Computed tomography imaging parameters for inhomogeneity correction in radiation treatment planning

Evaluating on-board kVCT- and MVCT-based dose calculation accuracy using a thorax phantom for helical tomotherapy treatments

Purpose.To evaluate the impact of CT number calibration and imaging parameter selection on dose calculation accuracy relative to the CT planning process in thoracic treatments for on-board helical CT imaging systems used in helical tomotherapy.Methods and Materials.Direct CT number calibrations were performed with appropriate protocols for each imaging system using an electron density phantom. Large volume and SBRT treatment plans were simulated and optimized for planning CT scans of an anthropomorphic thorax phantom and transferred to registered kVCT and MVCT scans of the phantom as appropriate. Relevant DVH metrics and dose-difference maps were used to evaluate and compare dose calculation accuracy relative to the planning CT based on a variation in imaging parameters applied for the on-board systems.Results.For helical kVCT scans of the thorax phantom, median differences in DVH parameters for the large volume treatment plan were less than ±1% with dose to the target volume either over- or underestimated depending on the imaging parameters utilized for CT number calibration and thorax phantom acquisition. For the lung SBRT plan calculated on helical kVCT scans, median dose differences were up to -2.7% with a more noticeable dependence on parameter selection. For MVCT scans, median dose differences for the large volume plan were within +2% with dose to the target overestimated regardless of the imaging protocol.Conclusion.Accurate dose calculations (median errors of <±1%) using a thorax phantom simulating realistic patient geometry and scatter conditions can be achieved with images acquired with a helical kVCT system on a helical tomotherapy unit. This accuracy is considerably improved relative to that achieved with the MV-based approach. In a clinical setting, careful consideration should be made when selecting appropriate kVCT imaging parameters for this process as dose calculation accuracy was observed to vary with both parameter selection and treatment type.

Diagnosis of Osteoporosis by Quantifying Volumetric Bone Mineral Density of Lumbar Vertebrae Using Abdominal CT Images and Two-Compartment Model

With the aging population, osteoporosis has become an important public health issue. The purpose of this study was to establish a two-compartment model (TCM) to quantify the volumetric bone mineral density (vBMD) of the lumbar spine using abdominal computed tomography (CT) images. The TCM approach uses water as the bone marrow equivalent and K₂HPO₄ solution as the cortical bone equivalent. A phantom study was performed to evaluate the accuracy of vBMD estimation at 100 kVp and 120 kVp. The data of 180 patients who underwent abdominal CT imaging and dual-energy X-ray absorptiometry (DXA) within one month were retrospectively collected. vBMD of L1-L4 vertebrae were calculated, and the receiver-operating characteristic curve analysis was performed to establish the diagnostic thresholds for osteoporosis and osteopenia in terms of vBMD. The average difference between the measured vBMD following TCM and the theoretical vBMD of the self-made phantom was 0.2%, and the maximum difference was 0.5%. vBMD of lumbar vertebrae obtained from TCM and aBMD obtained by DXA had a significant positive correlation (r = 0.655 to 0.723). The average diagnostic threshold for osteoporosis was 0.116 g/cm³. The sensitivity, specificity, and accuracy were 95.7%, 75.6.5%, and 80.0%, respectively. The average diagnostic threshold for osteopenia was 0.126 g/cm³. The sensitivity, specificity, and accuracy were 81.3%, 82.5%, and 82.7%, respectively. The aforementioned threshold values were used to perform the diagnostics on a test cohort, and the performance was equivalent to that in the experimental cohort. From the perspective of preventive medicine, opportunistic screening of bone mineral density using abdominal CT images and the TCM approach can facilitate early detection of osteoporosis and osteopenia and, with in-time treatment, slow down their progression.

The automated measurement of CT number linearity using an ACR accreditation phantom

We developed a software to automatically measure the linearity between the CT numbers and densities of objects using an ACR 464 CT phantom, and investigated the CT number linearity of 16 different CT scanners. The software included a segmentation-rotation method. After segmenting five objects within the phantom image, the software computed the mean CT number of each object and plotted a graph between the CT numbers and densities of the objects. Linear regression and coefficients of regression, R², were automatically calculated. The software was used to investigate the CT number linearity of 16 CT scanners from Toshiba, Siemens, Hitachi, and GE installed at 16 hospitals in Indonesia. The linearity of the CT number obtained on most of the scanners showed a strong linear correlation (R²> 0.99) between the CT numbers and densities of the five phantom materials. Two scanners (Siemens Emotion 16) had the strongest linear correlation withR²= 0.999, and two Hitachi Eclos scanners had the weakest linear correlation withR²< 0.99.

