CT beam dosimetric characterization procedure for personalized dosimetry

Cone beam CT doses in radiotherapy patient positioning in Finland-prostate treatments

Imaging parameters, frequencies and resulting patient organ doses in treatments of prostate cancer were assessed in Finnish radiotherapy centres. Based on a questionnaire to the clinics, Monte Carlo method was used to estimate organ doses in International Commission on Radiological Protection standard phantom for prostate, bladder, rectum and femoral head. The results show that doses from cone beam computed tomography imaging have reduced compared to earlier studies and are between 3.6 and 34.5 mGy per image for the above-mentioned organs and for normal sized patients. There still is room for further optimization of the patient exposure, as many centres use the default imaging parameters, and the length of the imaged region may not be optimal for the purpose.

Implementation of a new EGSnrc particle source class for computed tomography: validation and uncertainty quantification

Objective. Personalized dose monitoring and risk management are of increasing significance with the growing number of computer tomography (CT) examinations. These require high-quality Monte Carlo (MC) simulations that are of the utmost importance for the new developments in personalized CT dosimetry. This work aims to extend the MC framework EGSnrc source code with a new particle source. This, in turn, allows CT-scanner-specific dose and image calculations for any CT scanner. The novel method can be used with all modern EGSnrc user codes, particularly for the simulation of the effective dose based on DICOM images and the calculation of CT images.Approach. The new particle source can be used with input data derived by the user. The input data can be generated by the user based on a previously developed method for the experimental characterization of any CT scanner (doi.org/10.1016/j.ejmp.2015.09.006). Furthermore, the new particle source was benchmarked by air kerma measurements in an ionization chamber at a clinical CT scanner. For this, the simulated angular distribution and attenuation characteristics were compared to measurements to verify the source output free in air. In a second validation step, simulations of air kerma in a homogenous cylindrical and an anthropomorphic thorax phantom were performed and validated against experimentally determined results. A detailed uncertainty evaluation of the simulated air kerma values was developed.Main results. We successfully implemented a new particle source class for the simulation of realistic CT scans. This method can be adapted to any CT scanner. For the attenuation characteristics, there was a maximal deviation of 6.86% between the measurement and the simulation. The mean deviation for all tube voltages was 2.36% (σ= 1.6%). For the phantom measurements and simulations, all the values agreed within 5.0%. The uncertainty evaluation resulted in an uncertainty of 5.5% (k=1).

Organ dose prediction for patients undergoing radiotherapy CBCT chest examinations using artificial intelligence

PURPOSE

To propose an artificial intelligence (AI)-based method for personalized and real-time dosimetry for chest CBCT acquisitions.

METHODS

CT images from 113 patients who underwent radiotherapy treatment were collected for simulating thorax examinations using cone-beam computed tomography (CBCT) with the Monte Carlo technique. These simulations yielded organ dose data, used to train and validate specific AI algorithms. The efficacy of these AI algorithms was evaluated by comparing dose predictions with the actual doses derived from Monte Carlo simulations, which are the ground truth, utilizing Bland-Altman plots for this comparative analysis.

RESULTS

The absolute mean discrepancies between the predicted doses and the ground truth are (0.9 ± 1.3)% for bones, (1.2 ± 1.2)% for the esophagus, (0.5 ± 1.3)% for the breast, (2.5 ± 1.4)% for the heart, (2.4 ± 2.1)% for lungs, (0.8 ± 0.6)% for the skin, and (1.7 ± 0.7)% for integral. Meanwhile, the maximum discrepancies between the predicted doses and the ground truth are (14.4 ± 1.3)% for bones, (12.9 ± 1.2)% for the esophagus, (9.4 ± 1.3)% for the breast, (14.6 ± 1.4)% for the heart, (21.2 ± 2.1)% for lungs, (10.0 ± 0.6)% for the skin, and (10.5 ± 0.7)% for integral.

CONCLUSIONS

AI models that can make real-time predictions of the organ doses for patients undergoing CBCT thorax examinations as part of radiotherapy pre-treatment positioning were developed. The results of this study clearly show that the doses predicted by analyzed AI models are in close agreement with those calculated using Monte Carlo simulations.

Simulation study on the conversion between CT and CBCT dose quantities via the effective dose

In recent years, cone-beam computed tomography (CBCT) has been used in many imaging tasks traditionally performed by computed tomography (CT). This has created challenges for dosimetry, as the dose quantities in CBCT and CT, i.e. the dose-area product (DAP) and dose-length product (DLP), are not mutually convertible. Convertibility would be desirable to compare doses in similar clinical studies performed using CT or CBCT and ultimately for the application of diagnostic reference levels (DRLs). In this work, the conversion of the DAP into the DLP and vice versa via the effective doseEis investigated with the aim of finding common diagnostic reference levels. The dose calculation was performed using Monte Carlo simulations for scan regions with imaging tasks, which can be carried out either with CT or CBCT scanners. Four regions in the head and four in the trunk were chosen. The calculations resulted in conversion coefficientsk=DAPDLPof 30(4) cm for the cranium, 22(4) cm for the facial bones, 24(2) cm for the paranasal sinuses, 18(2) cm for the cervical spine, 78(12) cm for the thorax, 85(13) cm for the upper abdomen, 57(6) cm for the lumbar spine and 70(12) cm for the pelvis.

