Corticospinal tract-sparing intensity-modulated radiotherapy treatment planning

Aim

To establish intensity-modulated radiotherapy (IMRT) planning procedures that spare the corticospinal tract by integrating diffusion tensor tractography into the treatment planning software.

Background

Organs at risk are generally contoured according to the outline of the organ as demonstrated by CT or MRI. But a part of the organ with specific function is difficult to protect, because such functional part of the organ cannot be delineated on CT or conventional sequence of MRI.

Methods

Diagnostic and treatment planning images of glioblastoma patients who had been treated by conventional 3-dimensional conformal radiotherapy were used for re-planning of IMRT. Three-dimensional fiber maps of the corticospinal tracts were created from the diffusion tensors obtained from the patients before the surgery, and were blended with the anatomical MR images (i.e. gadolinium-enhanced T1-weighted images or T2-weighted images). DICOM-formatted blended images were transferred and fused to the planning CT images. Then, IMRT plans were attempted.

Results

The corticospinal tracts could be contoured as organs at risk (OARs), because the blended images contained both anatomical information and fiber-tract maps. Other OARs were contoured in a way similar to that of ordinary IMRT planning. Gross tumor volumes, clinical target volumes, planning target volumes, and other OARs were contoured on the treatment planning software, and IMRT plans were made.

Conclusions

IMRT plans with diminished doses to the corticospinal tract were attained. This technique enabled us to spare specific neuron fibers as OARs which were formerly “invisible” and to reduce the probability of late morbidities.     

Computerized planning for multiprobe cryosurgery using a force-field analogy

Cryosurgery is the destruction of undesired biological tissues by freezing. For internal organs, multiple cryoprobes are inserted into the tissue with the goal of maximizing cryoinjury within a predefined target region, while minimizing cryoinjury to the surrounding tissues. The objective of this study is to develop a computerized planning tool to determine the best locations to insert the cryoprobes, based on bioheat transfer simulations. This tool is general and suitable for all available cooling techniques and hardware. The planning procedure employs a novel iterative optimization technique based on a force-field analogy. In each iteration, a single transient bioheat transfer simulation of the cryoprocedure is computed. At the end of the simulation, regions of tissue that would have undesired temperatures apply "forces" to the cryoprobes directly moving them to better locations. This method is more efficient than traditional numerical optimization techniques, because it requires significantly fewer bioheat transfer simulations for each iteration of planning. For demonstration purposes, 2D examples on cross sections typical of prostate cryosurgery are given.     

Computerized planning of prostate cryosurgery using variable cryoprobe insertion depth

The current study presents a computerized planning scheme for prostate cryosurgery using a variable insertion depth strategy. This study is a part of an ongoing effort to develop computerized tools for cryosurgery. Based on typical clinical practices, previous automated planning schemes have required that all cryoprobes be aligned at a single insertion depth. The current study investigates the benefit of removing this constraint, in comparison with results based on uniform insertion depth planning as well as the so-called “pullback procedure”. Planning is based on the so-called “bubble-packing method”, and its quality is evaluated with bioheat transfer simulations. This study is based on five 3D prostate models, reconstructed from ultrasound imaging, and cryoprobe active length in the range of 15-35 mm. The variable insertion depth technique is found to consistently provide superior results when compared to the other placement methods. Furthermore, it is shown that both the optimal active length and the optimal number of cryoprobes vary among prostate models, based on the size and shape of the target region. Due to its low computational cost, the new scheme can be used to determine the optimal cryoprobe layout for a given prostate model in real time.     

Novel radio-chromic solution dosimeter for radiotherapy treatment planning

Nitro blue tetrazolium (NBT) solution dosimeters were prepared and investigated based on radiation-induced reduction of NBT²⁺. NBT solution dosimeters containing different concentrations of NBT dye from 1 to 5 mM were prepared in a solution of ethanol. The dosimeters were irradiated with 6 MV X-ray beam at doses up to 30 Gy. The dose sensitivity of NBT solution increases strongly with increase of concentrations of NBT dye. The dose response of NBT dosimeters increases remarkably by addition of various concentrations of sodium formate (0.5, 2.5 and 5 mM). It becomes more remarkable with increasing pH value of NBT-sodium formate dosimeters. The sensitivity of the solution increased fairly with increase of irradiation temperature, therefore, the response of the solutions has to be corrected under actual processing conditions. The stability of solution dosimeters after irradiation was very high up to 30 days.     