Towards Accurate and Precise Image-Guided Radiotherapy: Clinical Applications of the MR-Linac

Advances in image-guided radiotherapy have brought about improved oncologic outcomes and reduced toxicity. The next generation of image guidance in the form of magnetic resonance imaging (MRI) will improve visualization of tumors and make radiation treatment adaptation possible. In this review, we discuss the role that MRI plays in radiotherapy, with a focus on the integration of MRI with the linear accelerator. The MR linear accelerator (MR-Linac) will provide real-time imaging, help assess motion management, and provide online adaptive therapy. Potential advantages and the current state of these MR-Linacs are highlighted, with a discussion of six different clinical scenarios, leading into a discussion on the future role of these machines in clinical workflows.

Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning

Objective. Kilovoltage computed tomography (kVCT) is the cornerstone of radiotherapy treatment planning for delineating tissues and towards dose calculation. For the former, kVCT provides excellent contrast and signal-to-noise ratio. For the latter, kVCT may have greater uncertainty in determining relative electron density ( ρ e ) and proton stopping power ratio (SPR). Conversely, megavoltage CT (MVCT) may result in superior dose calculation accuracy. The purpose of this work was to convert kVCT HU to MVCT HU using deep learning to obtain higher accuracy ρ e and SPR. Approach. Tissue-mimicking phantoms were created to compare kVCT- and MVCT-determined ρ e and SPR to physical measurements. Using 100 head-and-neck datasets, an unpaired deep learning model was trained to learn the relationship between kVCTs and MVCTs, creating synthetic MVCTs (sMVCTs). Similarity metrics were calculated between kVCTs, sMVCTs, and MVCTs in 20 test datasets. An anthropomorphic head phantom containing bone-mimicking material with known composition was scanned to provide an independent determination of ρ e and SPR accuracy by sMVCT. Main results. In tissue-mimicking bone, ρ e errors were 2.20% versus 0.19% and SPR errors were 4.38% versus 0.22%, for kVCT versus MVCT, respectively. Compared to MVCT, in vivo mean difference (MD) values were 11 and 327 HU for kVCT and 2 and 3 HU for sMVCT in soft tissue and bone, respectively. ρ e MD decreased from 1.3% to 0.35% in soft tissue and 2.9% to 0.13% in bone, for kVCT and sMVCT, respectively. SPR MD decreased from 1.8% to 0.24% in soft tissue and 6.8% to 0.16% in bone, for kVCT and sMVCT, respectively. Relative to physical measurements, ρ e and SPR error in anthropomorphic bone decreased from 7.50% and 7.48% for kVCT to <1% for both MVCT and sMVCT. Significance. Deep learning can be used to map kVCT to sMVCT, suggesting higher accuracy ρ e and SPR is achievable with sMVCT versus kVCT.

The effect of variations in CT scan protocol on femoral finite element failure load assessment using phantomless calibration

Recently, it was shown that fracture risk assessment in patients with femoral bone metastases using Finite Element (FE) modeling can be performed using a calibration phantom or air-fat-muscle calibration and that non-patient-specific calibration was less favorable. The purpose of this study was to investigate if phantomless calibration can be used instead of phantom calibration when different CT protocols are used. Differences in effect of CT protocols on Hounsfield units (HU), calculated bone mineral density (BMD) and FE failure loads between phantom and two methods of phantomless calibrations were studied. Five human cadaver lower limbs were scanned atop a calibration phantom according to a standard scanning protocol and seven additional commonly deviating protocols including current, peak kilovoltage (kVp), slice thickness, rotation time, field of view, reconstruction kernel, and reconstruction algorithm. The HUs of the scans were calibrated to BMD (in mg/cm³) using the calibration phantom as well as using air-fat-muscle and non-patient-specific calibration, resulting in three models for each scan. FE models were created, and failure loads were calculated by simulating an axial load on the femur. HU, calculated BMD and failure load of all protocols were compared between the three calibration methods. The different protocols showed little variation in HU, BMD and failure load. However, compared to phantom calibration, changing the kVp resulted in a relatively large decrease of approximately 10% in mean HU and BMD of the trabecular and cortical region of interest (ROI), resulting in a 13.8% and 13.4% lower failure load when air-fat-muscle and non-patient-specific calibrations were used, respectively. In conclusion, while we observed significant correlations between air-fat-muscle calibration and phantom calibration as well as between non-patient-specific calibration and phantom calibration, our sample size was too small to prove that either of these calibration approaches was superior. Further studies are necessary to test whether air-fat-muscle or non-patient-specific calibration could replace phantom calibration in case of different scanning protocols.

