Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

Journey from 2D to 3D: Implant imaging a review

Imaging techniques play an important role in proper treatment planning for dental implant. Conventional radiographic imaging techniques provide sufficient information regarding suggested implant sites. But, small size, image distortion and magnification limit their use in many cases. Previously CT has been employed for preoperative planning of implant. The major disadvantages of CT are artifacts, high dose of radiation and cost. Advanced imaging modalities like CBCT produces 3D images at relatively low cost and radiation dose thus making it invaluable in coordination with other techniques providing the anatomical information thus helps in proper treatment plan, good prognosis and thus relatively low risks for surgical mishaps

Optimizing the Radiation Treatment Planning of Brain Tumors by Integration of Functional MRI and White Matter Tractography

Background: Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) present the ability to selectively protect functional regions and fiber tracts of the brain when brain tumors are treated with radiotherapy. Objective: This study aimed to assess whether the incorporation of fMRI and DTI data into the radiation treatment planning process of brain tumors could prevent the neurological parts of the brain from high doses of radiation. Material and Methods: In this investigational theoretical study, the fMRI and DTI data were obtained from eight glioma patients. This patient-specific fMRI and DTI data were attained based on tumor location, the patient’s general conditions, and the importance of the functional and fiber tract areas. The functional regions, fiber tracts, anatomical organs at risk, and the tumor were contoured for radiation treatment planning. Finally, the radiation treatment planning with and without fMRI & DTI information was obtained and compared. Results: The mean dose to the functional areas and the maximum doses were reduced by 25.36% and 18.57% on fMRI & DTI plans compared with the anatomical plans. In addition, 15.59% and 20.84% reductions were achieved in the mean and maximum doses of the fiber tracts, respectively.  Conclusion: This study demonstrated the feasibility of using fMRI and DTI data in radiation treatment planning to maximize radiation protection of the functional cortex and fiber tracts. The mean and maximum doses significantly decreased to neurologically relevant brain regions, resulting in reducing the neuro-cognitive complications and improving the patient’s quality of life

Functional image-based radiotherapy planning for non-small cell lung cancer: a simulation study

Background and purpose: To investigate the incorporation of data from single-photon emission computed tomography (SPECT) or hyperpolarized helium-3 magnetic resonance imaging (He-3-MRI) into intensity-modulated radiotherapy (IMRT) planning for non-small cell lung cancer (NSCLC). Material and methods: Seven scenarios were simulated that represent cases of NSCLC with significant functional lung defects. Two independent IMRT plans were produced for each scenario; one to minimise total lung volume receiving >= 20 Gy (V-20), and the other to minimise only the functional lung volume receiving >= 20 Gy (FV20). Dose-volume characteristics and a plan quality index related to planning target volume coverage by the 95% isodose (V-PTV95/FV20) were compared between anatomical and functional plans using the Wilcoxon signed ranks test. Results: Compared to anatomical IMRT plans, functional planning reduced FV20 (median 2.7%, range 0.6-3.5%, p = 0.02), and total lung V-20 (median 1.5%, 0.5-2.7%, p = 0.02), with a small reduction in mean functional lung dose (median 0.4 Gy, 0-0.7 Gy, p = 0.03). There were no significant differences in target volume coverage or organ-at-risk doses. Plan quality index was improved for functional plans (median increase 1.4, range 0-11.8, p = 0.02). Conclusions: Statistically significant reductions in FV20, V-20 and mean functional lung dose are possible when IMRT planning is supplemented by functional information derived from SPECT or He-3-MRI. (C) 2009 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 93 (2009) 32-3

Three-Dimensional Dose Prediction for Lung IMRT Patients with Deep Neural Networks: Robust Learning from Heterogeneous Beam Configurations

The use of neural networks to directly predict three-dimensional dose distributions for automatic planning is becoming popular. However, the existing methods only use patient anatomy as input and assume consistent beam configuration for all patients in the training database. The purpose of this work is to develop a more general model that, in addition to patient anatomy, also considers variable beam configurations, to achieve a more comprehensive automatic planning with a potentially easier clinical implementation, without the need of training specific models for different beam settings

3D-printing techniques in a medical setting : a systematic literature review

Background: Three-dimensional (3D) printing has numerous applications and has gained much interest in the medical world. The constantly improving quality of 3D-printing applications has contributed to their increased use on patients. This paper summarizes the literature on surgical 3D-printing applications used on patients, with a focus on reported clinical and economic outcomes. Methods: Three major literature databases were screened for case series (more than three cases described in the same study) and trials of surgical applications of 3D printing in humans. Results: 227 surgical papers were analyzed and summarized using an evidence table. The papers described the use of 3D printing for surgical guides, anatomical models, and custom implants. 3D printing is used in multiple surgical domains, such as orthopedics, maxillofacial surgery, cranial surgery, and spinal surgery. In general, the advantages of 3D-printed parts are said to include reduced surgical time, improved medical outcome, and decreased radiation exposure. The costs of printing and additional scans generally increase the overall cost of the procedure. Conclusion: 3D printing is well integrated in surgical practice and research. Applications vary from anatomical models mainly intended for surgical planning to surgical guides and implants. Our research suggests that there are several advantages to 3D- printed applications, but that further research is needed to determine whether the increased intervention costs can be balanced with the observable advantages of this new technology. There is a need for a formal cost-effectiveness analysis

Radiotherapy planning for glioblastoma based on a tumor growth model: Improving target volume delineation

Glioblastoma are known to infiltrate the brain parenchyma instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In clinical practice, a uniform margin is applied to account for microscopic spread of disease. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth: Anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. A retrospective study involving 10 glioblastoma patients has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most crucial model input. We conclude that the tumor growth model provides a method to account for anisotropic growth patterns of glioblastoma, and may therefore provide a tool to make target delineation more objective and automated

Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

Until recently, Computer-Aided Medical Interventions (CAMI) and Medical Robotics have focused on rigid and non deformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed