative in 22 patients and concordantly positive in one patient. The remaining scan was interpreted as positive by one reader and negative by three readers. Out of the 24 CTPA scans, the diagnostic conclusion was concordantly negative in 16 and concordantly positive in one. Out of the seven remaining scans, PE was reported by one reader in four cases, by two readers in two cases, by three readers in one case. Most of discordant results on CTPA were related to clots reported on subsegmental arteries. Mean kappa coefficient was 0.79 for V/Q PET-CT interpretation and 0.39 for CTPA interpretation. Conclusions: Interobserver agreement in the interpretation of V/Q PET-CT for PE diagnosis was substantial (kappa 0.79) in a population with a low prevalence of significant PE. Agreement was lower with CTPA, mainly as a result of discrepancies at the level of the subsegmental arteries.
Collapse
Affiliation(s)
- Romain Le Pennec
- Nuclear Medicine, Brest University Hospital, EA3878 (GETBO) IFR 148, Brest, France
| | - Amir Iravani
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Beverley Woon
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Brieg Dissaux
- Radiology, Brest University Hospital, EA3878 (GETBO) IFR 148, Brest, France
| | - Bibiche Gest
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | | | - Pierre-Yves Salaün
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Grégoire Le Gal
- Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Michael S Hofman
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Rodney J Hicks
- Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Pierre-Yves Le Roux
- Nuclear Medicine, Brest University Hospital, EA3878 (GETBO) IFR 148, Brest, France.,Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| |
Collapse
|
8
|
Bucknell N, Hardcastle N, Jackson P, Hofman M, Callahan J, Eu P, Iravani A, Lawrence R, Martin O, Bressel M, Woon B, Blyth B, MacManus M, Byrne K, Steinfort D, Kron T, Hanna G, Ball D, Siva S. Single-arm prospective interventional study assessing feasibility of using gallium-68 ventilation and perfusion PET/CT to avoid functional lung in patients with stage III non-small cell lung cancer. BMJ Open 2020; 10:e042465. [PMID: 33303468 PMCID: PMC7733178 DOI: 10.1136/bmjopen-2020-042465] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND In the curative-intent treatment of locally advanced lung cancer, significant morbidity and mortality can result from thoracic radiation therapy. Symptomatic radiation pneumonitis occurs in one in three patients and can lead to radiation-induced fibrosis. Local failure occurs in one in three patients due to the lungs being a dose-limiting organ, conventionally restricting tumour doses to around 60 Gy. Functional lung imaging using positron emission tomography (PET)/CT provides a geographic map of regional lung function and preclinical studies suggest this enables personalised lung radiotherapy. This map of lung function can be integrated into Volumetric Modulated Arc Therapy (VMAT) radiotherapy planning systems, enabling conformal avoidance of highly functioning regions of lung, thereby facilitating increased doses to tumour while reducing normal tissue doses. METHODS AND ANALYSIS This prospective interventional study will investigate the use of ventilation and perfusion PET/CT to identify highly functioning lung volumes and avoidance of these using VMAT planning. This single-arm trial will be conducted across two large public teaching hospitals in Australia. Twenty patients with stage III non-small cell lung cancer will be recruited. All patients enrolled will receive dose-escalated (69 Gy) functional avoidance radiation therapy. The primary endpoint is feasibility with this achieved if ≥15 out of 20 patients meet pre-defined feasibility criteria. Patients will be followed for 12 months post-treatment with serial imaging, biomarkers, toxicity assessment and quality of life assessment. DISCUSSION Using advanced techniques such as VMAT functionally adapted radiation therapy may enable safe moderate dose escalation with an aim of improving local control and concurrently decreasing treatment related toxicity. If this technique is proven feasible, it will inform the design of a prospective randomised trial to assess the clinical benefits of functional lung avoidance radiation therapy. ETHICS AND DISSEMINATION This study was approved by the Peter MacCallum Human Research Ethics Committee. All participants will provide written informed consent. Results will be disseminated via publications. TRIALS REGISTRATION NUMBER NCT03569072; Pre-results.
Collapse
Affiliation(s)
- Nicholas Bucknell
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales, Australia
| | - Price Jackson
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Michael Hofman
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Jason Callahan
- Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Peter Eu
- Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - Amir Iravani
- Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Department of Nuclear Medicine, Washington University School of Medicine, St Louis, Missouri, USA
| | - Rhonda Lawrence
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Olga Martin
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Mathias Bressel
- Centre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Beverley Woon
- Department of Radiology, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Benjamin Blyth
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael MacManus
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Keelan Byrne
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Daniel Steinfort
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Respiratory Medicine, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Tomas Kron
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Gerard Hanna
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - David Ball
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Shankar Siva
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
9
|
Monitoring DNA Damage and Repair in Peripheral Blood Mononuclear Cells of Lung Cancer Radiotherapy Patients. Cancers (Basel) 2020; 12:cancers12092517. [PMID: 32899789 PMCID: PMC7563254 DOI: 10.3390/cancers12092517] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 08/28/2020] [Accepted: 08/31/2020] [Indexed: 12/23/2022] Open
Abstract
Simple Summary Every patient responds to radiotherapy in individual manner. Some suffer severe side-effects because of normal tissue toxicity. Their radiosensitivity can be caused by inability of DNA repair system to fix radiation-induced damage. The γ-H2AX assay can detect such deficiency in untransformed primary cells (e.g., peripheral blood mononuclear cells, PBMC), over a period of only hours post ex-vivo irradiation. Earlier we have shown that the level and kinetics of decline (repair) of radiation-induced DNA damage detected by the assay is a measure of the cellular radiosensitivity. In this study, we applied the γ-H2AX assay to judge the radiosensitivity of lung cancer radiotherapy patients as normal or abnormal, based on kinetics of DNA damage repair. Considering the potential of the assay as a clinical biodosimeter, we also monitored DNA damage in serial samples of PBMC during the course of radiotherapy. This study opens an opportunity to monitor individual response to radiotherapy treatment. Abstract Thoracic radiotherapy (RT) is required for the curative management of inoperable lung cancer, however, treatment delivery is limited by normal tissue toxicity. Prior studies suggest that using radiation-induced DNA damage response (DDR) in peripheral blood mononuclear cells (PBMC) has potential to predict RT-associated toxicities. We collected PBMC from 38 patients enrolled on a prospective clinical trial who received definitive fractionated RT for non-small cell lung cancer. DDR was measured by automated counting of nuclear γ-H2AX foci in immunofluorescence images. Analysis of samples collected before, during and after RT demonstrated the induction of DNA damage in PBMC collected shortly after RT commenced, however, this damage repaired later. Radiation dose to the tumour and lung contributed to the in vivo induction of γ-H2AX foci. Aliquots of PBMC collected before treatment were also irradiated ex vivo, and γ-H2AX kinetics were analyzed. A trend for increasing of fraction of irreparable DNA damage in patients with higher toxicity grades was revealed. Slow DNA repair in three patients was associated with a combined dysphagia/cough toxicity and was confirmed by elevated in vivo RT-generated irreparable DNA damage. These results warrant inclusion of an assessment of DDR in PBMC in a panel of predictive biomarkers that would identify patients at a higher risk of toxicity.
Collapse
|
10
|
Mounessi FS, Eckardt J, Holstein A, Ewig S, Könemann S. Image-based lung functional radiotherapy planning for non-small cell lung cancer. Strahlenther Onkol 2019; 196:151-158. [DOI: 10.1007/s00066-019-01518-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 09/10/2019] [Indexed: 12/25/2022]
|
11
|
Iravani A, Turgeon GA, Akhurst T, Callahan JW, Bressel M, Everitt SJ, Siva S, Hofman MS, Hicks RJ, Ball DL, Mac Manus MP. PET-detected pneumonitis following curative-intent chemoradiation in non-small cell lung cancer (NSCLC): recognizing patterns and assessing the impact on the predictive ability of FDG-PET/CT response assessment. Eur J Nucl Med Mol Imaging 2019; 46:1869-1877. [PMID: 31190177 DOI: 10.1007/s00259-019-04388-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Accepted: 05/31/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE Inflammatory FDG uptake in the lung (PET-pneumonitis) following curative-intent radiotherapy (RT)/chemo-RT (CRT) in non-small cell lung cancer (NSCLC) can pose a challenge in FDG-PET/CT response assessment. The aim of this study is to describe different patterns of PET-pneumonitis to guide the interpretation of FDG-PET/CT and investigate its association with tumor response and overall survival (OS). METHODS Retrospective analysis was performed on 87 NSCLC patients in three prospective trials who were treated with radical RT (n = 7) or CRT (n = 80), with baseline and post-treatment FDG-PET/CT. Visual criteria were performed for post-treatment FDG-PET/CT response assessment. The grading of PET-pneumonitis was based on relative lung uptake intensity compared to organs of reference and classified as per Deauville score from grade 1-5. Distribution patterns of PET-pneumonitis were defined as follows: A) patchy/sub-pleural; B) diffuse (involving more than a segment); and C) peripheral (diffusely surrounding a photopenic region). RESULTS Follow-up FDG-PET/CT scans were performed approximately 3 months (median, 89 days; interquartile range, 79-93) after RT. Overall, PET-pneumonitis was present in 62/87 (71%) of patients, with Deauville 2 or 3 in 12/62 (19%) and 4 or 5 in 50/62 (81%) of patients. The frequency of patterns A, B and C of PET-pneumonitis was 19/62 (31%), 20/62 (32%) and 23/62 (37%), respectively. No association was found between grade or pattern of PET-pneumonitis and overall response at follow-up PET/CT (p = 0.27 and p = 0.56, respectively). There was also no significant association between PET-pneumonitis and OS (hazard ratio [HR], 1.3; 95% confidence interval [CI], 0.6-2.5; p = 0.45). Early FDG-PET/CT response assessment, however, was prognostic for OS (HR, 1.7; 95% CI, 1.2-2.2; p < 0.001). CONCLUSION PET-pneumonitis is common in early post-CRT/RT, but pattern recognition may assist in response assessment by FDG-PET/CT. While FDG-PET/CT is a powerful tool for response assessment and prognostication, PET-pneumonitis does not appear to confound early response assessment or to independently predict OS.
