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Chandy E, Szmul A, Stavropoulou A, Jacob J, Veiga C, Landau D, Wilson J, Gulliford S, Fenwick JD, Hawkins MA, Hiley C, McClelland JR. Quantitative Analysis of Radiation-Associated Parenchymal Lung Change. Cancers (Basel) 2022; 14:946. [PMID: 35205693 PMCID: PMC8870325 DOI: 10.3390/cancers14040946] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 02/07/2022] [Accepted: 02/08/2022] [Indexed: 02/01/2023] Open
Abstract
We present a novel classification system of the parenchymal features of radiation-induced lung damage (RILD). We developed a deep learning network to automate the delineation of five classes of parenchymal textures. We quantify the volumetric change in classes after radiotherapy in order to allow detailed, quantitative descriptions of the evolution of lung parenchyma up to 24 months after RT, and correlate these with radiotherapy dose and respiratory outcomes. Diagnostic CTs were available pre-RT, and at 3, 6, 12 and 24 months post-RT, for 46 subjects enrolled in a clinical trial of chemoradiotherapy for non-small cell lung cancer. All 230 CT scans were segmented using our network. The five parenchymal classes showed distinct temporal patterns. Moderate correlation was seen between change in tissue class volume and clinical and dosimetric parameters, e.g., the Pearson correlation coefficient was ≤0.49 between V30 and change in Class 2, and was 0.39 between change in Class 1 and decline in FVC. The effect of the local dose on tissue class revealed a strong dose-dependent relationship. Respiratory function measured by spirometry and MRC dyspnoea scores after radiotherapy correlated with the measured radiological RILD. We demonstrate the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible.
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Affiliation(s)
- Edward Chandy
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; (D.L.); (C.H.)
- Sussex Cancer Centre, Royal Sussex County Hospital, Brighton BN2 5BE, UK
| | - Adam Szmul
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
| | - Alkisti Stavropoulou
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
| | - Joseph Jacob
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
- UCL Respiratory Department, University College London Hospital, London NW1 2PG, UK
| | - Catarina Veiga
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
| | - David Landau
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; (D.L.); (C.H.)
| | - James Wilson
- Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (J.W.); (S.G.); (M.A.H.)
| | - Sarah Gulliford
- Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (J.W.); (S.G.); (M.A.H.)
| | - John D. Fenwick
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3GE, UK;
| | - Maria A. Hawkins
- Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (J.W.); (S.G.); (M.A.H.)
| | - Crispin Hiley
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; (D.L.); (C.H.)
| | - Jamie R. McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; (A.S.); (A.S.); (J.J.); (C.V.); (J.R.M.)
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Veiga C, Chandy E, Jacob J, Yip N, Szmul A, Landau D, McClelland JR. Investigation of the evolution of radiation-induced lung damage using serial CT imaging and pulmonary function tests. Radiother Oncol 2020; 148:89-96. [PMID: 32344262 PMCID: PMC7416106 DOI: 10.1016/j.radonc.2020.03.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 03/20/2020] [Accepted: 03/22/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE Radiation-induced lung damage (RILD) is a common consequence of lung cancer radiotherapy (RT) with unclear evolution over time. We quantify radiological RILD longitudinally and correlate it with dosimetry and respiratory morbidity. MATERIALS AND METHODS CTs were available pre-RT and at 3, 6, 12 and 24-months post-RT for forty-five subjects enrolled in a phase 1/2 clinical trial of isotoxic, dose-escalated chemoradiotherapy for locally advanced non-small cell lung cancer. Fifteen CT-based measures of parenchymal, pleural and lung volume change, and anatomical distortions, were calculated. Respiratory morbidity was assessed with the Medical Research Council (MRC) dyspnoea score and spirometric pulmonary function tests (PFTs): FVC, FEV1, FEV1/FVC and DLCO. RESULTS FEV1, FEV1/FVC and MRC scores progressively declined post-RT; FVC decreased by 6-months before partially recovering. Radiologically, an early phase (3-6 months) of acute inflammation was characterised by reversible parenchymal change and non-progressive anatomical distortion. A phase of chronic scarring followed (6-24 months) with irreversible parenchymal change, progressive volume loss and anatomical distortion. Post-RT increase in contralateral lung volume was common. Normal lung volume shrinkage correlated longitudinally with mean lung dose (r = 0.30-0.40, p = 0.01-0.04). Radiological findings allowed separation of patients with predominant acute versus chronic RILD; subjects with predominantly chronic RILD had poorer pre-RT lung function. CONCLUSIONS CT-based measures enable detailed quantification of the longitudinal evolution of RILD. The majority of patients developed progressive lung damage, even when the early phase was absent or mild. Pre-RT lung function and RT dosimetry may allow to identify subjects at increased risk of RILD.
