Preserving Functional Lung Using Perfusion Imaging and Intensity-Modulated Radiation Therapy for Advanced-Stage Non–Small Cell Lung Cancer

Shioyama, Yoshiyuki; Jang, Seonghoe; Liu, H. Helen; Guerrero, Thomas; Wang, Xuanmin; Gayed, Isis; Erwin, William D.; Liao, Zhongxing; Chang, Joe Y.; Jeter, Melenda; Yaremko, Brian; Borghero, Yerko; Cox, James D.; Komaki, Ritsuko; Mohan, Radhe

doi:10.1016/j.ijrobp.2007.02.015

Cited by 93 publications

(88 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Seven scenarios using simulated functional imaging data representing locally advanced NSCLC have demonstrated that inclusion of functional information in IMRT plan optimisation allowed improved avoidance of functional lung, as assessed by FV 20 and the MFLD, compared to anatomical IMRT alone. The median reduction in FV 20 of 2.7% demonstrated in this simulation study is in keeping with that observed previously by Ireland et al of 3.1% (range 0.4-5.1%) [18] when using 3 He-MRI data, although it is less than the 5-6% absolute median reductions in FV 20 observed in selected SPECT literature examining functional versus anatomical IMRT [12,13].…”

Section: Discussionsupporting

confidence: 91%

“…Early SPECT studies using conformal planning concluded that the greatest benefits were observed in patients with large localised defects in lung function [10,17], a view supported by the findings of a more recent study using IMRT [12]. However, another recent study comparing SPECT-based IMRT with functional 3D conformal planning failed to identify significant benefits in this group, suggesting instead diffuse inhomogeneity of lung function as the most favourable setting for the use of this combined technique [11,19].…”

mentioning

confidence: 94%

“…However, a significant proportion of NSCLC patients have defects in regional lung function caused either by local tumour effects or by concurrent pulmonary disease [9][10][11][12]. This observation has prompted investigations of functional image-based radiotherapy planning, utilising physiological information from either single-photon emission computed tomography (SPECT) [10][11][12][13], four-dimensional X-ray computed tomography (4D-CT) [14] or hyperpolarized helium-3 magnetic resonance imaging ( 3 He-MRI) [15,16].…”

mentioning

confidence: 99%

“…In addition, the combination of SPECT imaging data with IMRT techniques has shown the potential to improve functional lung avoidance when compared to both SPECT-based 3D conformal plans [11], and standard anatomical IMRT plans [12,13], permitting average reductions in FV 20 of 3-10.6% in patients with locally advanced disease, although this benefit has not been demonstrable in early stage patients [11][12][13].…”

mentioning

confidence: 99%

See 3 more Smart Citations

Functional image-based radiotherapy planning for non-small cell lung cancer: A simulation study

Bates

Bragg

Wild

et al. 2009

Radiotherapy and Oncology

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 91%

mentioning

confidence: 94%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Functional image-based radiotherapy planning for non-small cell lung cancer: A simulation study

Bates

Bragg

Wild

et al. 2009

Radiotherapy and Oncology

View full text Add to dashboard Cite

show abstract

“…All regions of the lung are usually deemed equal. Clinicians and researchers have proposed to advance normal lung sparing in thoracic cancer radiotherapy by introducing ventilation and/or perfusion imaging into radiotherapy treatment planning 25 , 26 . If clinically implemented, it could lead to reduced radiation toxicity to lung regions with high perfusion and/or ventilation while adequate dose coverage of tumors is maintained.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Zhang

Latifi

et al. 2016

J Applied Clin Med Phys

View full text Add to dashboard Cite

Ventilation distribution calculation using 4D CT has shown promising potential in several clinical applications. This study evaluated the direct geometric ventilation calculation method, namely the ΔV method, with xenon‐enhanced CT (XeCT) ventilation data from four sheep, and compared it with two other published methods, the Jacobian and the Hounsfield unit (HU) methods. Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used for the evaluation and comparison. The average SCC with one standard deviation was 0.44±0.13 with a range between 0.29 and 0.61 between the XeCT and DLV ventilation distributions. The average DSC value for lower 30% ventilation volumes between the XeCT and ΔV ventilation distributions was 0.55±0.07 with a range between 0.48 and 0.63. Ventilation difference introduced by deformable image registration errors improved with smoothing. In conclusion, ventilation distributions generated using ΔV‐4D CT and deformable image registration are in reasonably agreement with the in vivo XeCT measured ventilation distribution.PACS number(s): 87.57.N‐, 87.57.nj, 87.57.Q‐, 87.85.Pq

show abstract

Feasibility of function‐guided lung treatment planning with parametric response mapping

Matrosic

Owen

Polan

et al. 2021

J Applied Clin Med Phys

View full text Add to dashboard Cite

Purpose: Recent advancements in functional lung imaging have been developed to improve clinicians' knowledge of patient pulmonary condition prior to treatment. Ultimately, it may be possible to employ these functional imaging modalities to tailor radiation treatment plans to optimize patient outcome and mitigate pulmonary complications. Parametric response mapping (PRM) is a computed tomography (CT)-based functional lung imaging method that utilizes a voxel-wise image analysis technique to classify lung abnormality phenotypes, and has previously been shown to be effective at assessing lung complication risk in diagnostic applications. The purpose of this work was to demonstrate the implementation of PRM guidance in radiotherapy treatment planning. Methods and materials: A retrospective study was performed with 18 lung cancer patients to test the incorporation of PRM into a radiotherapy planning workflow. Paired inspiration/expiration pretreatment CT scans were acquired and PRM analysis was utilized to classify each voxel as normal, parenchymal disease, small airway disease, and emphysema. Density maps were generated for each PRM classification to contour high density regions of pulmonary abnormalities. Conventional volumetric-modulated arc therapy and PRM-guided treatment plans were designed for each patient. Results: PRM guidance was successfully implemented into the treatment planning process. The inclusion of PRM priorities resulted in statistically significant (p < 0.05) improvements to the V20Gy within the PRM avoidance contours. On average, reductions of 5.4% in the V20Gy(%) were found. The PRM-guided treatment plans did not significantly increase the dose to the organs at risk or result in insufficient planning target volume coverage, but did increase plan complexity. Conclusions: PRM guidance was successfully implemented into a treatment planning workflow and shown to be effective for dose redistribution within the lung. This work has provided a framework for the potential clinical implementation of PRM-guided treatment planning.

show abstract

Preserving Functional Lung Using Perfusion Imaging and Intensity-Modulated Radiation Therapy for Advanced-Stage Non–Small Cell Lung Cancer

Cited by 93 publications

References 21 publications

Functional image-based radiotherapy planning for non-small cell lung cancer: A simulation study

Functional image-based radiotherapy planning for non-small cell lung cancer: A simulation study

Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Feasibility of function‐guided lung treatment planning with parametric response mapping

Contact Info

Product

Resources

About