Collapse
Affiliation(s)
- Amir Iravani
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia. .,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.
| | - Guy-Anne Turgeon
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Tim Akhurst
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia
| | - Jason W Callahan
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia
| | - Mathias Bressel
- Department of Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Sarah J Everitt
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Department of Medical Imaging and Radiation Sciences, Faculty of Medicine and Dentistry, Monash University, Clayton, VIC, Australia
| | - Shankar Siva
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Michael S Hofman
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia
| | - Rodney J Hicks
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - David L Ball
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Michael P Mac Manus
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| |
Collapse
|
12
|
Kipritidis J, Tahir BA, Cazoulat G, Hofman MS, Siva S, Callahan J, Hardcastle N, Yamamoto T, Christensen GE, Reinhardt JM, Kadoya N, Patton TJ, Gerard SE, Duarte I, Archibald-Heeren B, Byrne M, Sims R, Ramsay S, Booth JT, Eslick E, Hegi-Johnson F, Woodruff HC, Ireland RH, Wild JM, Cai J, Bayouth JE, Brock K, Keall PJ. The VAMPIRE challenge: A multi-institutional validation study of CT ventilation imaging. Med Phys 2019; 46:1198-1217. [PMID: 30575051 DOI: 10.1002/mp.13346] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 11/18/2018] [Accepted: 11/23/2018] [Indexed: 01/31/2023] Open
Abstract
PURPOSE CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities. METHODS The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA-SPECT, and 4 sheep imaged with Xenon-CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B-splines, Free-form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel-wise Spearman coefficient r S , and Dice similarity coefficients evaluated for low function lung ( DSC low ) and high function lung ( DSC high ). RESULTS A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant-submitted DIR motion fields using the in-house software, VESPIR. The r S and DSC results reveal a high degree of inter-algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross-modality correlations used a biomechanical model-based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27-0.73) for r S , 0.52 (0.36-0.67) for DSC low , and 0.45 (0.28-0.62) for DSC high . All other algorithms exhibited at least one negative r S value, and/or one DSC value less than 0.5. CONCLUSIONS The VAMPIRE Challenge results demonstrate that the cross-modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a "gold standard," highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic centers to the clinic. It is hoped that the information gleaned from the VAMPIRE Challenge can help inform future validation efforts.
Collapse
Affiliation(s)
- John Kipritidis
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.,Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Bilal A Tahir
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK.,Academic Radiology, POLARIS, University of Sheffield, Sheffield, UK
| | - Guillaume Cazoulat
- The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA
| | | | - Shankar Siva
- Peter MacCallum Cancer Centre, Melbourne, Vic., Australia
| | - Jason Callahan
- Peter MacCallum Cancer Centre, Melbourne, Vic., Australia
| | | | - Tokihiro Yamamoto
- University of California Davis School of Medicine, Sacramento, CA, USA
| | | | | | - Noriyuki Kadoya
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | | | | | | | - Ben Archibald-Heeren
- Radiation Oncology Centres, Sydney Adventist Hospital, Sydney, NSW, Australia.,University of Wollongong, Wollongong, NSW, Australia
| | - Mikel Byrne
- Radiation Oncology Centres, Sydney Adventist Hospital, Sydney, NSW, Australia
| | - Rick Sims
- Auckland Radiation Oncology, Auckland, New Zealand
| | - Scott Ramsay
- Auckland Radiation Oncology, Auckland, New Zealand
| | - Jeremy T Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.,School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Enid Eslick
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.,Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Fiona Hegi-Johnson
- Sydney Medical School, University of Sydney, Sydney, NSW, Australia.,Peter MacCallum Cancer Centre, Melbourne, Vic., Australia
| | - Henry C Woodruff
- The D-Lab: Decision Support for Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Rob H Ireland
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK
| | - Jim M Wild
- Academic Radiology, POLARIS, University of Sheffield, Sheffield, UK
| | - Jing Cai
