An adaptive proton therapy workflow using cone beam computed tomography (CBCT) is proposed. It consists of an online evaluation of a fast range-corrected dose distribution based on a virtual CT (vCT) ...scan. This can be followed by more accurate offline dose recalculation on the vCT scan, which can trigger a rescan CT (rCT) for replanning.
The workflow was tested retrospectively for 20 consecutive lung cancer patients. A diffeomorphic Morphon algorithm was used to generate the lung vCT by deforming the average planning CT onto the CBCT scan. An additional correction step was applied to account for anatomic modifications that cannot be modeled by deformation alone. A set of clinical indicators for replanning were generated according to the water equivalent thickness (WET) and dose statistics and compared with those obtained on the rCT scan. The fast dose approximation consisted of warping the initial planned dose onto the vCT scan according to the changes in WET. The potential under- and over-ranges were assessed as a variation in WET at the target's distal surface.
The range-corrected dose from the vCT scan reproduced clinical indicators similar to those of the rCT scan. The workflow performed well under different clinical scenarios, including atelectasis, lung reinflation, and different types of tumor response. Between the vCT and rCT scans, we found a difference in the measured 95% percentile of the over-range distribution of 3.4 ± 2.7 mm. The limitations of the technique consisted of inherent uncertainties in deformable registration and the drawbacks of CBCT imaging. The correction step was adequate when gross errors occurred but could not recover subtle anatomic or density changes in tumors with complex topology.
A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.
Purpose:
The aim of this study was to evaluate the appropriateness of using computed tomography (CT) to cone-beam CT (CBCT) deformable image registration (DIR) for the application of calculating the ...“dose of the day” received by a head and neck patient.
Methods:
NiftyReg is an open-source registration package implemented in our institution. The affine registration uses a Block Matching-based approach, while the deformable registration is a GPU implementation of the popular B-spline Free Form Deformation algorithm. Two independent tests were performed to assess the suitability of our registrations methodology for “dose of the day” calculations in a deformed CT. A geometric evaluation was performed to assess the ability of the DIR method to map identical structures between the CT and CBCT datasets. Features delineated in the planning CT were warped and compared with features manually drawn on the CBCT. The authors computed the dice similarity coefficient (DSC), distance transformation, and centre of mass distance between features. A dosimetric evaluation was performed to evaluate the clinical significance of the registrations errors in the application proposed and to identify the limitations of the approximations used. Dose calculations for the same intensity-modulated radiation therapy plan on the deformed CT and replan CT were compared. Dose distributions were compared in terms of dose differences (DD), gamma analysis, target coverage, and dose volume histograms (DVHs). Doses calculated in a rigidly aligned CT and directly in an extended CBCT were also evaluated.
Results:
A mean value of 0.850 in DSC was achieved in overlap between manually delineated and warped features, with the distance between surfaces being less than 2 mm on over 90% of the pixels. Deformable registration was clearly superior to rigid registration in mapping identical structures between the two datasets. The dose recalculated in the deformed CT is a good match to the dose calculated on a replan CT. The DD is smaller than 2% of the prescribed dose on 90% of the body's voxels and it passes a 2% and 2 mm gamma-test on over 95% of the voxels. Target coverage similarity was assessed in terms of the 95%-isodose volumes. A mean value of 0.962 was obtained for the DSC, while the distance between surfaces is less than 2 mm in 95.4% of the pixels. The method proposed provided adequate dose estimation, closer to the gold standard than the other two approaches. Differences in DVH curves were mainly due to differences in the OARs definition (manual vs warped) and not due to differences in dose estimation (dose calculated in replan CT vs dose calculated in deformed CT).
Conclusions:
Deforming a planning CT to match a daily CBCT provides the tools needed for the calculation of the “dose of the day” without the need to acquire a new CT. The initial clinical application of our method will be weekly offline calculations of the “dose of the day,” and use this information to inform adaptive radiotherapy (ART). The work here presented is a first step into a full implementation of a “dose-driven” online ART.
Purpose
The purpose of this work is to evaluate the performance of dual‐energy CT (DECT) for determining proton stopping power ratios (SPRs) in an experimental environment and to demonstrate its ...potential advantages over conventional single‐energy CT (SECT) in clinical conditions.
Methods
Water equivalent range (WER) measurements of 12 tissue‐equivalent plastic materials and 12 fresh animal tissue samples are performed in a 195 MeV broad proton beam using the dose extinction method. SECT and DECT scans of the samples are performed with a dual‐source CT scanner (Siemens SOMATOM Definition Flash). The methods of Schneider et al. (1996), Bourque et al. (2014), and Lalonde et al. (2017) are used to predict proton SPR on SECT and DECT images. From predicted SPR values, the WER of the proton beam through the sample is predicted for SECT and DECT using Monte Carlo simulations and compared to the measured WER.
Results
For homogeneous tissue‐equivalent plastic materials, results with DECT are consistent with experimental measurements and show a systematic reduction of SPR uncertainty compared to SECT, with root‐mean‐square errors of 1.59% versus 0.61% for SECT and DECT, respectively. Measurements with heterogeneous animal samples show a clear reduction of the bias on range predictions in the presence of bones, with −0.88% for SECT versus −0.58% and −0.14% for both DECT methods. An uncertainty budget allows isolating the effect of CT number conversion to SPR and predicts improvements by DECT over SECT consistently with theoretical predictions, with 0.34% and 0.31% for soft tissues and bones in the experimental setup compared to 0.34% and 1.14% with the theoretical method.
Conclusions
The present work uses experimental measurements in a realistic clinical environment to show potential benefits of DECT for proton therapy treatment planning. Our results show clear improvements over SECT in tissue‐equivalent plastic materials and animal tissues. Further work towards using Monte Carlo simulations for treatment planning with DECT data and a more detailed investigation of the uncertainties on I‐value and limitations on the Bragg additivity rule could potentially further enhance the benefits of this imaging technology for proton therapy.
Purpose:
The aims of this work were to evaluate the performance of several deformable image registration (DIR) algorithms implemented in our in‐house software (NiftyReg) and the uncertainties ...inherent to using different algorithms for dose warping.
Methods:
The authors describe a DIR based adaptive radiotherapy workflow, using CT and cone‐beam CT (CBCT) imaging. The transformations that mapped the anatomy between the two time points were obtained using four different DIR approaches available in NiftyReg. These included a standard unidirectional algorithm and more sophisticated bidirectional ones that encourage or ensure inverse consistency. The forward (CT‐to‐CBCT) deformation vector fields (DVFs) were used to propagate the CT Hounsfield units and structures to the daily geometry for “dose of the day” calculations, while the backward (CBCT‐to‐CT) DVFs were used to remap the dose of the day onto the planning CT (pCT). Data from five head and neck patients were used to evaluate the performance of each implementation based on geometrical matching, physical properties of the DVFs, and similarity between warped dose distributions. Geometrical matching was verified in terms of dice similarity coefficient (DSC), distance transform, false positives, and false negatives. The physical properties of the DVFs were assessed calculating the harmonic energy, determinant of the Jacobian, and inverse consistency error of the transformations. Dose distributions were displayed on the pCT dose space and compared using dose difference (DD), distance to dose difference, and dose volume histograms.
Results:
All the DIR algorithms gave similar results in terms of geometrical matching, with an average DSC of 0.85 ± 0.08, but the underlying properties of the DVFs varied in terms of smoothness and inverse consistency. When comparing the doses warped by different algorithms, we found a root mean square DD of 1.9% ± 0.8% of the prescribed dose (pD) and that an average of 9% ± 4% of voxels within the treated volume failed a 2%pD DD‐test (DD2%‐pp). Larger DD2%‐pp was found within the high dose gradient (21% ± 6%) and regions where the CBCT quality was poorer (28% ± 9%). The differences when estimating the mean and maximum dose delivered to organs‐at‐risk were up to 2.0%pD and 2.8%pD, respectively.
Conclusions:
The authors evaluated several DIR algorithms for CT‐to‐CBCT registrations. In spite of all methods resulting in comparable geometrical matching, the choice of DIR implementation leads to uncertainties in dose warped, particularly in regions of high gradient and/or poor imaging quality.
