Tumor location, cirrhosis, and surgical history contribute to tumor movement in the liver, as measured during stereotactic irradiation using a real-time tumor-tracking radiotherapy system

Kitamura, Kei; Shirato, Hiroki; Seppenwoolde, Yvette; Shimizu, Tadashi; Kodama, Yoshihisa; Endo, Hitomi; Onimaru, Rikiya; Oda, Makoto; Fujita, Katsuhisa; Shimizu, Satoru; Miyasaka, Kazuo

doi:10.1016/s0360-3016(03)00082-8

Cited by 111 publications

(77 citation statements)

References 28 publications

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“…Kitamura et al (23) reported that the tumor motion of the right liver lobe was significantly larger than that of the left lobe in the LR and AP directions (

p < 0.01

). However, in our study no obvious variations in tumor motion were found for tumors in the right lobe and the left lobe in the LR (

p = 0.331

), AP (

p = 0.518

) and CC (

p = 0.746

).…”

Section: Discussionmentioning

confidence: 99%

Analysis of the advantage of individual PTVs defined on axial 3D CT and 4D CT images for liver cancer

Xing

et al. 2012

J Applied Clin Med Phys

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The purpose of this study was to compare positional and volumetric differences of planning target volumes (PTVs) defined on axial three dimensional CT (3D CT) and four dimensional CT (4D CT) for liver cancer. Fourteen patients with liver cancer underwent 3D CT and 4D CT simulation scans during free breathing. The tumor motion was measured by 4D CT. Three internal target volumes (ITVs) were produced based on the clinical target volume from 3DCT (CTV3D): i) A conventional ITV (ITVconv) was produced by adding 10 mm in CC direction and 5 mm in LR and and AP directions to CTV3D; ii) A specific ITV (ITVspec) was created using a specific margin in transaxial direction; iii) ITVvector was produced by adding an isotropic margin derived from the individual tumor motion vector. ITV4D was defined on the fusion of CTVs on all phases of 4D CT. PTVs were generated by adding a 5 mm setup margin to ITVs. The average centroid shifts between PTVs derived from 3DCT and PTV4D in left–right (LR), anterior–posterior (AP), and cranial–caudal (CC) directions were close to zero. Comparing PTV4D to PTVconv, PTVspec, and PTVvector resulted in a decrease in volume size by 33.18% ±12.39%, 24.95% ±13.01%, 48.08% ±15.32%, respectively. The mean degree of inclusions (DI) of PTV4D in PTVconv, and PTV4D in PTVspec, and PTV4D in PTVvector was 0.98, 0.97, and 0.99, which showed no significant correlation to tumor motion vector (r=‐0.470, 0.259, and 0.244; p=0.090, 0.371, and 0.401). The mean DIs of PTVconv in PTV4D, PTVspec in PTV4D, and PTVvector in PTV4D was 0.66, 0.73, and 0.52. The size of individual PTV from 4D CT is significantly less than that of PTVs from 3DCT. The position of targets derived from axial 3DCT images scatters around the center of 4D targets randomly. Compared to conventional PTV, the use of 3D CT‐based PTVs with individual margins cannot significantly reduce normal tissues being unnecessarily irradiated, but may contribute to reducing the risk of missing targets for tumors with large motion.PACS number: 87

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“…Kitamura et al (23) reported that the tumor motion of the right liver lobe was significantly larger than that of the left lobe in the LR and AP directions (

p < 0.01

). However, in our study no obvious variations in tumor motion were found for tumors in the right lobe and the left lobe in the LR (

p = 0.331

), AP (

p = 0.518

) and CC (

p = 0.746

).…”

Section: Discussionmentioning

confidence: 99%

Analysis of the advantage of individual PTVs defined on axial 3D CT and 4D CT images for liver cancer

Xing

et al. 2012

J Applied Clin Med Phys

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“…Respiratory motion and cardiac and aortic pulsations cause the position of the tumor to change during scanning. 36 As a result, surrounding liver tissue could move in and out of the tumor ROIs and, in addition, because tumor tissue is often less homogeneous than liver tissue, motion in a tumor ROI could have a larger effect than motion inside a normal liver ROI when comparing IVIM parameter maps. Respiratory and cardiac gating could circumvent this problem, but it would roughly double the total IVIM acquisition time.…”

Section: Discussionmentioning

confidence: 99%

Intravoxel Incoherent Motion Protocol Evaluation and Data Quality in Normal and Malignant Liver Tissue and Comparison to the Literature