- Duke University Medical Center, Durham, NC, USA.,Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | | | - Kristy Brock
- The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA
| | - Paul J Keall
- Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| |
Collapse
|
13
|
Le Roux PY, Hicks RJ, Siva S, Hofman MS. PET/CT Lung Ventilation and Perfusion Scanning using Galligas and Gallium-68-MAA. Semin Nucl Med 2019; 49:71-81. [DOI: 10.1053/j.semnuclmed.2018.10.013] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
|
14
|
Functional lung imaging in radiation therapy for lung cancer: A systematic review and meta-analysis. Radiother Oncol 2018; 129:196-208. [PMID: 30082143 DOI: 10.1016/j.radonc.2018.07.014] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 06/14/2018] [Accepted: 07/18/2018] [Indexed: 12/25/2022]
Abstract
RATIONALE Advanced imaging techniques allow functional information to be derived and integrated into treatment planning. METHODS A systematic review was conducted with the primary objective to evaluate the ability of functional lung imaging to predict risk of radiation pneumonitis. Secondary objectives were to evaluate dose-response relationships on post treatment functional imaging and assess the utility in including functional lung information into treatment planning. A structured search for publications was performed following PRISMA guidelines and registered on PROSPERO. RESULTS 814 articles were screened against review criteria and 114 publications met criteria. Methods of identifying functional lung included using CT, MRI, SPECT and PET to image ventilation or perfusion. Six studies compared differences between functional and anatomical lung imaging at predicting radiation pneumonitis. These found higher predictive values using functional lung imaging. Twenty-one studies identified a dose-response relationship on post-treatment functional lung imaging. Nineteen planning studies demonstrated the ability of functional lung optimised planning techniques to spare regions of functional lung. Meta-analysis of these studies found that mean (95% CI) functional volume receiving 20 Gy was reduced by 4.2% [95% CI: 2.3: 6.0] and mean lung dose by 2.2 Gy [95% CI: 1.2: 3.3] when plans were optimised to spare functional lung. There was significant variation between publications in the definition of functional lung. CONCLUSION Functional lung imaging may have potential utility in radiation therapy planning and delivery, although significant heterogeneity was identified in approaches and reporting. Recommendations have been made based on the available evidence for future functional lung trials.
Collapse
|
15
|
Wu M, Huang T, Wang J, Chen P, Mi W, Ying Y, Wang H, Zhao D, Huang S. Antilung cancer effect of ergosterol and cisplatin-loaded liposomes modified with cyclic arginine-glycine-aspartic acid and octa-arginine peptides. Medicine (Baltimore) 2018; 97:e11916. [PMID: 30113492 PMCID: PMC6113040 DOI: 10.1097/md.0000000000011916] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 07/20/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Lung cancer is one of the most important diseases threatening human health, and targeted therapy has become the main research direction. This work, therefore, aimed to develop cyclic arginine-glycine-aspartic (RGD) and octa-arginine (R8) peptide-modified ergosterol (ERG)-combined cisplatin (diamminedichloridoplatinum(II) [DDP]) liposomes (LIP) as a drug delivery system. METHODS Soybean phospholipids (SPC) and cholesterol (Chol) were selected to prepare different LIPs: ERG-loaded LIP (ERG-LIP), DDP and ERG-LIP (DDP/ERG-LIP), R8 peptide-modified DDP and ERG-LIP (R8-DDP/ERG-LIP), and cyclic RGD and R8-DDP/ERG-LIP (RGD/R8-DDP/ERG-LIP). The quality, tumor sphere penetrating ability, in vitro cellular uptake, mechanism of cellular uptake, and in vitro cytotoxicity of RGD/R8-DDP/ERG-LIP were evaluated. RESULTS The LIP quality evaluation revealed that RGD/R8-DDP/ERG-LIP is round with a double-layer structure. The average particle size, dispersion coefficient of the polydispersity index (PDI), and zeta potential of RGD/R8-DDP/ERG-LIP were 155.2 ± 8.7 nm, 0.102, and 4.74 ± 0.7 mV, respectively. Furthermore, the LIPs were stable in the serum, and obviously inhibited the growth of A549 lung cancer cells with RGD/R8-DDP/ERG-LIP exhibiting the strongest inhibitory effect. The highest cellular uptake rate, which was at 4 hours, was exhibited by RGD/R8-DDP/ERG-LIP in a concentration-dependent manner. CONCLUSION The results showed that LIP uptake by A549 cells was mainly by the clathrin-mediated endocytosis pathway (chlorpromazine). The results also suggest that RGD/R8-DDP/ERG-LIP might be a promising drug delivery system to improve antilung cancer drug effect and tumor-targeting in vitro.