Concentration modulated skin marker for radiotherapy treatment planning process

Background and purposeFor conformal radiotherapy, it is feasible to achieve high accuracy in contouring the outline of the target volume in treatment planning process. In contouring process, target volume is occasionally defined by means of either surgical clips or skin marker during patient anatomical data acquisition. Treatment planning systems are predicting invalid radiation dose distributions by using surgical clips and skin marker within the patient. Purpose of this study is the production of new skin marker which affects less dose distributions of electron beam.Materials and methodsThe influences of lead and commercial markers on dose calculations in a 3D treatment planning systems were investigated in terms of electron beam energy and dose profile depth. Dose deviation with commercial marker was observed to smaller than lead marker. However this dose deviation was still at big value. In order to reduce of this value, barium sulfate suspension and ultrasound gel were mixed with different volumetric ratio. With the purpose of acception the most suitable marker for radiation therapy, obtained new suspensions were investigated in terms of visibility and dose deviation.ResultsB:G/1:10 marker was determined to cause optimum visibility and the lowest dose deviation on dose calculations in terms of electron beam energy and dose profile depth.ConclusionsAppropriate marker, mixture of substances such as barium sulfate suspension and ultrasound gel can be produced. This marker is both ease of usage and practical and economical. Each clinic can prepare marker which is peculiar to suspension with different concentration of substance for specific visibility. But, it should be taken into account resultant dose deviation to beam calculation depending on barium sulfate concentration.     

Boosting runtime-performance of photon pencil beam algorithms for radiotherapy treatment planning

Pencil beam algorithms are still considered as standard photon dose calculation methods in Radiotherapy treatment planning for many clinical applications. Despite their established role in radiotherapy planning their performance and clinical applicability has to be continuously adapted to evolving complex treatment techniques such as adaptive radiation therapy (ART). We herewith report on a new highly efficient version of a well-established pencil beam convolution algorithm which relies purely on measured input data. A method was developed that improves raytracing efficiency by exploiting the capability of modern CPU architecture for a runtime reduction. Since most of the current desktop computers provide more than one calculation unit we used symmetric multiprocessing extensively to parallelize the workload and thus decreasing the algorithmic runtime. To maximize the advantage of code parallelization, we present two implementation strategies – one for the dose calculation in inverse planning software, and one for traditional forward planning. As a result, we could achieve on a 16-core personal computer with AMD processors a superlinear speedup factor of approx. 18 for calculating the dose distribution of typical forward IMRT treatment plans.     

Novel knowledge-based treatment planning model for hypofractionated radiotherapy of prostate cancer patients

PurposeTo demonstrate the strength of an innovative knowledge-based model-building method for radiotherapy planning using hypofractionated, multi-target prostate patients.Material and methodsAn initial RapidPlan model was trained using 48 patients who received 60 Gy to prostate (PTV60) and 44 Gy to pelvic nodes (PTV44) in 20 fractions. To improve the model's goodness-of-fit, an intermediate model was generated using the dose-volume histograms of best-spared organs-at-risk (OARs) of the initial model. Using the intermediate model and manual tweaking, all 48 cases were re-planned. The final model, trained using these re-plans, was validated on 50 additional patients. The validated final model was used to determine any planning advantage of using three arcs instead of two on 16 VMAT cases and tested on 25 additional cases to determine efficacy for single-PTV (PTV60-only) treatment planning.ResultsFor model validation, PTV V_95% of 99.9% was obtained by both clinical and knowledge-based planning. D_1% was lower for model plans: by 1.23 Gy (PTV60, CI = [1.00, 1.45]), and by 2.44 Gy (PTV44, CI = [1.72, 3.16]). OAR sparing was superior for knowledge-based planning: ΔD_mean = 3.70 Gy (bladder, CI = [2.83, 4.57]), and 3.22 Gy (rectum, CI = [2.48, 3.95]); ΔD_2% = 1.17 Gy (bowel bag, CI = [0.64, 1.69]), and 4.78 Gy (femoral heads, CI = [3.90, 5.66]). Using three arcs instead of two, improvements in OAR sparing and PTV coverage were statistically significant, but of magnitudes < 1 Gy. The model failed at reliable DVH predictions for single PTV plans.ConclusionsOur knowledge-based model delivers efficient, consistent plans with excellent PTV coverage and improved OAR sparing compared to clinical plans.     

Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning

Background and purposeComputed tomography (CT) imaging is the current gold standard for radiotherapy treatment planning (RTP). The establishment of a magnetic resonance imaging (MRI) only RTP workflow requires the generation of a synthetic CT (sCT) for dose calculation. This study evaluates the feasibility of using a multi-atlas sCT synthesis approach (sCT_a) for head and neck and prostate patients.Material and methodsThe multi-atlas method was based on pairs of non-rigidly aligned MR and CT images. The sCT_a was obtained by registering the MRI atlases to the patient’s MRI and by fusing the mapped atlases according to morphological similarity to the patient. For comparison, a bulk density assignment approach (sCT_bda) was also evaluated. The sCT_bda was obtained by assigning density values to MRI tissue classes (air, bone and soft-tissue). After evaluating the synthesis accuracy of the sCTs (mean absolute error), sCT-based delineations were geometrically compared to the CT-based delineations. Clinical plans were re-calculated on both sCTs and a dose-volume histogram and a gamma analysis was performed using the CT dose as ground truth.ResultsResults showed that both sCTs were suitable to perform clinical dose calculations with mean dose differences less than 1% for both the planning target volume and the organs at risk. However, only the sCT_a provided an accurate and automatic delineation of bone.ConclusionsCombining MR delineations with our multi-atlas CT synthesis method could enable MRI-only treatment planning and thus improve the dosimetric and geometric accuracy of the treatment, and reduce the number of imaging procedures.     

Challenges of radiotherapy: Report on the 4D treatment planning workshop 2013

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop.     

Computerized tomography in the diagnosis of hemorrhage caused by ruptured intracranial aneurysm]

The authors presented current views on usefulness of computed tomography (CT) for diagnosing the bleeding from a ruptured intracranial aneurysm. CT should be done in every such case, whereas the lumbar puncture remains the diagnostic method of choice, when CT is not available or in those patients in whom CT shows no haemorrhage. Sensitivity of CT decreases with time that elapsed from the stroke; false negative results are the least likely to occur within the first 48 hours after bleeding episode to subarachnoid space.     

Radiomics classifier to quantify automatic segmentation quality of cardiac sub-structures for radiotherapy treatment planning

PurposeA radiomics features classifier was implemented to evaluate segmentation quality of heart structures. A robust feature set sensitive to incorrect contouring would provide an ideal quantitative index to drive autocontouring optimization.MethodsTwenty-five cardiac sub-structures were contoured as regions of interest in 36 CTs. Radiomic features were extracted from manually-contoured (MC) and Hierarchical-Clustering automatic-contouring (AC) structures. A robust feature-set was identified from correctly contoured CT datasets. Features variation was analyzed over a MC/AC dataset. A supervised-learning approach was used to train an Artificial-Intelligence (AI) classifier; incorrect contouring cases were generated from the gold-standard MC datasets with translations, expansions and contractions. ROC curves and confusion matrices were used to evaluate the AI-classifier performance.ResultsTwenty radiomics features, were found to be robust across structures, showing a good/excellent intra-class correlation coefficient (ICC) index comparing MC/AC. A significant correlation was obtained with quantitative indexes (Dice-Index, Hausdorff-distance). The trained AI-classifier detected correct contours (CC) and not correct contours (NCC) with an accuracy of 82.6% and AUC of 0.91. True positive rate (TPR) was 85.1% and 81.3% for CC and NCC. Detection of NCC at this point of the development still depended strongly on degree of contouring imperfection.ConclusionsA set of radiomics features, robust on “gold-standard” contour and sensitive to incorrect contouring was identified and implemented in an AI-workflow to quantify segmentation accuracy. This workflow permits an automatic assessment of segmentation quality and may accelerate expansion of an existing autocontouring atlas database as well as improve dosimetric analyses of large treatment plan databases.     

A genetic algorithm approach to the inverse problem of treatment planning for intensity-modulated radiotherapy

A genetic algorithm optimization approach for designing treatment plans in intensity-modulated radiotherapy is proposed. The approach determines the beam intensities of the pencil-beam dose model such that the optimized dose distribution closely matches the prescribed dose distribution. The approach indirectly inverts the ill-conditioned dose-projection matrix, which can be very large and extremely sparse. The beam intensities are treated as chromosomes that are encoded as binary strings. The approach was used to design treatment plans for two deceptive clinical test cases. In both case, cancerous tissues in the planning target region received at least 98% of the prescribed dose level while dose levels delivered to the organs at risk were well within safe limits, with a maximum exposure of 2.5 and 52.5% of the prescribed tolerance level for the brain and prostrate cancer cases, respectively. Dose levels delivered to the healthy tissues were small with a mean exposure of 22.8 and 23.5% of the prescribed tolerance level.