The Magnetic Resonance Imaging–Linac System Lagendijk, Jan J.W., PhD; Raaymakers, Bas W., PhD; van Vulpen, Marco, MD, PhD
Seminars in radiation oncology,
07/2014, Letnik:
24, Številka:
3
Journal Article
Recenzirano
The current image-guided radiotherapy systems are suboptimal in the esophagus, pancreas, kidney, rectum, lymph node, etc. These locations in the body are not easily accessible for fiducials and ...cannot be visualized sufficiently on cone-beam computed tomographies, making daily patient set-up prone to geometrical uncertainties and hinder dose optimization. Additional interfraction and intrafraction uncertainties for those locations arise from motion with breathing and organ filling. To allow real-time imaging of all patient tumor locations at the actual treatment position a fully integrated 1.5-T, diagnostic quality, magnetic resonance imaging with a 6-MV linear accelerator is presented. This system must enable detailed dose painting at all body locations.
The key goal and main challenge of radiation therapy is the elimination of tumors without any concurring damages of the surrounding healthy tissues and organs. Radiation doses required to achieve ...sufficient cancer‐cell kill exceed in most clinical situations the dose that can be tolerated by the healthy tissues, especially when large parts of the affected organ are irradiated. High‐precision radiation oncology aims at optimizing tumor coverage, while sparing normal tissues. Medical imaging during the preparation phase, as well as in the treatment room for localization of the tumor and directing the beam, referred to as image‐guided radiotherapy (IGRT), is the cornerstone of precision radiation oncology. Sophisticated high‐resolution real‐time IGRT using X‐rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. IGRT is the most convincing success story of radiation oncology over the last decades, and it remains a major driving force of innovation, contributing to the development of personalized oncology, for example, through the use of real‐time imaging biomarkers for individualized dose delivery.
Sophisticated, high‐resolution, real‐time image‐guided radiotherapy (IGRT) using X‐rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. Here, we review IGRT research and applications and discuss how they contribute to the development of personalized oncology, for example, through the use of real‐time imaging biomarkers for individualized dose delivery.
Objective
This study was conducted in order to determine the optimal timing of diffusion-weighted magnetic resonance imaging (DW-MRI) for prediction of pathologic complete response (pCR) to ...neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer.
Methods
Patients with esophageal adenocarcinoma or squamous cell carcinoma who planned to undergo nCRT followed by surgery were enrolled in this prospective study. Patients underwent six DW-MRI scans: one baseline scan before the start of nCRT and weekly scans during 5 weeks of nCRT. Relative changes in mean apparent diffusion coefficient (ADC) values between the baseline scans and the scans during nCRT (ΔADC(%)) were compared between pathologic complete responders (pCR) and non-pCR (tumor regression grades 2–5). The discriminative ability of ΔADC(%) was determined based on the
c
-statistic.
Results
A total of 24 patients with 142 DW-MRI scans were included. pCR was observed in seven patients (29%). ΔADC(%) from baseline to week 2 was significantly higher in patients with pCR versus non-pCR (median IQR, 36% 30%, 41% for pCR versus 16% 14%, 29% for non-pCR,
p
= 0.004). The ΔADC(%) of the second week in combination with histology resulted in the highest
c
-statistic for the prediction of pCR versus non-pCR (0.87). The
c
-statistic of this model increased to 0.97 after additional exclusion of patients with a small tumor volume (< 7 mL,
n
= 3) and tumor histology of the resection specimen other than adenocarcinoma or squamous cell carcinoma (
n
= 1).
Conclusion
The relative change in tumor ADC (ΔADC(%)) during the first 2 weeks of nCRT is the most predictive for pathologic complete response to nCRT in esophageal cancer patients.
Key Points
• DW-MRI during the second week of neoadjuvant chemoradiotherapy is most predictive for pathologic complete response in esophageal cancer.
• A model including ΔADC
week 2
was able to discriminate between pathologic complete responders and non-pathologic complete responders in 87%.
• Improvements in future MRI studies for esophageal cancer may be obtained by incorporating motion management techniques.
Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution ...MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.
Abstract Purpose To explore the value of diffusion-weighted magnetic resonance imaging (DW-MRI) for the prediction of pathologic response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer. ...Material and methods In 20 patients receiving nCRT for esophageal cancer DW-MRI scanning was performed before nCRT, after 8–13 fractions, and before surgery. The median tumor apparent diffusion coefficient (ADC) was determined at these three time points. The predictive potential of initial tumor ADC, and change in ADC (ΔADC) during and after treatment for pathologic complete response (pathCR) and good response were assessed. Good response was defined as pathCR or near-pathCR (tumor regression grade TRG 1 or 2). Results A pathCR after nCRT was found in 4 of 20 patients (20%), and 8 patients (40%) showed a good response to nCRT. The ΔADCduring was significantly higher in pathCR vs. non-pathCR patients (34.6% ± 10.7% mean ± SD vs. 14.0% ± 13.1%, p = 0.016), as well as in good vs. poor responders (30.5% ± 8.3% vs. 9.5% ± 12.5%, p = 0.002). The ΔADCduring was predictive of residual cancer at a threshold of 29% (sensitivity of 100%, specificity of 75%, PPV of 94%, and NPV of 100%), and for poor pathologic response at a threshold of 21% (sensitivity of 82%, specificity of 100%, PPV of 100%, and NPV of 80%). Conclusions In this exploratory study, the treatment-induced change in ADC during the first 2–3 weeks of nCRT for esophageal cancer seemed highly predictive of histopathologic response. Larger series are warranted to verify these results.