Collapse
Affiliation(s)
- Meijia Wu
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Ting Huang
- General Surgical Department, Hangzhou Red Cross Hospital
| | - Juan Wang
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Ping Chen
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Wanwan Mi
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Yuanyuan Ying
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Hangli Wang
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| | - Dandan Zhao
- Pharmacy Department, Hangzhou Zhongxing Hospital, Hangzhou, Zhejiang, China
| | - Shengwu Huang
- College of Pharmaceutical Science, Zhejiang Chinese Medical University
| |
Collapse
|
16
|
Turgeon GA, Iravani A, Akhurst T, Beaulieu A, Callahan JW, Bressel M, Cole AJ, Everitt SJ, Siva S, Hicks RJ, Ball DL, Mac Manus MP. What 18F-FDG PET Response-Assessment Method Best Predicts Survival After Curative-Intent Chemoradiation in Non-Small Cell Lung Cancer: EORTC, PERCIST, Peter Mac Criteria, or Deauville Criteria? J Nucl Med 2018; 60:328-334. [PMID: 30030343 DOI: 10.2967/jnumed.118.214148] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 07/09/2018] [Indexed: 12/17/2022] Open
Abstract
The optimal methodology for defining response with 18F-FDG PET after curative-intent chemoradiation for non-small cell lung cancer (NSCLC) is unknown. We compared survival outcomes according to the criteria of the European Organization for Research and Treatment of Cancer (EORTC), PERCIST 1.0, the Peter Mac metabolic visual criteria, and the Deauville criteria, respectively. Methods: Three prospective trials of chemoradiation for NSCLC, involving baseline and posttreatment 18F-FDG PET/CT imaging, were conducted between 2004 and 2016. Responses were categorized as complete metabolic response (CMR), partial metabolic response, stable metabolic disease, or progressive metabolic disease. Cox proportional-hazards models and log-rank tests assessed the impact of each response on overall survival (OS). Results: Eighty-seven patients underwent 18F-FDG PET/CT before and after radical chemoradiation for NSCLC. Follow-up 18F-FDG PET/CT scans were performed at a median of 89 d (interquartile range, 79-93 d) after radiotherapy. Median follow-up and OS after PET response imaging were 49 and 28 mo, respectively. Interobserver agreements for EORTC, PERCIST, Peter Mac, and Deauville had κ values of 0.76, 0.76, 0.87, and 0.84, respectively. All 4 response criteria were significantly associated with OS. Peter Mac and Deauville showed better fit than EORTC and PERCIST and distinguished better between CMR and non-CMR. Conclusion: All 4 response criteria were highly predictive of OS, but visual criteria showed greater interobserver agreement and stronger discrimination between CMR and non-CMR, highlighting the importance of visual assessment to recognize radiation pneumonitis, changes in lung configuration, and patterns of response.
Collapse
Affiliation(s)
- Guy-Anne Turgeon
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Amir Iravani
- Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Tim Akhurst
- Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Alexis Beaulieu
- Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Jason W Callahan
- Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Mathias Bressel
- Department of Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Aidan J Cole
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Centre for Cancer Research and Cell Biology, Queen's University, Belfast, Northern Ireland
| | - Sarah J Everitt
- Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; and.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Shankar Siva
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Rodney J Hicks
- Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - David L Ball
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael P Mac Manus
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
17
|
|
18
|
Le Roux PY, Siva S, Callahan J, Claudic Y, Bourhis D, Steinfort DP, Hicks RJ, Hofman MS. Automatic delineation of functional lung volumes with 68Ga-ventilation/perfusion PET/CT. EJNMMI Res 2017; 7:82. [PMID: 29019109 PMCID: PMC5634989 DOI: 10.1186/s13550-017-0332-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 10/06/2017] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Functional volumes computed from 68Ga-ventilation/perfusion (V/Q) PET/CT, which we have shown to correlate with pulmonary function test parameters (PFTs), have potential diagnostic utility in a variety of clinical applications, including radiotherapy planning. An automatic segmentation method would facilitate delineation of such volumes. The aim of this study was to develop an automated threshold-based approach to delineate functional volumes that best correlates with manual delineation. Thirty lung cancer patients undergoing both V/Q PET/CT and PFTs were analyzed. Images were acquired following inhalation of Galligas and, subsequently, intravenous administration of 68Ga-macroaggreted-albumin (MAA). Using visually defined manual contours as the reference standard, various cutoff values, expressed as a percentage of the maximal pixel value, were applied. The average volume difference and Dice similarity coefficient (DSC) were calculated, measuring the similarity of the automatic segmentation and the reference standard. Pearson's correlation was also calculated to compare automated volumes with manual volumes, and automated volumes optimized to PFT indices. RESULTS For ventilation volumes, mean volume difference was lowest (- 0.4%) using a 15%max threshold with Pearson's coefficient of 0.71. Applying this cutoff, median DSC was 0.93 (0.87-0.95). Nevertheless, limits of agreement in volume differences were large (- 31.0 and 30.2%) with differences ranging from - 40.4 to + 33.0%. For perfusion volumes, mean volume difference was lowest and Pearson's coefficient was highest using a 15%max threshold (3.3% and 0.81, respectively). Applying this cutoff, median DSC was 0.93 (0.88-0.93). Nevertheless, limits of agreement were again large (- 21.1 and 27.8%) with volume differences ranging from - 18.6 to + 35.5%. Using the 15%max threshold, moderate correlation was demonstrated with FEV1/FVC (r = 0.48 and r = 0.46 for ventilation and perfusion images, respectively). No correlation was found between other PFT indices. CONCLUSIONS To automatically delineate functional volumes with 68Ga-V/Q PET/CT, the most appropriate cutoff was 15%max for both ventilation and perfusion images. However, using this unique threshold systematically provided unacceptable variability compared to the reference volume and relatively poor correlation with PFT parameters. Accordingly, a visually adapted semi-automatic method is favored, enabling rapid and quantitative delineation of lung functional volumes with 68Ga-V/Q PET/CT.