In order to maximize the potential of nanoparticles (NPs) in cancer imaging and therapy, their mechanisms of interaction with host tissue need to be fully understood. NP uptake is known to be ...dramatically influenced by the tumor microenvironment, and an imaging platform that could replicate in vivo cellular conditions would make big strides in NP uptake studies. Here, a novel NP uptake platform consisting of a tissue‐engineered 3D in vitro cancer model (tumoroid), which mimics the microarchitecture of a solid cancer mass and stroma, is presented. As the tumoroid exhibits fundamental characteristics of solid cancer tissue and its cellular and biochemical parameters are controllable, it provides a real alternative to animal models. Furthermore, an X‐ray fluorescence imaging system is developed to demonstrate 3D imaging of GNPs and to determine uptake efficiency within the tumoroid. This platform has implications for optimizing the targeted delivery of NPs to cells to benefit cancer diagnostics and therapy.
A novel 3D biomimetic tumour model and custom‐made nanoparticle imager is presented as a platform for nanoparticle uptake studies. The model comprises a dense cancer mass with stroma, each with engineerable characteristics. Cancer versus stromal cellular uptake of gold nanoparticles within the model is quantified and 3D imaged, the delineated cancer mass emitting five times more than the surrounding stroma.
Materials with a high atomic number (Z) are shown to cause an increase in the level of cell kill by ionizing radiation when introduced into tumor cells. This study uses in vitro experiments to ...investigate the differences in radiosensitization between two cell lines (MCF‐7 and U87) and three commercially available nanoparticles (gold, gadolinium, and iron oxide) irradiated by 6 MV X‐rays. To assess cell survival, clonogenic assays are carried out for all variables considered, with a concentration of 0.5 mg mL−1 for each nanoparticle material used. This study demonstrates differences in cell survival between nanoparticles and cell line. U87 shows the greatest enhancement with gadolinium nanoparticles (2.02 ± 0.36), whereas MCF‐7 cells have higher enhancement with gold nanoparticles (1.74 ± 0.08). Mass spectrometry, however, shows highest elemental uptake with iron oxide and U87 cells with 4.95 ± 0.82 pg of iron oxide per cell. A complex relationship between cellular elemental uptake is demonstrated, highlighting an inverse correlation with the enhancement, but a positive relation with DNA damage when comparing the same nanoparticle between the two cell lines.
This study investigates the enhancement effect of nanoparticles combined with radiotherapy, relating both cell survival and DNA damage to cellular elemental uptake. Different nanoparticles and cancer cells are used, where in all cases, nanoparticles cause a level of enhancement. The complexity in enhancement with increasing uptake can be seen, highlighting different mechanisms contributing to the enhancement effect.
Nasopharyngeal carcinoma (NPC) is a malignant epithelial tumor, most commonly located in the pharyngeal recess and endemic to parts of Asia. It is often detected at a late stage which is associated ...with poor prognosis (5-year survival rate of 63%). Treatment for this malignancy relies predominantly on radiotherapy and/or systemic chemotherapy, which can be associated with significant morbidity and impaired quality of life. In endemic regions NPC is associated with infection by Epstein-Barr virus (EBV) which was shown to upregulate the somatostatin receptor 2 (SSTR2) cell surface receptor. With recent advances in molecular techniques allowing for an improved understanding of the molecular aetiology of this disease and its relation to SSTR2 expression, we provide a comprehensive and up-to-date overview of this disease and highlight the emergence of SSTR2 as a key tumor biomarker and promising target for imaging and therapy.
This paper describes the potential application of an active pixel sensor-based x-ray diffraction (APXRD) system in the field of breast cancer diagnosis. The design and initial testing of the system ...was reported previously (Bohndiek et al 2008b Phys. Med. Biol. 53 655-72). The system has potential both as a 'diffraction enhanced breast imager' (DEBI) and as a probe for quantitative analysis of breast biopsy samples. The resolution of the system in a DEBI arrangement is 1 mm and the contrast available using a material-specific x-ray diffraction image was found to be up to seven times greater than that of a transmission image. Scatter signatures from a series of biopsy-equivalent samples, ranging in composition from 100% fat to 100% fibrous tissue, were acquired with the APXRD system. Multivariate data analysis was used to produce a partial least squares (PLS) model sensitive to sample fat content. The final model is able to accurately predict the fat content of a series of unknown samples and is robust to significant added noise. This suggests that the APXRD system could provide a simple, semi-automated, quantitative measurement system for analysis of breast biopsy samples. Training on a range of scatter signatures from real breast biopsy samples covering various stages of disease is now needed to test this hypothesis.