The reliability of CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy simulation: A narrative review

BACKGROUND AND PURPOSE

The purpose of this review was to examine the reported factors that affect the reliability of Computed Tomography (CT) numbers and their impact on clinical applications in diagnostic scanning, dental imaging, and radiation therapy dose calculation.

METHODS

A comprehensive search of the literature was conducted using Medline (PubMed), Google Scholar, and Ovid databases which were searched using the keywords CT number variability, CT number accuracy and uniformity, tube voltage, patient positioning, patient off-centring, and size dependence. A narrative summary was used to compile the findings under the overarching theme.

DISCUSSION

A total of 47 articles were identified to address the aim of this review. There is clear evidence that CT numbers are highly dependent on the energy level applied based on the effective atomic number of the scanned tissue. Furthermore, body size and anatomical location have also indicated an influence on measured CT numbers, especially for high-density materials such as bone tissue and dental implants. Patient off-centring was reported during CT imaging, affecting dose and CT number reliability, which was demonstrated to be dependent on the shaping filter size.

CONCLUSION

CT number accuracy for all energy levels, body sizes, anatomical locations, and degrees of patient off-centring is observed to be a variable under certain common conditions. This has significant implications for several clinical applications. It is crucial for those involved in CT imaging to understand the limitations of their CT system to ensure radiologists and operators avoid potential pitfalls associated with using CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy dose calculation.

Effects of lung tissue characterization in radiotherapy of breast cancer under deep inspiration breath hold when using Monte Carlo dosimetry

PURPOSE

To investigate the sensitivity of Monte Carlo (MC) calculated lung dose distributions to lung tissue characterization in external beam radiotherapy of breast cancer under Deep Inspiration Breath Hold (DIBH).

METHODS

EGSnrc based MC software was employed. Mean lung densities for one hundred patients were analysed. CT number frequency and clinical dose distributions were calculated for 15 patients with mean lung density below 0.14 g/cm³. Lung volume with a pre-defined CT numbers was also considered. Lung tissue was characterized by applying different CT calibrations in the low-density region and air-lung tissue thresholds. Dose impact was estimated by Dose Volume Histogram (DVH) parameters.

RESULTS

Mean lung densities below 0.14 g/cm³ were found in 10% of the patients. CT numbers below -960 HU dominated the CT frequency distributions with a high rate of CT numbers at -990 HU. Mass density conversion approach influenced the DVH shape. V_4Gy and V_8Gy varied by 7% and 5% for the selected patients and by 9% and 3.5% for the pre-defined lung volume. V_16Gy and V_20Gy, were within 2.5%. Regions above 20 Gy were affected. Variations in air- lung tissue differentiation resulted in DVH parameters within 1%. Threshold at -990 HU was confirmed by the CT number frequency distributions.

CONCLUSIONS

Lung dose distributions were more sensitive to variations in the CT calibration curve below lung (inhale) density than to air-lung tissue differentiation. Low dose regions were mostly affected. The dosimetry effects were found to be potentially important to 10% of the patients treated under DIBH.

Evolution of materials for implants in metastatic spine disease till date - Have we found an ideal material?

"Metastatic Spine Disease" (MSD) often requires surgical intervention and instrumentation with spinal implants. Ti6Al4V is widely used in metastatic spine tumor surgery (MSTS) and is the current implant material of choice due to improved biocompatibility, mechanical properties, and compatibility with imaging modalities compared to stainless steel. However, it is still not the ideal implant material due to the following issues. Ti6Al4V implants cause stress-shielding as their Young's modulus (110 gigapascal [GPa]) is higher than cortical bone (17-21 GPa). Ti6Al4V also generates artifacts on CT and MRI, which interfere with the process of postoperative radiotherapy (RT), including treatment planning and delivery. Similarly, charged particle therapy is hindered in the presence of Ti6Al4V. In addition, artifacts on CT and MRI may result in delayed recognition of tumor recurrence and postoperative complications. In comparison, polyether-ether-ketone (PEEK) is a promising alternative. PEEK has a low Young's modulus (3.6 GPa), which results in optimal load-sharing and produces minimal artifacts on imaging with less hinderance on postoperative RT. However, PEEK is bioinert and unable to provide sufficient stability in the immediate postoperative period. This issue may possibly be mitigated by combining PEEK with other materials to form composites or through surface modification, although further research is required in these areas. With the increasing incidence of MSD, it is an opportune time for the development of spinal implants that possess all the ideal material properties for use in MSTS. Our review will explore whether there is a current ideal implant material, available alternatives and whether these require further investigation.