Collapse
Affiliation(s)
- Pierre-Yves Le Roux
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, 3000, Australia. .,Nuclear Medicine Department, Brest University Hospital, EA3878 (GETBO) IFR, 148, Brest, France. .,Service de médecine nucléaire, CHRU de Brest, 29609, Brest CEDEX, France.
| | - Shankar Siva
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, 3000, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia
| | - Jason Callahan
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, 3000, Australia
| | - Yannis Claudic
- Nuclear Medicine Department, Brest University Hospital, EA3878 (GETBO) IFR, 148, Brest, France
| | - David Bourhis
- Nuclear Medicine Department, Brest University Hospital, EA3878 (GETBO) IFR, 148, Brest, France
| | - Daniel P Steinfort
- Respiratory Medicine, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, Australia
| | - Rodney J Hicks
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, 3000, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia
| | - Michael S Hofman
- Cancer Imaging, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, 3000, Australia. .,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia.
| |
Collapse
|
19
|
Doganay O, Stirrat E, McKenzie C, Schulte RF, Santyr GE. Quantification of regional early stage gas exchange changes using hyperpolarized (129)Xe MRI in a rat model of radiation-induced lung injury. Med Phys 2017; 43:2410. [PMID: 27147352 DOI: 10.1118/1.4946818] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To assess the feasibility of hyperpolarized (HP) (129)Xe MRI for detection of early stage radiation-induced lung injury (RILI) in a rat model involving unilateral irradiation by assessing differences in gas exchange dynamics between irradiated and unirradiated lungs. METHODS The dynamics of gas exchange between alveolar air space and pulmonary tissue (PT), PT and red blood cells (RBCs) was measured using single-shot spiral iterative decomposition of water and fat with echo asymmetry and least-squares estimation images of the right and left lungs of two age-matched cohorts of Sprague Dawley rats. The first cohort (n = 5) received 18 Gy irradiation to the right lung using a (60)Co source and the second cohort (n = 5) was not irradiated and served as the healthy control. Both groups were imaged two weeks following irradiation when radiation pneumonitis (RP) was expected to be present. The gas exchange data were fit to a theoretical gas exchange model to extract measurements of pulmonary tissue thickness (LPT) and relative blood volume (VRBC) from each of the right and left lungs of both cohorts. Following imaging, lung specimens were retrieved and percent tissue area (PTA) was assessed histologically to confirm RP and correlate with MRI measurements. RESULTS Statistically significant differences in LPT and VRBC were observed between the irradiated and non-irradiated cohorts. In particular, LPT of the right and left lungs was increased approximately 8.2% and 5.0% respectively in the irradiated cohort. Additionally, VRBC of the right and left lungs was decreased approximately 36.1% and 11.7% respectively for the irradiated cohort compared to the non-irradiated cohort. PTA measurements in both right and left lungs were increased in the irradiated group compared to the non-irradiated cohort for both the left (P < 0.05) and right lungs (P < 0.01) confirming the presence of RP. PTA measurements also correlated with the MRI measurements for both the non-irradiated (r = 0.79, P < 0.01) and irradiated groups (r = 0.91, P < 0.01). CONCLUSIONS Regional RILI can be detected two weeks post-irradiation using HP (129)Xe MRI and analysis of gas exchange curves. This approach correlates well with histology and can potentially be used clinically to assess radiation pneumonitis associated with early RILI to improve radiation therapy outcomes.
