557 research outputs found
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
METHODOLOGY TO ASSESS AUTOMATED ATLAS-BASED SEGMENTATIONS AND INTER- AND INTRA-OBSERVER VARIABILITY IN THE DELINEATION OF THE PROSTATE BED
The purpose of the study was to assess the accuracy, validity and time-savings of automated atlas-based segmentations (AABS). Further, the study assessed the inter- and intra observer variability in the delineation of the prostate bed (PB) and the five regions of interest for postoperative conformal radiotherapy in prostate cancer patients. Finally, the study reports on the development of an appropriate methodology for similar studies. Seventy-five DICOM Computed Tomography (CT) datasets were obtained to create the prostate bed atlas and another five datasets were retrospectively contoured by the atlas builder, the expert panel and the AABS tool. Consensus segmentations (CS) were also generated. The mean dice similarity coefficient comparing the edited AABS and CS was 0.67, 0.88, 0.93, 0.92, 0.54 and 0.78 for the PB, bladder, left- and right femoral head, penile bulb and rectum, respectively. Significant inter observer variation was observed in the PB and bilateral femoral heads. Significant time savings were obtained using the average AABS editing time (p = 0.003) versus the manual contouring time. We successfully developed a methodology and validated the AABS tool for routine clinical use
GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy
Online adaptive radiation therapy (ART) has great promise to significantly
reduce normal tissue toxicity and/or improve tumor control through real-time
treatment adaptations based on the current patient anatomy. However, the major
technical obstacle for clinical realization of online ART, namely the inability
to achieve real-time efficiency in treatment re-planning, has yet to be solved.
To overcome this challenge, this paper presents our work on the implementation
of an intensity modulated radiation therapy (IMRT) direct aperture optimization
(DAO) algorithm on graphics processing unit (GPU) based on our previous work on
CPU. We formulate the DAO problem as a large-scale convex programming problem,
and use an exact method called column generation approach to deal with its
extremely large dimensionality on GPU. Five 9-field prostate and five 5-field
head-and-neck IMRT clinical cases with 5\times5 mm2 beamlet size and
2.5\times2.5\times2.5 mm3 voxel size were used to evaluate our algorithm on
GPU. It takes only 0.7~2.5 seconds for our implementation to generate optimal
treatment plans using 50 MLC apertures on an NVIDIA Tesla C1060 GPU card. Our
work has therefore solved a major problem in developing ultra-fast
(re-)planning technologies for online ART
Intensity modulated radiotherapy: advantages, limitations and future developments
Intensity modulated radiotherapy (IMRT) is widely used in clinical applications in developed countries, for the treatment of malignant and non-malignant diseases. This technique uses multiple radiation beams of non-uniform intensities. The beams are modulated to the required intensity maps for delivering highly conformal doses of radiation to the treatment targets, while sparing the adjacent normal tissue structures. This treatment technique has superior dosimetric advantages over 2-dimensional (2D) and conventional 3-dimensional conformal radiotherapy (3DCRT) treatments. It can potentially benefit the patient in three ways. First, by improving conformity with target dose it can reduce the probability of in-field recurrence. Second, by reducing irradiation of normal tissue it can minimise the degree of morbidity associated with treatment. Third, by facilitating escalation of dose it can improve local control. Early clinical results are promising, particularly in the treatment of nasopharyngeal carcinoma (NPC). However, as the IMRT is a sophisticated treatment involving high conformity and high precision, it has specific requirements. Therefore, tight tolerance levels for random and systematic errors, compared with conventional 2D and 3D treatments, must be applied in all treatment and pre-treatment procedures. For this reason, a large-scale routine clinical implementation of the treatment modality demands major resources and, in some cases, is impractical. This paper will provide an overview of the potential advantages of the IMRT, methods of treatment delivery, and equipment currently available for facilitating the treatment modality. It will also discuss the limitations of the equipment and the ongoing development work to improve the efficiency of the equipment and the treatment techniques and procedures
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
Development of CBCT-based prostate setup correction strategies and impact of rectal distension.
BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality.
METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared.
RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR.
CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours
Evaluating and Improving 4D-CT Image Segmentation for Lung Cancer Radiotherapy
Lung cancer is a high-incidence disease with low survival despite surgical advances and concurrent chemo-radiotherapy strategies. Image-guided radiotherapy provides for treatment measures, however, significant challenges exist for imaging, treatment planning, and delivery of radiation due to the influence of respiratory motion. 4D-CT imaging is capable of improving image quality of thoracic target volumes influenced by respiratory motion. 4D-CT-based treatment planning strategies requires highly accurate anatomical segmentation of tumour volumes for radiotherapy treatment plan optimization. Variable segmentation of tumour volumes significantly contributes to uncertainty in radiotherapy planning due to a lack of knowledge regarding the exact shape of the lesion and difficulty in quantifying variability. As image-segmentation is one of the earliest tasks in the radiotherapy process, inherent geometric uncertainties affect subsequent stages, potentially jeopardizing patient outcomes. Thus, this work assesses and suggests strategies for mitigation of segmentation-related geometric uncertainties in 4D-CT-based lung cancer radiotherapy at pre- and post-treatment planning stages
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