Implementation and experimental evaluation of Mega-voltage fan-beam CT using a linear accelerator

BACKGROUND

Mega-voltage fan-beam Computed Tomography (MV-FBCT) holds potential in accurate determination of relative electron density (RED) and proton stopping power ratio (SPR) but is not widely available.

OBJECTIVE

To demonstrate the feasibility of MV-FBCT using a medical linear accelerator (LINAC) with a 2.5 MV imaging beam, an electronic portal imaging device (EPID) and multileaf collimators (MLCs).

METHODS

MLCs were used to collimate MV beam along z direction to enable a 1 cm width fan-beam. Projection data were acquired within one gantry rotation and preprocessed with in-house developed artifact correction algorithms before the reconstruction. MV-FBCT data were acquired at two dose levels: 30 and 60 monitor units (MUs). A Catphan 604 phantom was used to evaluate basic image quality. A head-sized CIRS phantom with three configurations of tissue-mimicking inserts was scanned and MV-FBCT Hounsfield unit (HU) to RED calibration was established for each insert configuration using linear regression. The determination coefficient ([Formula: see text]) was used to gauge the accuracy of HU-RED calibration. Results were compared with baseline single-energy kilo-voltage treatment planning CT (TP-CT) HU-RED calibration which represented the current standard clinical practice.

RESULTS

The in-house artifact correction algorithms effectively suppressed ring artifact, cupping artifact, and CT number bias in MV-FBCT. Compared to TP-CT, MV-FBCT was able to improve the prediction accuracy of the HU-RED calibration curve for all three configurations of insert materials, with [Formula: see text] > 0.9994 and [Formula: see text] < 0.9990 for MV-FBCT and TP-CT HU-RED calibration curves of soft-tissue inserts, respectively. The measured mean CT numbers of blood-iodine mixture inserts in TP-CT drastically deviated from the fitted values but not in MV-FBCT. Reducing the radiation level from 60 to 30 MU did not decrease the prediction accuracy of the MV-FBCT HU-RED calibration curve.

CONCLUSION

We demonstrated the feasibility of MV-FBCT and its potential in providing more accurate RED estimation.

An efficient planning technique for low dose whole lung radiation therapy for covid-19 pandemic patients

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An efficient low dose whole lung RT technique developed for severe COVID-19 patients.

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Empirical MU Calculation formula fitted from actual CT images of clinical patients.

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Acceptable dose distribution verified by 3D dose calculation in real patient anatomy.

This study aimed to establish an efficient planning technique for low dose whole lung treatment that can be implemented rapidly and safely. The treatment technique developed here relied only on chest radiograph and a simple empirical monitor unit calculation formula. The 3D dose calculation in real patient anatomy, including both nonCOVID and COVID-19 patients, which took into account tissue heterogeneity showed that the dose delivered to lungs had reasonable uniformity even with this simple and quick setup.

Measurement of radiation attenuation parameters of modified defatted soy flour-soy protein isolate-based mangrove wood particleboards to be used for CT phantom production

For the first time, Rhizophora spp. (Rh. spp.) particleboard phantoms were developed using defatted soy flour (DSF) and soy protein isolate (SPI) modified by sodium hydroxide and itaconic acid polyamidoamine-epichlorohydrin (IA-PAE) adhesive. The microstructural characterization and X-ray diffraction patterns of the material revealed that the modified DSF and SPI adhesives became more compact and homogeneous when NaOH/IA-PAE was added, which prevented damage by moisture. It was confirmed that the composite is crystalline with (101), (002), and (004) orientations. Phantoms made of this material were scanned with X-ray computed tomography (CT) typically used for abdominal examinations with varying energies corresponding to 80, 120, and 135 kVp, to determine CT numbers, electron densities, and density distribution profiles. The radiation attenuation parameters were found to be not significantly different from those of water (XCOM) with p values [Formula: see text] 0.05 for DSF and SPI. The DSF- and SPI-based particleboard phantoms showed CT numbers close to those of water at the three X-ray CT energies. In addition, electron density and density distribution profiles of DSF-SPI-Rh. spp. particleboard phantoms with 15 wt% IA-PAE content were even closer to those of water and other commercial phantom materials at the three X-ray CT energies. It is concluded that DSF-SPI with NaOH/IA-PAE added can be used as a potential adhesive in Rh. spp. particleboard phantoms for radiation dosimetry.