Collapse
Affiliation(s)
- Ozkan Doganay
- Department of Medical Biophysics, Western University, London, Ontario N6A5C1, Canada; Imaging Research Laboratories, Robarts Research Institute, London, Ontario N6A5C1, Canada; and Department of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, United Kingdom
| | - Elaine Stirrat
- Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G1X8, Canada
| | - Charles McKenzie
- Department of Medical Biophysics, Western University, London, Ontario N6A5C1, Canada and Imaging Research Laboratories, Robarts Research Institute, London, Ontario N6A5C1, Canada
| | | | - Giles E Santyr
- Department of Medical Biophysics, Western University, London, Ontario N6A5C1, Canada; Imaging Research Laboratories, Robarts Research Institute, London, Ontario N6A5C1, Canada; Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G1X8, Canada; and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G1L7, Canada
| |
Collapse
|
20
|
Matuszak MM, Matrosic C, Jarema D, McShan DL, Stenmark MH, Owen D, Jolly S, Kong FMS, Ten Haken RK. Priority-driven plan optimization in locally advanced lung patients based on perfusion SPECT imaging. Adv Radiat Oncol 2016; 1:281-289. [PMID: 28740898 PMCID: PMC5514230 DOI: 10.1016/j.adro.2016.10.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Revised: 10/13/2016] [Accepted: 10/24/2016] [Indexed: 12/25/2022] Open
Abstract
Purpose Limits on mean lung dose (MLD) allow for individualization of radiation doses at safe levels for patients with lung tumors. However, MLD does not account for individual differences in the extent or spatial distribution of pulmonary dysfunction among patients, which leads to toxicity variability at the same MLD. We investigated dose rearrangement to minimize the radiation dose to the functional lung as assessed by perfusion single photon emission computed tomography (SPECT) and maximize the target coverage to maintain conventional normal tissue limits. Methods and materials Retrospective plans were optimized for 15 patients with locally advanced non-small cell lung cancer who were enrolled in a prospective imaging trial. A staged, priority-based optimization system was used. The baseline priorities were to meet physical MLD and other dose constraints for organs at risk, and to maximize the target generalized equivalent uniform dose (gEUD). To determine the benefit of dose rearrangement with perfusion SPECT, plans were reoptimized to minimize the generalized equivalent uniform functional dose (gEUfD) to the lung as the subsequent priority. Results When only physical MLD is minimized, lung gEUfD was 12.6 ± 4.9 Gy (6.3-21.7 Gy). When the dose is rearranged to minimize gEUfD directly in the optimization objective function, 10 of 15 cases showed a decrease in lung gEUfD of >20% (lung gEUfD mean 9.9 ± 4.3 Gy, range 2.1-16.2 Gy) while maintaining equivalent planning target volume coverage. Although all dose-limiting constraints remained unviolated, the dose rearrangement resulted in slight gEUD increases to the cord (5.4 ± 3.9 Gy), esophagus (3.0 ± 3.7 Gy), and heart (2.3 ± 2.6 Gy). Conclusions Priority-driven optimization in conjunction with perfusion SPECT permits image guided spatial dose redistribution within the lung and allows for a reduced dose to the functional lung without compromising target coverage or exceeding conventional limits for organs at risk.
Collapse
Affiliation(s)
- Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.,Department of Nuclear Engineering & Radiological Sciences, University of Michigan, Ann Arbor, Michigan
| | - Charles Matrosic
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.,Department of Nuclear Engineering & Radiological Sciences, University of Michigan, Ann Arbor, Michigan
| | - David Jarema
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Daniel L McShan
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew H Stenmark
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Dawn Owen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| |
Collapse
|
21
|
Kipritidis J, Hofman MS, Siva S, Callahan J, Le Roux PY, Woodruff HC, Counter WB, Keall PJ. Estimating lung ventilation directly from 4D CT Hounsfield unit values. Med Phys 2015; 43:33. [DOI: 10.1118/1.4937599] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
|
22
|
Schembri GP, Roach PJ, Bailey DL, Freeman L. Artifacts and Anatomical Variants Affecting Ventilation and Perfusion Lung Imaging. Semin Nucl Med 2015; 45:373-91. [DOI: 10.1053/j.semnuclmed.2015.02.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
|
23
|
Hardcastle N, Hofman MS, Hicks RJ, Callahan J, Kron T, MacManus MP, Ball DL, Jackson P, Siva S. Accuracy and Utility of Deformable Image Registration in (68)Ga 4D PET/CT Assessment of Pulmonary Perfusion Changes During and After Lung Radiation Therapy. Int J Radiat Oncol Biol Phys 2015; 93:196-204. [PMID: 26279034 DOI: 10.1016/j.ijrobp.2015.05.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2014] [Revised: 04/29/2015] [Accepted: 05/08/2015] [Indexed: 11/28/2022]
Abstract
PURPOSE Measuring changes in lung perfusion resulting from radiation therapy dose requires registration of the functional imaging to the radiation therapy treatment planning scan. This study investigates registration accuracy and utility for positron emission tomography (PET)/computed tomography (CT) perfusion imaging in radiation therapy for non-small cell lung cancer. METHODS (68)Ga 4-dimensional PET/CT ventilation-perfusion imaging was performed before, during, and after radiation therapy for 5 patients. Rigid registration and deformable image registration (DIR) using B-splines and Demons algorithms was performed with the CT data to obtain a deformation map between the functional images and planning CT. Contour propagation accuracy and correspondence of anatomic features were used to assess registration accuracy. Wilcoxon signed-rank test was used to determine statistical significance. Changes in lung perfusion resulting from radiation therapy dose were calculated for each registration method for each patient and averaged over all patients. RESULTS With B-splines/Demons DIR, median distance to agreement between lung contours reduced modestly by 0.9/1.1 mm, 1.3/1.6 mm, and 1.3/1.6 mm for pretreatment, midtreatment, and posttreatment (P < .01 for all), and median Dice score between lung contours improved by 0.04/0.04, 0.05/0.05, and 0.05/0.05 for pretreatment, midtreatment, and posttreatment (P < .001 for all). Distance between anatomic features reduced with DIR by median 2.5 mm and 2.8 for pretreatment and midtreatment time points, respectively (P = .001) and 1.4 mm for posttreatment (P > .2). Poorer posttreatment results were likely caused by posttreatment pneumonitis and tumor regression. Up to 80% standardized uptake value loss in perfusion scans was observed. There was limited change in the loss in lung perfusion between registration methods; however, Demons resulted in larger interpatient variation compared with rigid and B-splines registration. CONCLUSIONS DIR accuracy in the data sets studied was variable depending on anatomic changes resulting from radiation therapy; caution must be exercised when using DIR in regions of low contrast or radiation pneumonitis. Lung perfusion reduces with increasing radiation therapy dose; however, DIR did not translate into significant changes in dose-response assessment.
