Inter- and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI

Cui, Lei; Yin, Jianbing; Hu, Chunhong; Gong, Shenchu; Xu, Junfeng; Yang, Jushun

doi:10.1016/j.clinimag.2016.04.002

Cited by 15 publications

(18 citation statements)

References 15 publications

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“…The reproducibility of ADC values was slightly poorer than that of D values, although fewer b values were used to generate ADC maps and one of them is 0 s/mm 2 , suggesting that the D values derived from biexponential data fitting and the ADC values derived from monoexponential data fitting were probably similar in a uniform tissue . Also, our study showed similar reproducibility of ADC in lung cancer compared to the value reported by Cui et al (WCV 3.6–5.7%). We also achieved slightly better results than those reported by Bernardin et al (CV 8.9–11%), which may be because the latter focused on populations with smaller lung metastases, although they used a region‐growing function method to reduce the measurement errors.…”

Section: Discussionsupporting

confidence: 50%

“…However, the image quality using this technique can be degraded due to low resolution, artifacts, and geometric distortion. 13 3T MRI has been advocated for the 13,24 A previous study 25 has shown that ADC has good inter-and intraobserver agreement in all freebreathing, breath-hold, and respiratory-triggered DWIs. However, the duration of respiratory-triggered scan is prolonged by irregular breathing and breath-holding scan may be confronted with low compliance in patients with massive pleural effusion or large chest tumors.…”

Section: Discussionmentioning

confidence: 99%

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Lung Cancer: Short‐Term Reproducibility of Intravoxel Incoherent Motion Parameters and Apparent Diffusion Coefficient at 3T

Jiang

Yin

Cui

et al. 2017

Magnetic Resonance Imaging

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Section: Discussionsupporting

confidence: 50%

Section: Discussionmentioning

confidence: 99%

Lung Cancer: Short‐Term Reproducibility of Intravoxel Incoherent Motion Parameters and Apparent Diffusion Coefficient at 3T

Jiang

Yin

Cui

et al. 2017

Magnetic Resonance Imaging

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“…Intra‐ and interobserver variations for manual contours of lung tumors are well documented in the literature, in CT, in PET/CT fusion and in 4DCT images. In terms of MRI of lung cancer, intra/inter observer metrics have been evaluated for breath held lung volumes in MR/CT images, as well diffusion metrics . However, in terms of lung tumor target delineation, to the best knowledge of the authors (i.e., PubMed/Google Scholar), this is the first assessment of intraobserver and interobserver variations in the dynamic lung MR images for monitoring the changes in tumor shape and location in real‐time.…”

Section: Discussionmentioning

confidence: 99%

“…In terms of MRI of lung cancer, intra/inter observer metrics have been evaluated for breath held lung volumes in MR/CT images, 25 as well diffusion metrics. 26,27 However, in terms of lung tumor target delineation, to the best knowledge of the authors (i.e., PubMed/Google Scholar), this is the first assessment of intraobserver and interobserver variations in the dynamic lung MR images for monitoring the changes in tumor shape and location in real-time. This is also the first study in which a user-trained autocontouring algorithm has been benchmarked against variation metrics of multiple expert users, as suggested by Valentini et al 28 on dynamic lung MR images.…”

Section: Discussionmentioning

confidence: 99%

Evaluating performance of a user‐trained MR lung tumor autocontouring algorithm in the context of intra‐ and interobserver variations

et al. 2017

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Purpose: Real-time tracking of lung tumors using magnetic resonance imaging (MRI) has been proposed as a potential strategy to mitigate the ill-effects of breathing motion in radiation therapy. Several autocontouring methods have been evaluated against a "gold standard" of a single human expert user. However, contours drawn by experts have inherent intra-and interobserver variations. In this study, we aim to evaluate our user-trained autocontouring algorithm with manually drawn contours from multiple expert users, and to contextualize the accuracy of these autocontours within intra-and interobserver variations. Methods: Six nonsmall cell lung cancer patients were recruited, with institutional ethics approval. Patients were imaged with a clinical 3 T Philips MR scanner using a dynamic 2D balanced SSFP sequence under free breathing. Three radiation oncology experts, each in two separate sessions, contoured 130 dynamic images for each patient. For autocontouring, the first 30 images were used for algorithm training, and the remaining 100 images were autocontoured and evaluated. Autocontours were compared against manual contours in terms of Dice's coefficient (DC) and Hausdorff distances (d H ). Intra-and interobserver variations of the manual contours were also evaluated. Results: When compared with the manual contours of the expert user who trained it, the algorithm generates autocontours whose evaluation metrics (same session: DC = 0.90(0.03), d H = 3.8(1.6) mm; different session DC = 0.88(0.04), d H = 4.3(1.5) mm) are similar to or better than intraobserver variations (DC = 0.88(0.04), and d H = 4.3(1.7) mm) between two sessions. The algorithm's autocontours are also compared to the manual contours from different expert users with evaluation metrics (DC = 0.87(0.04), d H = 4.8(1.7) mm) similar to interobserver variations (DC = 0.87(0.04), d H = 4.7(1.6) mm). Conclusions: Our autocontouring algorithm delineates tumor contours (<20 ms per contour), in dynamic MRI of lung, that are comparable to multiple human experts (several seconds per contour), but at a much faster speed. At the same time, the agreement between autocontours and manual contours is comparable to the intra-and interobserver variations. This algorithm may be a key component of the real time tumor tracking workflow for our hybrid Linac-MR device in the future.

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“…If motion corrections or registration techniques are not utilised, the respiratory motion might possibly alter ADC results and hinder DWI score evaluation. However, it has been recently shown that reliable ADC measurements can be obtained in free breathing, breath-hold and respiratory triggered DWI of lung cancer [30]. Moreover at the time of the study, we did not have the dedicated software for imaging registration that we are currently developing.…”

Section: Discussionmentioning

confidence: 99%

Detection and monitoring of lung inflammation in cystic fibrosis during respiratory tract exacerbation using diffusion-weighted magnetic resonance imaging

et al. 2017

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The aim was to investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects and monitors inflammatory and lung function changes during respiratory tract exacerbations (RTE) treatment in patients with cystic fibrosis (CF).29 patients with RTE underwent DWI pre- and post-antibiotic treatment. A control group of 27 stable patients, matched for age and sex, underwent DWI with the same time gap as those undergoing RTE treatment. Clinical status and lung function were assessed at each DWI time point. The CF-MRI scoring system was used to assess structural lung changes in both CF groups.Significant reduction in the DWI score over the course of antibiotic treatment (p<0.0001) was observed in patients with RTE, but not in the control group. DWI score had a strong inverse correlation with clinical status (r=-0.504, p<0.0001) and lung function (r=-0.635, p<0.0001) in patients with RTE. Interestingly, there were persistent significant differences in the CF-MRI score between the RTE and control group at both baseline and follow-up (p<0.001), while the differences in DWI score were only observed at baseline (p<0.001).DWI is a promising imaging method for noninvasive detection of pulmonary inflammation during RTE, and may be used to monitor treatment efficacy of anti-inflammatory treatment.

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Inter- and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI

Cited by 15 publications

References 15 publications

Lung Cancer: Short‐Term Reproducibility of Intravoxel Incoherent Motion Parameters and Apparent Diffusion Coefficient at 3T

Lung Cancer: Short‐Term Reproducibility of Intravoxel Incoherent Motion Parameters and Apparent Diffusion Coefficient at 3T

Evaluating performance of a user‐trained MR lung tumor autocontouring algorithm in the context of intra‐ and interobserver variations

Detection and monitoring of lung inflammation in cystic fibrosis during respiratory tract exacerbation using diffusion-weighted magnetic resonance imaging

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