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Affiliation(s)
- Catarina Veiga
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, University College London, UK.
| | | | - Joseph Jacob
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, University College London, UK; Department of Respiratory Medicine, University College London, UK
| | - Natalie Yip
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, University College London, UK
| | - Adam Szmul
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, University College London, UK
| | - David Landau
- Department of Oncology, University College London Hospital, UK; Department of Clinical Oncology, Guy's & St Thomas' NHS Foundation Trust, UK
| | - Jamie R McClelland
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, University College London, UK
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Sharifi H, McDonald GC, Lee JK, Ajlouni MI, Chetty IJ, Zhong H. Four-dimensional computed tomography-based biomechanical measurements of pulmonary function and their correlation with clinical outcome for lung stereotactic body radiation therapy patients. Quant Imaging Med Surg 2019; 9:1278-1287. [PMID: 31448213 PMCID: PMC6685808 DOI: 10.21037/qims.2019.07.03] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 06/30/2019] [Indexed: 12/25/2022]
Abstract
BACKGROUND Functional image guided radiotherapy allows for the delivery of an equivalent dose to tumor targets while sparing high ventilation lung tissues. In this study, we investigate whether radiation dose to functional lung is associated with clinical outcome for stereotactic body radiation therapy (SBRT) patients. METHODS Four-dimensional computed tomography (4DCT) images were used to assess lung function. Deformable image registration (DIR) was performed from the end-inhale phase to the end-exhale phase with resultant displacement vectors used to calculate ventilation maps. In addition to the Jacobian-based ventilation we introduce a volumetric variation method (Rv) based on a biomechanical finite element method (FEM), to assess lung ventilation. Thirty NSCLC patients, treated with SBRT, were evaluated in this study. 4DCT images were used to calculate both Jacobian and Rv-based ventilation images. Areas under the receiver operating characteristic curve (AUC) were used to assess the predictive power of functional metrics. Metrics were calculated over the whole lung as well as high and low ventilated regions. RESULTS Ventilation in dose regions between 1 and 5 Gy had higher AUC values compared to other dose regions. Rv based ventilation imaging method also showed to be less spatially variant and less heterogeneous, and the resultant Rv metrics had higher AUC values for predicting grade 2+ dyspnea. CONCLUSIONS Low dose delivered to high ventilation areas may also increase the risk of compromised pulmonary function. Rv based ventilation images could be useful for the prediction of clinical toxicity for lung SBRT patients.