Voert¹,

Delso²,

Porto

et al. 2016

Investigative Radiology

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OBJECTIVES: Although intravoxel incoherent motion (IVIM) becomes more and more popular, there is currently no clear consensus on the number and distribution of b-values to use. In this work, we (1) tested and evaluated the data quality of a 25-b-value IVIM protocol in patients with malignant liver lesions and normal liver tissue as a standard of reference, (2) calculated an optimal b-value distribution and compared with the standard of reference, and (3) compared the 25-b-value protocol with other proposed protocols in the literature. MATERIALS AND METHODS: Intravoxel incoherent motion imaging with 25 b-values was performed at 3 T in a total of 15 patients with malignant liver lesions. Reference IVIM parameter maps were calculated in tumor and normal liver tissue. With these parameters, optimal IVIM protocols with reduced numbers of b-values were calculated. These optimal IVIM protocols were again applied to calculate new IVIM parameter maps that were compared with the reference parameter maps by calculating mean relative errors. In addition, 35 other IVIM protocols, as found in literature, were compared in a similar way with the 25-b-value protocol serving as a standard of reference. RESULTS: The mean relative error depends on the number of b-values and their distribution. In tumor tissue, the error is higher and more variable than in normal-appearing liver tissue. The largest errors occur in tumor tissue and in the protocols having low numbers of b-values in the IVIM protocols. In the calculated optimal IVIM protocols, the mean relative errors decreased by 40% or more when the number of b-values included increased from 4 to 16. The mean relative errors in the protocols adapted from the literature vary substantially between the various b-value distributions. One optimized 16-b-value protocol, which was found in literature, reduced the average relative error by 80% when compared with 4-and 5-b-value protocols listed in literature. CONCLUSIONS: Including more b-values and applying an optimized b-value distribution significantly reduces errors in the IVIM parameter estimates, thereby increasing its accuracy.This effect is even more pronounced in inhomogeneous tumor compared with that in normal liver tissue. However, when restrictions in acquisition time or patient-related factors apply, a minimum of 16 b-values should be considered for reliable results.

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“…2 Kitamura et al analyzed the liver tumor motion under tidal breathing and showed a tumor motion up to 4 mm (range 1-12 mm), 9 mm (range 2-19 mm) and 5 mm (range 2-12 mm) in the left-right (LR), CC and anterior-posterior (AP) directions, respectively. 2,3 Several techniques can be used to manage tumor motion, such as active breath control, abdominal compression, respiratory gating and real-time tumor tracking. [4][5][6][7][8][9] In this study, we used the respiratory gating technique with an external surrogate placed on the patient's abdominal wall associated with implanted fiducial markers to manage liver motion.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of reproducibility of tumor repositioning during multiple breathing cycles for liver stereotactic body radiotherapy treatment

Bedos

Riou

Aillères

et al. 2017

Reports of Practical Oncology & Radiotherapy

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a b s t r a c tAim: To evaluate the tumor repositioning during gated volumetric modulated arc therapy (VMAT) for liver stereotactic body radiotherapy(SBRT) treatment using implanted fiducial markers and intrafraction kilovoltage (kV) images acquired during dose delivery. Materials and methods:Since 2012, 47 liver cancer patients with implanted fiducial markers were treated using the gated VMAT technique with a Varian Truebeam STx linear accelerator.The fiducial markers were implanted inside or close to the tumor target before treatment simulation. They were defined at the maximum inhalation and exhalation phases on a 4-dimensionnal computed tomography (4DCT) acquisition. During the treatment, kV images were acquired just before the beam-on at each breathing cycle at maximum exhalation and inhalation phases to verify the fiducial markers positions. For the five first fractions of treatment in the first ten consecutive patients, a total of 2705 intrafraction kV images were retrospectively analyzed to assess the differences between expected and actual positions of the fiducial markers along the cranio-caudal (CC) direction during the exhalation phase. Results:The mean absolute intrafractional fiducial marker deviation along the CC direction was 1.0 mm at the maximum exhalation phase. In 99%, 95% and 90% cases, the fiducial marker deviations were ≤4.5 mm, 2.8 mm and 2.2 mm, respectively. Conclusion:Intrafraction kV images allowed us to ensure the consistency of tumor repositioning during treatment. In 99% cases, the fiducial marker deviations were ≤4.5 mm corresponding to our 5 mm treatment margin. This margin seems to be well-adapted to the gated VMAT SBRT treatment in liver disease.

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Tumor location, cirrhosis, and surgical history contribute to tumor movement in the liver, as measured during stereotactic irradiation using a real-time tumor-tracking radiotherapy system

Cited by 111 publications

References 28 publications

Analysis of the advantage of individual PTVs defined on axial 3D CT and 4D CT images for liver cancer

Analysis of the advantage of individual PTVs defined on axial 3D CT and 4D CT images for liver cancer

Intravoxel Incoherent Motion Protocol Evaluation and Data Quality in Normal and Malignant Liver Tissue and Comparison to the Literature

Evaluation of reproducibility of tumor repositioning during multiple breathing cycles for liver stereotactic body radiotherapy treatment

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