Conformal radiotherapy (CRT) planning for lung cancer: analysis of intrathoracic organ motion during extreme phases of breathing

Giraud, P.; Rycke, Yann De; Dubray, Bernard; Helfre, Sylvie; Voican, Daniel; Guo, Lingfei; Rosenwald, Jean-Claude; Keraudy, K.; Housset, M.; Touboul, E.; Cosset, Jean‐Marc

doi:10.1016/s0360-3016(01)01766-7

Cited by 149 publications

(107 citation statements)

References 21 publications

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“…Parameters a , c , and n of Equation 4 were set to 3 cm, 5 s, and 2 respectively, which is consistent with a large clinical breathing cycle. ( 25 , 26 ) One cycle of this analytic equation was sampled. Points of the curve (speed and position) were selected and implemented as a SEL sequence.…”

Section: Methodsmentioning

confidence: 99%

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Initial evaluation of a four‐dimensional computed tomography system, using a programmable motor

Simon

Giraud

Servois

et al. 2006

J Applied Clin Med Phys

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A dynamic lung tumor phantom was used to investigate the geometric reconstruction accuracy of a commercial four‐dimensional computed tomography (4D‐CT) system. A ball filled with resin, embedded in a cork cube, was placed on a moving platform. Various realistic antero‐posterior (AP) motions were programmed to reproduce the respiratory motion of a lung tumor. Several three‐dimensional (3D) CT and 4D‐CT images of this moving object were acquired and compared using different acquisition parameters. Apparent volume and diameter of the ball were measured and compared to the real values. The position of two points (the AP limits of the ball) during the motion in the coordinate system of the CT scanner were also compared with the expected values. Volume error was shown to increase with object speed. However, although the volume error was associated with intraslice artifacts, it did not reflect large interslice inconstancies in object position and should not be used as an indicator of image accuracy. The 3D‐CT gave a random position of the tumor along the phantom excursion; accuracy in the assessment of position by 4D‐CT ranged from 0.4 mm to 2.6 mm during extreme phases of breathing. We used average projection (AVE) and maximum intensity projection (MIP) algorithms available on the commercial software to create internal target volumes (ITVs) by merging gross tumor volume (GTV) images at various respiratory phases. The ITVs were compared to a theoretical value computed from the programmed ball excursion. The ITVs created from the MIP algorithm were closer to the theoretical value (within 12%) than were those created from the AVE algorithm (within 40%).PACS numbers: 87.53.Xd, 87.56.Mp, 87.57.Ce, 87.59.Fm

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Section: Methodsmentioning

confidence: 99%

“…However, Ross et al measured AP tumor motion that could reach 22 mm (25) . Giraud et al also observed, for one patient, an AP motion of 37 mm during deep breathing (26) . In practice, actual tumor motion is a combination of AP and SI motions.…”

Section: Introductionmentioning

confidence: 99%

Initial evaluation of a four‐dimensional computed tomography system, using a programmable motor

Simon

Giraud

Servois

et al. 2006

J Applied Clin Med Phys

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“…These movements are mainly caused by breathing and by cardiac motion, and can have an amplitude of up to 5 cm in extreme cases [1]. This motion can be compensated by new technical developments like multileaf collimators, robotic patient couches, Vero or the CyberKnife R Synchrony system [2].…”

Section: Introductionmentioning

confidence: 99%

Respiratory Motion Compensation with Relevance Vector Machines

Dürichen

Wissel

Ernst

et al. 2013

Advanced Information Systems Engineering

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Abstract. In modern robotic radiation therapy, tumor movements due to respiration can be compensated. The accuracy of these methods can be increased by time series prediction of external optical surrogates. An algorithm based on relevance vector machines (RVM) is introduced. We evaluate RVM with linear and nonlinear basis functions on a real patient data set containing 304 motion traces and compare it with a wavelet based least mean square algorithm (wLMS), the best algorithm for this data set so far. Linear RVM outperforms wLMS significantly and increases the prediction accuracy for 80.3 % of the data. We show that real time prediction is possible in case of linear RVM and discuss how the predicted variance can be used to construct promising hybrid algorithms, which further reduce the prediction error.

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“…However, Giraud et al analyzed the tumor position during respiratory cycle in ten different NSCLC patients and showed that for patients with SS-NSCLC, the median proximal-distal motion was 7 mm, and this was nearly zero in the other directions. 44 Thus, tomotherapy IMRT does not seem to be problematic for SS-NSCLC. The second point is more concerning because of the increase in the number of beams required to deliver the highly conformal dose, tomotherapy IMRT (and all IMRT modes) increases the lowdose distribution.…”

Section: Discussionmentioning

confidence: 99%

Superior sulcus non-small cell lung carcinoma: A comparison of IMRT and 3D-RT dosimetry

Truntzer¹,

Antoni

Santelmo

et al. 2016

Reports of Practical Oncology & Radiotherapy

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Conformal radiotherapy (CRT) planning for lung cancer: analysis of intrathoracic organ motion during extreme phases of breathing

Cited by 149 publications

References 21 publications

Initial evaluation of a four‐dimensional computed tomography system, using a programmable motor

Initial evaluation of a four‐dimensional computed tomography system, using a programmable motor

Respiratory Motion Compensation with Relevance Vector Machines

Superior sulcus non-small cell lung carcinoma: A comparison of IMRT and 3D-RT dosimetry

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