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Affiliation(s)
- Hoda Sharifi
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
| | - Gary C. McDonald
- Department of Mathematics and Statistics, Oakland University, Rochester, MI, USA
| | - Joon Kyu Lee
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Munther I. Ajlouni
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Indrin J. Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
| | - Hualiang Zhong
- Department of Physics, Oakland University, Rochester, MI, USA
- Department of Radiation Oncology, Medical College of Wisconsin, Madison, WI, USA
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Sharifi H, Brown S, McDonald GC, Chetty IJ, Zhong H. 4-Dimensional computed tomography-based ventilation and compliance images for quantification of radiation-induced changes in pulmonary function. J Med Imaging Radiat Oncol 2019; 63:370-377. [PMID: 30932346 DOI: 10.1111/1754-9485.12881] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 03/05/2019] [Indexed: 11/26/2022]
Abstract
INTRODUCTION 4-Dimensional computed tomography (4DCT)-based ventilation imaging is a promising technique for evaluating pulmonary function, but lung elasticity and mechanics are usually not part of the ventilation image analysis. In this study we demonstrate a 4DCT-based imaging technique that can be used to calculate regional lung compliance changes after radiotherapy (RT). METHODS Six lung cancer patients were included in this study. Four of the patients had 4DCT images acquired pre-RT, 3 and 9 months post-RT. Ventilation and compliance were calculated from the deformable image registration (DIR) of 4DCTs, performed from the end-inhale to the end-exhale breathing phase. Regional compliance was defined as the ratio of volumetric variation and associated stress in each voxel, representing lung elasticity and computed using a FEM-based framework. Ventilation, compliance and CT density were calculated for all pre-RT and post-RT 4DCTs and evaluation metrics were computed. RESULTS Average CT density changes were 13.6 ± 11.4HU after 3 months and 26.9 ± 15.8HU after 9 months. Ventilation was reduced at 3 months, but improved at 9 months in regions with dose ≥ 35 Gy, encompassing about 10% of the lung volume; compliance was reduced at both time-points. Radiation dose ≥ 35 Gy caused major change in lung density and ventilation, which was higher than that previously reported in the literature (i.e. 24 Gy). CONCLUSION Lung tissue response is diverse with respect to CT density, ventilation and compliance. Combination of ventilation and compliance with CT density could be beneficial for understanding radiation-induced lung damage and consequently could help develop improved treatment protocols for lung cancer patients.
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Affiliation(s)
- Hoda Sharifi
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA.,Department of Physics, Oakland University, Rochester, Michigan, USA
| | - Stephen Brown
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Gary C McDonald
- Department of Mathematics and Statistics, Oakland University, Rochester, Michigan, USA
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Hualiang Zhong
- Department of Radiation Oncology, Medical College of Wisconsin, Madison, Wisconsin, USA
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Defraene G, La Fontaine M, van Kranen S, Reymen B, Belderbos J, Sonke JJ, De Ruysscher D. Radiation-Induced Lung Density Changes on CT Scan for NSCLC: No Impact of Dose-Escalation Level or Volume. Int J Radiat Oncol Biol Phys 2018; 102:642-650. [PMID: 30244882 DOI: 10.1016/j.ijrobp.2018.06.038] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 05/23/2018] [Accepted: 06/20/2018] [Indexed: 12/25/2022]
Abstract
PURPOSE Dose-escalation for patients with non-small cell lung cancer (NSCLC) in the positron emission tomography (PET)-boost trial (NCT01024829) exposes portions of normal lung tissue to high radiation doses. The relationship between lung parenchyma dose and density changes on computed tomography (CT) was analyzed. MATERIALS AND METHODS The CT scans of 59 patients with stage IB to III NSCLC, randomized between a boost to the whole primary tumor and an integrated boost to its 50% SUVmax (maximum standardized uptake value) volume. Patients were treated with concurrent or sequential chemoradiation or radiation only. Deformable registration mapped the 3-month follow-up CT to the planning CT. Hounsfield unit differences (ΔHU) were extracted to assess lung parenchyma density changes. Equivalent dose in 2 Gy fractions (EQD2)-ΔHU response was described sigmoidally, and regional response variation was studied by polar analysis. Prognostic factors of ΔHU were obtained through generalized linear modeling. RESULTS Saturation of ΔHU was observed above 60 Gy. No interaction was found between boost dose distribution (D1cc and V70Gy) and ΔHU at lower doses. ΔHU was lowest peripherally from the tumor and peaked posteriorly at 3 cm from the tumor border (3.1 HU/Gy). Right lung location was an independent risk factor for ΔHU (P = .02). CONCLUSIONS No apparent increase of lung density changes at 3-month follow-up was observed above 60 Gy EQD2 for patients with NSCLC treated with (concurrent or sequential chemo) radiation. The mild response observed peripherally in the lung parenchyma might be exploited in plan optimization routines minimizing lung damage.