A comparison study between single- and dual-energy CT density extraction methods for neurological proton monte carlo treatment planning

Monte Carlo proton dose calculations requires mass densities calculated from the patient CT image. This work investigates the impact of different single-energy CT (SECT) and dual-energy CT (DECT) to density conversion methods in proton dose distributions for brain tumours.Material and methods: Head CT scans for four patients were acquired in SECT and DECT acquisition modes. Commercial software was used to reconstruct DirectDensity^™ images in Relative Electron Densities (RED, [Formula: see text]) and to obtain DECT-based pseudo-monoenergetic images (PMI). PMI and SECT images were converted to RED using piecewise linear interpolations calibrated on a head-sized phantom, these fits were referred to as "PMI2RED" and "CT2RED". Two DECT-based calibration methods ("Hünemohr-15it" and "Saito-15it") were also investigated. [Formula: see text] images were converted to mass-densities ([Formula: see text]) to investigate [Formula: see text]differences and one representative patient case was used to make a proton treatment plan. Using CT2RED as reference method, dose distribution differences in the target and in five organs-at-risk (OARs) were quantified.Results: In the phantom study, Saito-15it and Hünemohr-15it produced the lowest [Formula: see text]root-mean-square error (0.7%) and DirectDensity^™ the highest error (2.7%). The proton plan evaluated in the Saito-15it and Hünemohr-15it datasets showed the largest relative differences compared to initial CT2RED plan down to -6% of the prescribed dose. Compared to CT2RED, average range differences were calculated: -0.1 ± 0.3 mm for PMI2RED; -0.8 ± 0.4 mm for Hünemohr-15it, and -1.2 ± 0.4 mm for Saito-15it.Conclusion: Given the wide choice of available conversion methods, studies investigating the density accuracy for proton dose calculations are necessary. However, there is still a gap between performing accuracy studies in reference [Formula: see text]phantoms and applying these methods in human CT images. For this treatment case, the PMI2RED method was equivalent to the conventional CT2RED method in terms of dose distribution, CTV coverage and OAR sparing, whereas Hünemohr-15it and Saito-15it presented the largest differences.

Technical Report: Diagnostic Scan-Based Planning (DSBP), A Method to Improve the Speed and Safety of Radiation Therapy for the Treatment of Critically Ill Patients

PURPOSE

Treating critically ill patients in radiation oncology departments poses multiple safety risks. This study describes a method to improve the speed of radiation treatment for patients in the intensive care unit by eliminating the need for computed tomography (CT) simulation or on-table treatment planning using patients' previously acquired diagnostic CT scans.

METHODS AND MATERIALS

Initially, a retrospective planning study was performed to assess the applicability and safety of diagnostic scan-based planning (DSBP) for 3 typical indications for radiation therapy in patients in the intensive care unit: heterotopic ossification (10), spine metastases (cord compression; 10), and obstructive lung lesions (5). After identification of an appropriate diagnostic CT scan, treatment planning was performed using the diagnostic scan data set. These treatment plans were then transferred to the patients' simulation scans, and a dosimetric comparison was performed between the 2 sets of plans. Additionally, a time study of the first 10 patients treated with DSBP in our department was performed.

RESULTS

The retrospective analysis demonstrated that DSBP resulted in treatment plans that, when transferred to the CT simulation data sets, provided excellent target coverage, a median D_95% of 96% (range, 86%-100%) of the prescription dose with acceptable hot spots, and a median D_max108% (range, 102%-113%). Subsequently, DSBP has been used for 10 critically ill patients. The patients were treated without CT simulation, and the median time between patient check-in to the department and completion of radiation therapy was 28 minutes (range, 18-47 minutes.) CONCLUSIONS: This study demonstrates that it is possible to safely use DSBP for the treatment of critically ill patients. This method has the potential to simplify the treatment process and improve the speed and safety of treatment.

