Dose-guided radiation therapy with megavoltage cone-beam CT

UCSF Comprehensive Cancer Center, Department of Radiation Oncology, University of California San Francisco, 1600 Divisadero Street, Suite H1031, San Francisco, CA 94143, USA.
The British journal of radiology (Impact Factor: 2.03). 10/2006; 79 Spec No 1(special_issue_1):S87-98. DOI: 10.1259/bjr/60612178
Source: PubMed


Recent advances in fractionated external beam radiation therapy have increased our ability to deliver radiation doses that conform more tightly to the tumour volume. The steeper dose gradients delivered in these treatments make it increasingly important to set precisely the positions of the patient and the internal organs. For this reason, considerable research now focuses on methods using three-dimensional images of the patient on the treatment table to adapt either the patient position or the treatment plan, to account for variable organ locations. In this article, we briefly review the different adaptive methods being explored and discuss a proposed dose-guided radiation therapy strategy that adapts the treatment for future fractions to compensate for dosimetric errors from past fractions. The main component of this strategy is a procedure to reconstruct the dose delivered to the patient based on treatment-time portal images and pre-treatment megavoltage cone-beam computed tomography (MV CBCT) images of the patient. We describe the work to date performed to develop our dose reconstruction procedure, including the implementation of a MV CBCT system for clinical use, experiments performed to calibrate MV CBCT for electron density and to use the calibrated MV CBCT for dose calculations, and the dosimetric calibration of the portal imager. We also present an example of a reconstructed patient dose using a preliminary reconstruction program and discuss the technical challenges that remain to full implementation of dose reconstruction and dose-guided therapy.

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    • "On the other hand, patients with oesophageal cancer often have problems maintaining their calorie intake and it is not preferable to change their dietary habits. With the implementation of image-guided radiotherapy (IGRT) and dose recalculation based on the kilovoltage cone-beam computed tomography (kV CBCT), we can calculate the delivered dose to the target volume during treatment and eventually adjust treatment if necessary [10] [11]. This study has two main objectives: (1) to investigate the necessity of adaptive radiotherapy for patients with GEJ tumours in case of unaccounted stomach changes e.g. "
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    ABSTRACT: Purpose: To evaluate whether adaptive radiotherapy for unaccounted stomach changes in patients with adenocarcinoma of the gastroesophageal junction (GEJ) is necessary and whether dose differences could be prevented by giving patients food and fluid instructions before treatment simulation and radiotherapy. Material and methods: Twenty patients were randomly assigned into two groups: patients with and without instructions about restricting food and fluid intake prior to radiotherapy simulation and treatment. Redelineation and offline recalculation of dose distributions based on cone-beam computed tomography (n=100) were performed. Dose-volume parameters were analysed for the clinical target volume extending into the stomach. Results: Four patients who did not receive instructions had a geometric miss (0.7-12cm(3)) in only one fraction. With instructions, 3 out of 10 patients had a geometric miss (0.1-1.9cm(3)) in one (n=2) or two (n=1) fractions. The V95% was reduced by more than 5% for one patient, but this underdosage was in an in-air region without further clinical importance. Conclusions: Giving patients food and fluid instructions for the treatment of GEJ cancer offers no clinical benefit. Using a planning target volume margin of 1cm implies that there is no need for adaptive radiotherapy for GEJ tumours.
    Radiotherapy and Oncology 09/2015; DOI:10.1016/j.radonc.2015.09.006 · 4.36 Impact Factor
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    • "This recent adaptive radiotherapy (ART) strategy appears however complex, in particular to decide when and how many times to replan during the treatment course [11] [12]. In this context, a key step is the capability to monitor the cumulated dose received by the deformed OARs, fraction after fraction, then to compare this dose with the planned dose, and finally to decide whether or not to replan within a dose-guided adaptive radiotherapy strategy [13] [14]. Deformable image registration (DIR) is a keystone of the dose accumulation process (Figure 1). "
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    ABSTRACT: In the context of head and neck cancer (HNC) adaptive radiation therapy (ART), the two purposes of the study were to compare the performance of multiple deformable image registration (DIR) methods and to quantify their impact for dose accumulation, in healthy structures. Fifteen HNC patients had a planning computed tomography (CT0) and weekly CTs during the 7 weeks of intensity-modulated radiation therapy (IMRT). Ten DIR approaches using different registration methods (demons or B-spline free form deformation (FFD)), preprocessing, and similarity metrics were tested. Two observers identified 14 landmarks (LM) on each CT-scan to compute LM registration error. The cumulated doses estimated by each method were compared. The two most effective DIR methods were the demons and the FFD, with both the mutual information (MI) metric and the filtered CTs. The corresponding LM registration accuracy (precision) was 2.44 mm (1.30 mm) and 2.54 mm (1.33 mm), respectively. The corresponding LM estimated cumulated dose accuracy (dose precision) was 0.85 Gy (0.93 Gy) and 0.88 Gy (0.95 Gy), respectively. The mean uncertainty (difference between maximal and minimal dose considering all the 10 methods) to estimate the cumulated mean dose to the parotid gland (PG) was 4.03 Gy (SD = 2.27 Gy, range: 1.06–8.91 Gy).
    BioMed Research International 01/2015; 2015. DOI:10.1155/2015/726268 · 3.17 Impact Factor
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    • "This analysis typically includes the calculation of dose-volume histograms, which plot the percentage of a previously-segmented volume in the image data receiving a certain dose from the treatment beams. One could define dose-guided radiotherapy (Chen et al. (2006)) as an extension of adaptive radiotherapy where dosimetric considerations are the basis for decisions about whether future treatment fractions should be reoptimized, readjusted or re-planned to compensate for dosimetric errors. In this paper, we present an integrated constrained nonrigid registration and automatic segmentation algorithm designed to meet the demands of IGRT. "
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    ABSTRACT: External beam radiotherapy (EBRT) has become the preferred options for nonsurgical treatment of prostate cancer and cervix cancer. In order to deliver higher doses to cancerous regions within these pelvic structures (i.e. prostate or cervix) while maintaining or lowering the doses to surrounding non-cancerous regions, it is critical to account for setup variation, organ motion, anatomical changes due to treatment and intra-fraction motion. In previous work, manual segmentation of the soft tissues is performed and then images are registered based on the manual segmentation. In this paper, we present an integrated automatic approach to multiple organ segmentation and nonrigid constrained registration, which can achieve these two aims simultaneously. The segmentation and registration steps are both formulated using a Bayesian framework, and they constrain each other using an iterative conditional model strategy. We also propose a new strategy to assess cumulative actual dose for this novel integrated algorithm, in order to both determine whether the intended treatment is being delivered and, potentially, whether or not a plan should be adjusted for future treatment fractions. Quantitative results show that the automatic segmentation produced results that have an accuracy comparable to manual segmentation, while the registration part significantly outperforms both rigid and nonrigid registration. Clinical application and evaluation of dose delivery show the superiority of proposed method to the procedure currently used in clinical practice, i.e. manual segmentation followed by rigid registration.
    Medical image analysis 05/2011; 15(5):772-85. DOI:10.1016/ · 3.65 Impact Factor
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