Purpose
Dual‐energy CT (DECT) promises improvements in estimating stopping power ratios (SPRs) for proton therapy treatment planning. Although several comparable mathematical formalisms have been ...proposed in literature, the optimal techniques to characterize human tissue SPRs with DECT in a clinical environment are not fully established. The aim of this work is to compare the most robust DECT methods against conventional single‐energy CT (SECT) in conditions reproducing a clinical environment, where CT artifacts and noise play a major role on the accuracy of these techniques.
Methods
Available DECT tissue characterization methods are investigated and their ability to predict SPRs is compared in three contexts: (a) a theoretical environment using the XCOM cross section database; (b) experimental data using a dual‐source CT scanner on a calibration phantom; (c) simulations of a virtual humanoid phantom with the ImaSim software. The latter comparison accounts for uncertainties caused by CT artifacts and noise, but leaves aside other sources of uncertainties such as CT grid size and the I‐values. To evaluate the clinical impact, a beam range calculation model is used to predict errors from the probability distribution functions determined with ImaSim simulations. Range errors caused by SPR errors in soft tissues and bones are investigated.
Results
Range error estimations demonstrate that DECT has the potential of reducing proton beam range uncertainties by 0.4% in soft tissues using low noise levels of 12 and 8 HU in DECT, corresponding to 7 HU in SECT. For range uncertainties caused by the transport of protons through bones, the reduction in range uncertainties for the same levels of noise is found to be up to 0.6 to 1.1 mm for bone thicknesses ranging from 1 to 5 cm, respectively. We also show that for double the amount noise, i.e., 14 HU in SECT and 24 and 16 HU for DECT, the advantages of DECT in soft tissues are lost over SECT. In bones however, the reduction in range uncertainties is found to be between 0.5 and 0.9 mm for bone thicknesses ranging from 1 to 5 cm, respectively.
Conclusion
DECT has a clear potential to improve proton beam range predictions over SECT in proton therapy. However, in the current state high levels of noise remain problematic for DECT characterization methods and do not allow getting the full benefits of this technology. Future work should focus on adapting DECT methods to noise and investigate methods based on raw‐data to reduce CT artifacts.
X-ray diffraction studies give material-specific information about biological tissue. Ideally, a large area, low noise, wide dynamic range digital x-ray detector is required for laboratory-based ...x-ray diffraction studies. The goal of this work is to introduce a novel imaging technology, the CMOS active pixel sensor (APS) that has the potential to fulfil all these requirements, and demonstrate its feasibility for coherent scatter imaging. A prototype CMOS APS has been included in an x-ray diffraction demonstration system. An industrial x-ray source with appropriate beam filtration is used to perform angle dispersive x-ray diffraction (ADXRD). Optimization of the experimental set-up is detailed including collimator options and detector operating parameters. Scatter signatures are measured for 11 different materials, covering three medical applications: breast cancer diagnosis, kidney stone identification and bone mineral density calculations. Scatter signatures are also recorded for three mixed samples of known composition. Results are verified using two independent models for predicting the APS scatter signature: (1) a linear systems model of the APS and (2) a linear superposition integral combining known monochromatic scatter signatures with the input polychromatic spectrum used in this case. Cross validation of experimental, modelled and literature results proves that APS are able to record biologically relevant scatter signatures. Coherent scatter signatures are sensitive to multiple materials present in a sample and provide a means to quantify composition. In the future, production of a bespoke APS imager for x-ray diffraction studies could enable simultaneous collection of the transmitted beam and scattered radiation in a laboratory-based coherent scatter system, making clinical transfer of the technique attainable.
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