Four-dimensional multislice helical CT of the lung: Qualitative comparison of retrospectively gated and static images in an ex-vivo system

Dinkel, Julien; Welzel, Thomas; Bolte, Hendrik; Hoffmann, B.; Thierfelder, C; Mende, Ulrich; Debus, Jürgen; Heller, Martin; Kauczor, Hans‐Ulrich; Biederer, J.

doi:10.1016/j.radonc.2007.09.003

Cited by 18 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From previous studies, the team was familiar with the ex vivo system and with low pitch helical 4D-CT. An analysis of image quality demonstrated typical, but tolerable, artifacts in respiration-correlated 4D-CT reconstructions (29). The reproducibility of spatial information for small objects was proven with computer-assisted lung nodule volumetry (14).…”

Section: Previous Experiencementioning

confidence: 97%

4D-Imaging of the Lung: Reproducibility of Lesion Size and Displacement on Helical CT, MRI, and Cone Beam CT in a Ventilated Ex Vivo System

Biederer

Dinkel

Remmert

et al. 2009

International Journal of Radiation Oncology*Biology*Physics

Self Cite

View full text Add to dashboard Cite

Section: Previous Experiencementioning

confidence: 97%

4D-Imaging of the Lung: Reproducibility of Lesion Size and Displacement on Helical CT, MRI, and Cone Beam CT in a Ventilated Ex Vivo System

Biederer

Dinkel

Remmert

et al. 2009

International Journal of Radiation Oncology*Biology*Physics

Self Cite

View full text Add to dashboard Cite

“…It provides ‘instant’ capture of the target volume corresponding to different respiratory phases throughout a respiratory cycle. Respiratory motion artifacts can be mitigated by 4DCT that accounts for respiratory motion [12]. Moreover, most patients can tolerate 4DCT scanning, because it is performed during free breathing.…”

Section: Introductionmentioning

confidence: 99%

Geometrical differences in gross target volumes between 3DCT and 4DCT imaging in radiotherapy for non-small-cell lung cancer

Zhang

et al. 2013

Journal of Radiation Research

View full text Add to dashboard Cite

The aim of this study was to explore the characteristic of 3DCT scanning phases and estimate the comparative amount of respiration motion information included in 3DCT and 4DCT by comparing the volumetric and positional difference between the volumes from 3DCT and 4DCT for the radiotherapy of non-small-cell lung cancer (NSCLC). A total of 28 patients with NSCLC sequentially underwent 3DCT and 4DCT simulation scans of the thorax during free breathing. The 4DCT images with respiratory signal data were reconstructed and sorted into 10 phases throughout a respiratory cycle. GTV-3D from 3DCT, GTV-0%, GTV-20%, GTV-50% and GTV-70% from end-inspiration, mid-expiration, end-expiration and mid-inspiration of 4DCT, and the internal GTV (IGTV-10) from the fused phase of 4DCT were delineated based on the 50% phase image, respectively. The differences in the position, size, matching index (MI) and degree of inclusion (DI) for different volumes were evaluated. The variation in the centroid shifts of GTV-0% and GTV-3D, GTV-20% and GTV-3D, GTV-50% and GTV-3D, and GTV-90% and GTV-3D in the 3D direction was not significant (P = 0.990). The size ratios of GTV-0%, GTV-20%, GTV-50%, GTV-70% and IGTV-10 to GTV-3D were 0.94 ± 0.18, 0.95 ± 0.18, 0.98 ± 0.15, 1.00 ± 0.18 and 1.60 ± 0.55, respectively. DIs of GTV-3D in IGTV-10, and IGTV-10 in GTV-3D were 0.88 ± 0.14 and 0.59 ± 0.16 (P < 0.001). The 3DCT scanning phases are irregular. The CTV-to-ITV expansion should be isotropic when defining the ITV on the 3DCT. The internal GTV derived from 4DCT cannot completely include the GTV from 3DCT. An additional margin may be required when defining the ITV-based 4DCT.

show abstract

“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] 4D-CT image sets are a sequence of 3D-CT datasets indexed by respiratory phase, acquired using sorting based on the respiration amplitude or the phase of fan-or cone-beam images. 18,19 Such methods can be acquired for sequential table positions, also termed the cine acquisition method, [20][21][22] or by "helical" scanning, also called spiral acquisition, [23][24][25][26][27] and the differences between these two methods is well-documented. 21 Approaches to 4D-CT gating include retrospective gating 17,20,24,26,28,29 and prospective gating 30 and commonly applied acquisition methods include phase- 4,24,26,28,31 and amplitude-based sorting.…”

Section: Introductionmentioning

confidence: 99%

Characterization and identification of spatial artifacts during 4D‐CT imaging

et al. 2011

View full text Add to dashboard Cite

Purpose: The purpose of this work is twofold: First, to characterize the artifacts occurring in helical 4D-CT imaging; second, to propose a method that can automatically identify the artifacts in 4D-CT images. The authors have designed a process that can automatically identify the artifacts in 4D-CT images, which may be invaluable in quantifying the quality of 4D-CT images and reducing the artifacts from the reconstructed images on a large dataset. Methods: Given two adjacent stacks obtained from the same respiration phase, the authors determine if there are artifacts between them. The proposed method uses a "bridge" stack strategy to connect the two stacks. Using normalized cross correlation convolution ͑NCCC͒, the two stacks are mapped to the bridge stack and the best matching positions can be located. Using this position information, the authors can then determine if there are artifacts between the two stacks. By combining the matching positions with NCCC values, the performance can be improved. Results: To validate the method, three expert observers independently labeled over 600 stacks on five patients. The results confirmed that high performance was obtained using the proposed method. The average sensitivity was about 0.87 and the average specificity was 0.82. The proposed method also outperformed the method of using respiratory signal ͑sensitivity increased from 0.50 to 0.87 and specificity increased from 0.70 to 0.82͒. Conclusions: This study shows that the spatial artifacts during 4D-CT imaging are characterized and can be located automatically by the proposed method. The method is relatively simple but effective. It provides a way to evaluate the artifacts more objectively and accurately. The reported approach has promising potential for automatically identifying the types and frequency of artifacts on large scale 4D-CT image dataset.

show abstract

Four-dimensional multislice helical CT of the lung: Qualitative comparison of retrospectively gated and static images in an ex-vivo system

Cited by 18 publications

References 24 publications

4D-Imaging of the Lung: Reproducibility of Lesion Size and Displacement on Helical CT, MRI, and Cone Beam CT in a Ventilated Ex Vivo System

4D-Imaging of the Lung: Reproducibility of Lesion Size and Displacement on Helical CT, MRI, and Cone Beam CT in a Ventilated Ex Vivo System

Geometrical differences in gross target volumes between 3DCT and 4DCT imaging in radiotherapy for non-small-cell lung cancer

Characterization and identification of spatial artifacts during 4D‐CT imaging

Contact Info

Product

Resources

About