Hyperthermia treatment planning (HTP) is valuable to optimize tumor heating during thermal therapy delivery. Yet, clinical hyperthermia treatment plans lack quantitative accuracy due to uncertainties ...in tissue properties and modeling, and report tumor absorbed power and temperature distributions which cannot be linked directly to treatment outcome. Over the last decade, considerable progress has been made to address these inaccuracies and therefore improve the reliability of hyperthermia treatment planning. Patient-specific electrical tissue conductivity derived from MR measurements has been introduced to accurately model the power deposition in the patient. Thermodynamic fluid modeling has been developed to account for the convective heat transport in fluids such as urine in the bladder. Moreover, discrete vasculature trees have been included in thermal models to account for the impact of thermally significant large blood vessels. Computationally efficient optimization strategies based on SAR and temperature distributions have been established to calculate the phase-amplitude settings that provide the best tumor thermal dose while avoiding hot spots in normal tissue. Finally, biological modeling has been developed to quantify the hyperthermic radiosensitization effect in terms of equivalent radiation dose of the combined radiotherapy and hyperthermia treatment. In this paper, we review the present status of these developments and illustrate the most relevant advanced elements within a single treatment planning example of a cervical cancer patient. The resulting advanced HTP workflow paves the way for a clinically feasible and more reliable patient-specific hyperthermia treatment planning.
•5 patients with pelvic lymph node metastases received SBRT using a 1.5 T MR-linac.•Session time was <60 min for all 25 treatment fractions.•All quality assurance tests were passed (dose calculations ...& film measurements).
Online adaptive radiotherapy using the 1.5 Tesla MR-linac is feasible for SBRT (5 × 7 Gy) of pelvic lymph node oligometastases. The workflow allows full online planning based on daily anatomy. Session duration is less than 60 min. Quality assurance tests, including independent 3D dose calculations and film measurements were passed.
MRI/linac integration Lagendijk, Jan J.W; Raaymakers, Bas W; Raaijmakers, Alexander J.E ...
Radiotherapy and oncology,
01/2008, Letnik:
86, Številka:
1
Journal Article
Recenzirano
Abstract Purpose/objectives In radiotherapy the healthy tissue involvement still poses serious dose limitations. This results in sub-optimal tumour dose and complications. Daily image guided ...radiotherapy (IGRT) is the key development in radiation oncology to solve this problem. MRI yields superb soft-tissue visualization and provides several imaging modalities for identification of movements, function and physiology. Integrating MRI functionality with an accelerator can make these capacities available for high precision, real time IGRT. Design and results The system being built at the University Medical Center Utrecht is a 1.5 T MRI scanner, with diagnostic imaging functionality and quality, integrated with a 6 MV radiotherapy accelerator. The realization of a prototype of this hybrid system is a joint effort between the Radiotherapy Department of the University of Utrecht, the Netherlands, Elekta, Crawley, U.K., and Philips Research, Hamburg, Germany. Basically, the design is a 1.5 T Philips Achieva MRI scanner with a Magnex closed bore magnet surrounded by a single energy (6 MV) Elekta accelerator. Monte Carlo simulations are used to investigate the radiation beam properties of the hybrid system, dosimetry equipment and for the construction of patient specific dose deposition kernels in the presence of a magnetic field. The latter are used to evaluate the IMRT capability of the integrated MRI linac. Conclusions A prototype hybrid MRI/linac for on-line MRI guidance of radiotherapy (MRIgRT) is under construction. The aim of the system is to deliver the radiation dose with mm precision based on diagnostic quality MR images.
To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time adaptation, motion must be quickly estimated with low latency. The motion estimate is used to adapt the radiation beam to ...the current anatomy, yielding a more conformal dose distribution. As the MR acquisition is the largest component of latency, deep learning (DL) may reduce the total latency by enabling much higher undersampling factors compared to conventional reconstruction and motion estimation methods. The benefit of DL on image reconstruction and motion estimation was investigated for obtaining accurate deformation vector fields (DVFs) with high temporal resolution and minimal latency. 2D cine MRI acquired at 1.5 T from 135 abdominal cancer patients were retrospectively included in this study. Undersampled radial golden angle acquisitions were retrospectively simulated. DVFs were computed using different combinations of conventional- and DL-based methods for image reconstruction and motion estimation, allowing a comparison of four approaches to achieve real-time motion estimation. The four approaches were evaluated based on the end-point-error and root-mean-square error compared to a ground-truth optical flow estimate on fully-sampled images, the structural similarity (SSIM) after registration and time necessary to acquire k-space, reconstruct an image and estimate motion. The lowest DVF error and highest SSIM were obtained using conventional methods up to R≤10. For undersampling factors R>10, the lowest DVF error and highest SSIM were obtained using conventional image reconstruction and DL-based motion estimation. We have found that, with this combination, accurate DVFs can be obtained up to R=25 with an average root-mean-square error up to 1 millimeter and an SSIM greater than 0.8 after registration, taking 60 milliseconds. High-quality 2D DVFs from highly undersampled k-space can be obtained with a high temporal resolution with conventional image reconstruction and a deep learning-based motion estimation approach for real-time adaptive MRI-guided radiotherapy.
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