A nonparametric measure of noise in x-ray diagnostic images-mammography

Objective.In x-ray diagnostics, modern image reconstruction or image processing methods may render established methods of image quality assessment inadequate. Task specific quality assessment by using model observers has the disadvantage of being very labour-intensive. Therefore, it appears highly desirable to develop novel image quality parameters that neither rely on the linearity and the shift-invariace of the imaging system nor require the acquisition of hundreds of images as is necessary for the application of model observers, and which can be derived directly from diagnostic images.Approach.A new measure for the noise based on non-maximum-suppression images is defined and its properties are explored using simulated images before it is applied to an exposure series of mammograms of a homogeneous phantom and a 3D-printed breast phantom to demonstrate its usefulness under realistic conditions.Main results.The new noise parameter cannot only be derived from images with a homogeneous background but it can be extracted directly from images containing anatomic structures and is proportional to the standard deviation of the noise. At present, the applicability is restricted to mammography, which satisfies the assumption of short covariance length of the noise.Significance.The new measure of the noise is but a first step of the development of a set of parameters that are required to quantify image quality directly from diagnostic images without relying on the assumption of a linear, shift-invariant system, e.g. by providing measures of sharpness, contrast and structural complexity, in addition to the noise measure. For mammography, a convenient method is now available to quantify noise in processed diagnostic images.

Patient-level dose monitoring in computed tomography: tracking cumulative dose from multiple multi-sequence exams with tube current modulation in children

BACKGROUND

In children exposed to multiple computed tomography (CT) exams, performed with varying z-axis coverage and often with tube current modulation, it is inaccurate to add volume CT dose index (CTDI_vol) and size-specific dose estimate (SSDE) to obtain cumulative dose values.

OBJECTIVE

To introduce the patient-size-specific z-axis dose profile and its dose line integral (DLI) as new dose metrics, and to use them to compare cumulative dose calculations against conventional measures.

MATERIALS AND METHODS

In all children with 2 or more abdominal-pelvic CT scans performed from 2013 through 2019, we retrospectively recorded all series kV, z-axis tube current profile, CTDI_vol, dose-length product (DLP) and calculated SSDE. We constructed dose profiles as a function of z-axis location for each series. One author identified the z-axis location of the superior mesenteric artery origin on each series obtained to align the dose profiles for construction of each patient's cumulative profile. We performed pair-wise comparisons between the peak dose of the cumulative patient dose profile and ΣSSDE, and between ΣDLI and ΣDLP.

RESULTS

We recorded dose data in 143 series obtained in 48 children, ages 0-2 years (n=15) and 8-16 years (n=33): ΣSSDE 12.7±6.7 and peak dose 15.1±8.1 mGy, ΣDLP 278±194 and ΣDLI 550±292 mGy·cm. Peak dose exceeded ΣSSDE by 20.6% (interquartile range [IQR]: 9.9-26.4%, P<0.001), and ΣDLI exceeded ΣDLP by 114% (IQR: 86.5-147.0%, P<0.001).

CONCLUSION

Our methodology represents a novel approach for evaluating radiation exposure in recurring pediatric abdominal CT examinations, both at the individual and population levels. Under a wide range of patient variables and acquisition conditions, graphic depiction of the cumulative z-axis dose profile across and beyond scan ranges, including the peak dose of the profile, provides a better tool for cumulative dose documentation than simple summations of SSDE. ΣDLI is advantageous in characterizing overall energy absorption over ΣDLP, which significantly underestimated this in all children.

PATIENT-SPECIFIC DOSE ESTIMATES IN DYNAMIC COMPUTED TOMOGRAPHY MYOCARDIAL PERFUSION EXAMINATION

The study aimed to implement realistic source models of a computed tomography (CT) scanner and Monte Carlo simulations to actual patient data and to calculate patient-specific organ and effective dose estimates for patients undergoing dynamic CT myocardial perfusion examinations. Source models including bowtie filter, tube output and x-ray spectra were determined for a dual-source Siemens Somatom Definition Flash scanner. Twenty CT angiography patient datasets were merged with a scaled International Commission on Radiological Protection (ICRP) 110 voxel phantom. Dose simulations were conducted with ImpactMC software. Effective dose estimates varied from 5.0 to 14.6 mSv for the 80 kV spectrum and from 8.9 to 24.7 mSv for the 100 kV spectrum. Significant differences in organ doses and effective doses between patients emphasise the need to use actual patient data merged with matched anthropomorphic anatomy in the dose simulations to achieve a reasonable level of accuracy in the dose estimation procedure.