Hematoma Segmentation Using Dilated Convolutional Neural Network

Traumatic brain injury (TBI) is a global health challenge. Accurate and fast automatic detection of hematoma in the brain is essential for TBI diagnosis and treatment. In this study, we developed a fully automated system to detect and segment hematoma regions in head Computed Tomography (CT) images of patients with acute TBI. We adapted the structure of a fully convolutional network by introducing dilated convolution and removing down-sampling and up-sampling layers. Skip layers are also used to combine low-level features and high-level features. By integrating the information from different scales without losing spatial resolution, the network can perform more accurate segmentation. Our final hematoma segmentations achieved the Dice, sensitivity, and specificity of 0.62, 0.81, and 0.96, respectively, which outperformed the results from previous methods.

Determination of computed tomography number of high-density materials in 12-bit, 12-bit extended and 16-bit depth for dosimetric calculation in treatment planning system

Aim

The main aim was to examine the effect of bit depth on computed tomography (CT) number for high-density materials. Analysis of the CT number for high-density materials using 16-bit scanners will extend the CT scale that currently exists for 12-bit scanners and thus will be beneficial for use in CT–electron density (ED) curve in radiotherapy treatment planning system (TPS). Implementation of this extended CT scale will compensate for tissue heterogeneity during CT–ED conversion in treatment planning.

Materials and methods

An in-house built phantom with 10 different metal samples was scanned using 80, 100 and 120 kVp in two different CT scanners. A region of interest was set at the centre of the material and the mean CT numbers together with data deviation were determined. Dosimetry calculation was performed by applying a direct anterior beam on 12-bit, 12-bit extended and 16-bit.

Results

High-density materials (&gt;4·34 g cm−3) in 16-bit depth provide disparities up to 44% compared to Siemens’ 12-bit extended. Influence of tube voltage showed a significant difference (p&lt;0·05) in both bit depth and CT number of the gold and amalgam saturated in 16-bit depth. A 120 kVp energy illustrated a low variation on CT number for different scanners, but dosimetry calculation showed significant disparities at the metal interface in 12-bit, 12-bit extended and 16-bit.

Findings

High-density materials require 16-bit scanners to obtain CT number to be implemented in treatment planning in radiotherapy. This also suggests that proper tube voltage together with correct CT–ED resulted in accurate TPS algorithm calculation.

Role and future of MRI in radiation oncology

Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis-a field known as Radiomics-thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.

The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations

Background and Purpose

A key step in electron Monte Carlo dose calculation requires converting Computed Tomography (CT) numbers from a tomographic acquisition to a mass density. This study investigates the dosimetric consequences of perturbations applied to a calibration table between CT number and mass density.

Materials and Methods

A literature search was performed to define lower and upper bounds for physically reasonable perturbations to a reference CT number to mass density calibration table. Electron beam dose was calculated for ten patients using these variations and the results were compared to clinical plans originally derived with a reference calibration table. Dose differences both globally and in the Planning Target Volume (PTV) were assessed using dose- and volume-based metrics and 3- dimensional gamma analysis for each patient.

Results

Small but statistically significant differences were observed between perturbations and reference data for certain metrics including volume of the 50% prescription isodose. Upper and lower variations in CT number to mass density calibration yielded mean values of V50% that were 4.4% larger and 2.1% smaller than reference values respectively. Gamma analysis using 3%/3mm criteria indicated >99% passing rate for the PTV for all patients. Global gamma analysis for some patients showed larger discrepancies possibly due to large electron path lengths through inhomogeneities.

Conclusions

In most patients, physically reasonable perturbations in CT number to mass density curves will not induce clinically significant impact on calculated target dose distributions. Strong dependence of electron transport on voxel material may produce dose speckle throughout the volume. Care should be taken in evaluating critical structures at depths beyond the target volume in highly heterogeneous regions.

Emerging role of MRI in radiation therapy

Advances in multimodality imaging, providing accurate information of the irradiated target volume and the adjacent critical structures or organs at risk (OAR), has made significant improvements in delivery of the external beam radiation dose. Radiation therapy conventionally has used computed tomography (CT) imaging for treatment planning and dose delivery. However, magnetic resonance imaging (MRI) provides unique advantages: added contrast information that can improve segmentation of the areas of interest, motion information that can help to better target and deliver radiation therapy, and posttreatment outcome analysis to better understand the biologic effect of radiation. To take advantage of these and other potential advantages of MRI in radiation therapy, radiologists and MRI physicists will need to understand the current radiation therapy workflow and speak the same language as our radiation therapy colleagues. This review article highlights the emerging role of MRI in radiation dose planning and delivery, but more so for MR-only treatment planning and delivery. Some of the areas of interest and challenges in implementing MRI in radiation therapy workflow are also briefly discussed. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;48:1468-1478.