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Affiliation(s)
- Gilles Defraene
- Department of Oncology, Experimental Radiation Oncology, KU Leuven-University of Leuven, Belgium.
| | - Matthew La Fontaine
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Simon van Kranen
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Bart Reymen
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - José Belderbos
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Dirk De Ruysscher
- Department of Oncology, Experimental Radiation Oncology, KU Leuven-University of Leuven, Belgium; Maastricht University Medical Center, Maastricht, The Netherlands; Department of Radiation Oncology (Maastro Clinic), GROW School for Developmental Biology and Oncology, Maastricht, The Netherlands
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Underwood TSA, Grassberger C, Bass R, MacDonald SM, Meyersohn NM, Yeap BY, Jimenez RB, Paganetti H. Asymptomatic Late-phase Radiographic Changes Among Chest-Wall Patients Are Associated With a Proton RBE Exceeding 1.1. Int J Radiat Oncol Biol Phys 2018; 101:809-819. [PMID: 29976493 DOI: 10.1016/j.ijrobp.2018.03.037] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 02/13/2018] [Accepted: 03/26/2018] [Indexed: 12/20/2022]
Abstract
PURPOSE Clinical practice assumes a fixed proton relative biological effectiveness (RBE) of 1.1, but in vitro experiments demonstrate higher RBEs at the distal edge of the proton spread-out Bragg peak, that is, in a region that falls within the lung for chest-wall patients. We performed retrospective qualitative and quantitative analyses of lung-density changes-indicative of asymptomatic fibrosis-for chest-wall patients treated with protons or photons. Our null hypothesis was that, assuming a fixed RBE of 1.1, these changes would be the same for the 2 cohorts, supporting current RBE practice. Our alternative hypothesis was that radiographic abnormalities would be greater for the proton cohort, suggesting an RBE > 1.1. METHODS AND MATERIALS We analyzed follow-up computed tomography (CT) scans for 20 proton and photon patients. All were prescribed 50.4 Gy (RBE) in 28 fractions, assuming a fixed RBE of 1.1 for protons and 1 for photons. Deformable registrations enabled us to calculate density changes in the normal lung, specifically (1) median Hounsfield unit (HU) values among posttreatment CT scans and (2) changes in median HU values between pretreatment and posttreatment CT scans, both as a function of grays (RBE). In addition, qualitative abnormality grading was performed by a radiologist. RESULTS Proton patients exhibited higher values of HU/Gy (RBE) (endpoint 1) and ΔHU/Gy (RBE) (endpoint 2): P = .049 and P = .00019, respectively, were obtained (likelihood ratio tests of full linear mixed-effects models against models without "modality"). Furthermore, qualitative radiologic scoring indicated a significant difference between the cohorts (Wilcoxon P = .018; median score, 3 of 9 for protons and 1.5 of 9 for photons). CONCLUSIONS Our data support the hypothesis that the proton RBE for lung-density changes exceeds 1.1. This RBE elevation could be attributable to (1) the late, normal tissue endpoint that we consider or (2) end-of-range proton linear energy transfer elevation-or a combination of the two. Regardless, our results suggest that variations in proton RBE prove important in vivo as well as in vitro.