Collapse
Affiliation(s)
- Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, East Melbourne, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.
| | - Michael S Hofman
- Molecular Imaging, Centre for Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Rodney J Hicks
- Molecular Imaging, Centre for Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia; Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Jason Callahan
- Molecular Imaging, Centre for Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Tomas Kron
- Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Australia; The Sir Peter MacCallum Department of Oncology, Melbourne University, Victoria, Australia
| | - Michael P MacManus
- Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia; The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - David L Ball
- Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia; The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Price Jackson
- Department of Physical Sciences, Peter MacCallum Cancer Centre, East Melbourne, Australia
| | - Shankar Siva
- Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia
| |
Collapse
|
24
|
Siva S, Thomas R, Callahan J, Hardcastle N, Pham D, Kron T, Hicks RJ, MacManus MP, Ball DL, Hofman MS. High-resolution pulmonary ventilation and perfusion PET/CT allows for functionally adapted intensity modulated radiotherapy in lung cancer. Radiother Oncol 2015; 115:157-62. [PMID: 25935743 DOI: 10.1016/j.radonc.2015.04.013] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Revised: 04/12/2015] [Accepted: 04/19/2015] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND PURPOSE To assess the utility of functional lung avoidance using IMRT informed by four-dimensional (4D) ventilation/perfusion (V/Q) PET/CT. MATERIALS AND METHODS In a prospective clinical trial, patients with non-small cell lung cancer (NSCLC) underwent 4D-V/Q PET/CT scanning before 60Gy of definitive chemoradiation. Both "highly perfused" (HPLung) and "highly ventilated" (HVLung) lung volumes were delineated using a 70th centile SUV threshold, and a "ventilated lung volume" (VLung) was created using a 50th centile SUV threshold. For each patient four IMRT plans were created, optimised to the anatomical lung, HPLung, HVLung and VLung volumes, respectively. Improvements in functional dose volumetrics when optimising to functional volumes were assessed using mean lung dose (MLD), V5, V10, V20, V30, V40, V50 and V60 parameters. RESULTS The study cohort consisted of 20 patients with 80 IMRT plans. Plans optimised to HPLung resulted in a significant reduction of functional MLD by a mean of 13.0% (1.7Gy), p=0.02. Functional V5, V10 and V20 were improved by 13.2%, 7.3% and 3.8% respectively (p-values<0.04). There was no significant sparing of dose to functional lung when adapting to VLung or HVLung. Plan quality was highly consistent with a mean PTV D95 and D5 ranging from 60.8Gy to 61.0Gy and 63.4Gy to 64.5Gy, respectively, and mean conformity and heterogeneity index ranging from 1.11 to 1.17 and 0.94 to 0.95, respectively. CONCLUSION IMRT plans adapted to perfused but not ventilated lung on 4D-V/Q PET/CT allowed for reduced dose to functional lung whilst maintaining consistent plan quality.
Collapse
Affiliation(s)
- Shankar Siva
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Australia
| | - Roshini Thomas
- Department of Radiotherapy Services, Peter MacCallum Cancer Centre, Australia
| | - Jason Callahan
- Centre for Molecular Imaging, Peter MacCallum Cancer Centre, Australia
| | | | - Daniel Pham
- Department of Radiotherapy Services, Peter MacCallum Cancer Centre, Australia
| | - Tomas Kron
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Department of Physical Sciences, Peter MacCallum Cancer Centre, Australia
| | - Rodney J Hicks
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Centre for Molecular Imaging, Peter MacCallum Cancer Centre, Australia
| | - Michael P MacManus
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Australia
| | - David L Ball
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Australia
| | - Michael S Hofman
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia; Centre for Molecular Imaging, Peter MacCallum Cancer Centre, Australia
| |
Collapse
|