Dosimetric evaluation of magnetic resonance-generated synthetic CT for radiation treatment of rectal cancer

Purpose

The purpose of this study was to assess the dosimetric equivalence of magnetic resonance (MR)-generated synthetic CT (synCT) and simulation CT for treatment planning in radiotherapy of rectal cancer.

Methods

This study was conducted on eleven patients who underwent whole-body PET/MR and PET/CT examination in a prospective IRB-approved study. For each patient synCT was generated from Dixon MR using a model-based method. Standard treatment planning directives were used to create a four-field box (4F), an oblique four-field (O4F) and a volumetric modulated arc therapy (VMAT) plan on synCT for treatment of rectal cancer. The plans were recalculated on CT with the same monitor units (MUs) as that of synCT. Dose-volume metrics of planning target volume (PTV) and organs at risk (OARs) as well as gamma analysis of dose distributions were evaluated to quantify the difference between synCT and CT plans. All plans were calculated using the analytical anisotropic algorithm (AAA). The VMAT plans on synCT and CT were also calculated using the Acuros XB algorithm for comparison with the AAA calculation.

Results

Medians of absolute differences in PTV metrics between synCT and CT plans were 0.2%, 0.2% and 0.3% for 4F, O4F and VMAT respectively. No significant differences were observed in OAR dose metrics including bladder V40Gy, mean dose in bladder, bowel V45Gy and femoral head V30Gy in any techniques. Gamma analysis with 2%/2mm dose difference/distance to agreement criteria showed median passing rates of 99.8% (range: 98.5 to 100%), 99.9% (97.2 to 100%), and 99.9% (99.4 to 100%) for 4F, O4F and VMAT, respectively. Using Acuros XB dose calculation, 2%/2mm gamma analysis generated a passing rate of 99.2% (97.7 to 99.9%) for VMAT plans.

Conclusion

SynCT enabled dose calculation equivalent to conventional CT for treatment planning of 3D conformal treatment as well as VMAT of rectal cancer. The dosimetric agreement between synCT and CT calculated doses demonstrated the potential of MR-only treatment planning for rectal cancer using MR generated synCT.

Dosimetric impact of gastrointestinal air column in radiation treatment of pancreatic cancer

OBJECTIVE

Dosimetric evaluation of air column in gastrointestinal (GI) structures in intensity modulated radiation therapy (IMRT) of pancreatic cancer.

METHODS

Nine sequential patients were retrospectively chosen for dosimetric analysis of air column in the GI apparatus in pancreatic cancer using cone beam CT (CBCT). The four-dimensional CT (4DCT) was used for target and organs at risk (OARs) and non-coplanar IMRT was used for treatment. Once a week, these patients underwent CBCT for air filling, isocentre verification and dose calculations retrospectively.

RESULTS

Abdominal air column variation was as great as ±80% between weekly CBCT and 4DCT. Even with such a large air column in the treatment path for pancreatic cancer, changes in anteroposterior dimension were minimal (2.8%). Using IMRT, variations in air column did not correlate dosimetrically with large changes in target volume. An average dosimetric deviation of mere -3.3% and a maximum of -5.5% was observed.

CONCLUSION

CBCT revealed large air column in GI structures; however, its impact is minimal for target coverage. Because of the inherent advantage of segmentation in IMRT, where only a small fraction of a given beam passes through the air column, this technique might have an advantage over 3DCRT in treating upper GI malignancies where the daily air column can have significant impact. Advances in knowledge: Radiation treatment of pancreatic cancer has significant challenges due to positioning, imaging of soft tissues and variability of air column in bowels. The dosimetric impact of variable air column is retrospectively studied using CBCT. Even though, the volume of air column changes by ± 80%, its dosimetric impact in IMRT is minimum.

Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer

Background

Interest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer.

Methods

Eleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions.

Results

Mean differences between PTV doses on synCT and CT across all the plans were −0.1% ± 0.4%, 0.1% ± 0.5%, and 0.4% ± 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of −0.14 ± 0.07 Gy, 0.0% ± 0.1%, and −0.1% ± 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% ± 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan.

Conclusions

The synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.