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Affiliation(s)
- Tracy S A Underwood
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
| | - Clemens Grassberger
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rhedise Bass
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Shannon M MacDonald
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nandini M Meyersohn
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Beow Y Yeap
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rachel B Jimenez
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Lung density change after SABR: A comparative study between tri-Co-60 magnetic resonance-guided system and linear accelerator. PLoS One 2018; 13:e0195196. [PMID: 29608606 PMCID: PMC5880382 DOI: 10.1371/journal.pone.0195196] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 03/14/2018] [Indexed: 12/25/2022] Open
Abstract
Radiation-induced lung damage is an important treatment-related toxicity after lung stereotactic ablative radiotherapy (SABR). After implementing a tri-60Co magnetic-resonance image guided system, ViewRayTM, we compared the associated early radiological lung density changes to those associated with a linear accelerator (LINAC). Eight patients treated with the tri-60Co system were matched 1:1 with patients treated with LINAC. Prescription doses were 52 Gy or 60 Gy in four fractions, and lung dose-volumetric parameters were calculated from each planning system. The first two follow-up computed tomography (CT) were co-registered with the planning CT through deformable registration software, and lung density was measured by isodose levels. Tumor size was matched between the two groups, but the planning target volume of LINAC was larger than that of the tri-60Co system (p = 0.036). With regard to clinically relevant dose-volumetric parameters in the lungs, the ipsilateral lung mean dose, V10Gy and V20Gy were significantly poorer in tri-60Co plans compared to LINAC plans (p = 0.012, 0.036, and 0.017, respectively). Increased lung density was not observed in the first follow-up scan compared to the planning scan. A significant change of lung density was shown in the second follow-up scan and there was no meaningful difference between the tri-60Co system and LINAC for all dose regions. In addition, no patient developed clinical radiation pneumonitis until the second follow-up scan. Therefore, there was no significant difference in the early radiological lung damage between the tri-60Co system and LINAC for lung SABR despite of the inferior plan quality of the tri-60Co system compared to that of LINAC. Further studies with a longer follow-up period are needed to confirm our findings.
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Abravan A, Knudtsen IS, Eide HA, Løndalen AM, Helland Å, van Luijk P, Malinen E. A new method to assess pulmonary changes using 18F-fluoro-2-deoxyglucose positron emission tomography for lung cancer patients following radiotherapy. Acta Oncol 2017; 56:1597-1603. [PMID: 28849707 DOI: 10.1080/0284186x.2017.1349336] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND 18F-fluoro-2-deoxyglucose positron emission tomography (18F-FDG-PET) may be used for assessing radiation induced alterations in the lung. However, there is a need to further develop methodologies to improve quantification. Using computed tomography (CT), a local structure method has been shown to be superior to conventional CT-based analysis. Here, we investigate whether the local structure method based on 18F-FDG-PET improves radiotherapy (RT) dose-response quantification for lung cancer patients. MATERIAL AND METHODS Sixteen patients with lung cancer undergoing fractionated RT were examined by 18F-FDG-PET/CT at three sessions (pre, mid, post) and the lung was delineated in the planning CT images. The RT dose matrix was co-registered with the PET images. For each PET image series, mean (μ) and standard deviation (σ) maps were calculated based on cubes in the lung (3 × 3 × 3 voxels), where the spread in pre-therapy μ and σ was characterized by a covariance ellipse in a sub-volume of 3 × 3 × 3 cubes. Mahalanobis distance was used to measure the distance of individual cube values to the origin of the ellipse and to further form local structure 'S' maps. The structural difference maps (ΔS) and mean difference maps (Δμ) were calculated by subtracting pre-therapy maps from maps at mid- and post-therapy. Corresponding maps based on CT images were also generated. RESULTS ΔS identified new areas of interest in the lung compared to conventional Δμ maps. ΔS for PET and CT gave a significantly elevated lung signal compared to a control group during and post-RT (p < .05). Dose-response analyses by linear regression showed that ΔS between pre- and post-therapy for 18F-FDG-PET was the only parameter significantly associated with local lung dose (p = .04). CONCLUSIONS The new method using local structures on 18F-FDG-PET provides a clearer uptake dose-response compared to conventional analysis and CT-based approaches and may be valuable in future studies addressing lung toxicity.
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Affiliation(s)
- Azadeh Abravan
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Medical Physics, Oslo University Hospital, Oslo, Norway
| | - Ingerid Skjei Knudtsen
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Medical Physics, Oslo University Hospital, Oslo, Norway
| | - Hanne Astrid Eide
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | | | - Åslaug Helland
- Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Peter van Luijk
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands
- Department of Cell Biology, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Eirik Malinen
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Medical Physics, Oslo University Hospital, Oslo, Norway
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