Application and progress of artificial intelligence in radiation therapy dose prediction

Radiation therapy (RT) nowadays is a main treatment modality of cancer. To ensure the therapeutic efficacy of patients, accurate dose distribution is often required, which is a time-consuming and labor-intensive process. In addition, due to the differences in knowledge and experience among participants and diverse institutions, the predicted dose are often inconsistent. In last several decades, artificial intelligence (AI) has been applied in various aspects of RT, several products have been implemented in clinical practice and confirmed superiority. In this paper, we will review the research of AI in dose prediction, focusing on the progress in deep learning (DL).

Lexicographic optimization-based planning for stereotactic radiosurgery of brain metastases

AIM

To validate a fully-automated lexicographic optimization-planning system (mCycle, Elekta) for single-(SL) and multiple-(ML, up to 4 metastases) lesions in intracranial stereotactic radiosurgery (SRS, 21 Gy, single fraction).

METHODS

A pre-determined priority list, Wish-List (WL), represents a dialogue between planner and clinician, establishing strict constraints and pursuing objectives. In order to satisfy the clinical protocol without manual intervention, four patients were required to tweak and fine-tune each WL (SLp, MLp) for coplanar arcs. Thirty-five testing plans (20 SLp, 15 MLp) were automatically re-planned (mCP). Automatic and manual plans were compared including dose constraints, conformality, modulation complexity score (MCS), delivery time, and local gamma analysis (2%/2 mm). To ensure plan clinical acceptability, two radiation oncologists conducted an independent blind plan choice.

RESULTS

Each WL-tuning took 3 days. Estimated median manual plans and mCP calculation time were 8 and 3 h, respectively. Significant increases in SLp and MLp target coverage and conformity were registered. mCP showed a not significant and clinically acceptable higher median brain V12Gy. SLp registered a -5.8% MU decrease with comparable median delivery time (MP 2.0 min, mCP 1.9 min) while MLp showed a +9.8% MU increase and longer delivery time (MP 3.5 min, mCP 4.4 min). mCP MCS resulted significantly higher without affecting gamma passing rates. At blind choice, mCP were preferred in the majority of cases.

CONCLUSIONS

Lexicographic optimization produced acceptable SRS plans with coplanar arcs significantly reducing the overall planning time in cases with up to 4 brain metastases. These planning improvements suggest further investigations by setting high-quality non-coplanar arc plans as a reference.

On the need of in vivo verifications as quality control for intraoperative electron radiotherapy in breast cancer

INTRODUCTION

Intraoperative electron radiotherapy (IOERT) is a technique aiming to deliver radiotherapy during oncological surgery. In breast IOERT, the applicator and shielding disc placement are correlated with organs at risk (OAR) irradiation, in vivo verification of these parameters is scarcely reported. The aim of our study is to report and analyze possible causes of the misalignment using radiochromic films and compare our results to others reported in the bibliography.

METHODS

From November 2019 to April 2023, in vivo verifications were performed for 33 patients. IOERT was performed using a LIAC 10 MeV (Sordina, Italy) electron accelerator. We attached a radiochromic film to the upper side of the polytetrafluoroethylene cover of the shielding disc. The percentage of the irradiation area outside the disc was recorded and various parameters (applicator angulations, prescription depth, tumor location and breast size) were analyzed to find possible correlations.

RESULTS

For 29 patients, 20 Gy were prescribed while 10 Gy were prescribed to 4 patients. The average irradiated area outside the disc was 19% (0-56%) corresponding to a surface of 4.5 cm2 (0-17.4 cm2). The applicator of 5 cm was used for most of the patients. The mean prescription depth was 1.4 cm (0.5-2.5 cm). We found no correlation between the analyzed parameters and misalignment.

CONCLUSION

This study confirms the presence and magnitude of the misalignments. We strongly recommend in vivo verifications as a quality check during IOERT procedures. The misalignment has no correlation with tumor localization parameters, so the solution could be based on technical improvements of the applicator.

Bringing MRI to low- and middle-income countries: Directions, challenges and potential solutions

The global disparity of magnetic resonance imaging (MRI) is a major challenge, with many low- and middle-income countries (LMICs) experiencing limited access to MRI. The reasons for limited access are technological, economic and social. With the advancement of MRI technology, we explore why these challenges still prevail, highlighting the importance of MRI as the epidemiology of disease changes in LMICs. In this paper, we establish a framework to develop MRI with these challenges in mind and discuss the different aspects of MRI development, including maximising image quality using cost-effective components, integrating local technology and infrastructure and implementing sustainable practices. We also highlight the current solutions-including teleradiology, artificial intelligence and doctor and patient education strategies-and how these might be further improved to achieve greater access to MRI.

Bladder trigone sparing radiotherapy in prostate cancer treatment

INTRODUCTION

Evidence suggests the bladder trigone to be a potential organ at risk (OAR) in predicting acute and late genitourinary (GU) side effects when treating prostate cancer with radiotherapy.

METHODS

A search of MEDLINE, Cinahl, EMBASE, PubMed, the Cochrane Database of Systematic Reviews and OpenGrey was conducted and no current or underway systematic reviews or scoping reviews on the topic were identified. A systematic literature review was carried out assessing the quality of this evidence. All evidence that prospectively or retrospectively reviewed radiotherapy or modelled radiotherapy dose to the bladder trigone were included. The search was conducted on the 8th July 2021 with 32 studies included in this review. This was repeated 10th June 2023 and two additional studies were identified. Any evidence published since this date have not been included and are a limitation of this review.

RESULTS

MRI imaging is recommended to assist in delineating the trigone which has been shown to have a high amount of inter-observer variability and the use of specific training may reduce this. Across all radiotherapy treatment modalities, trigone dose contributed to GU acute and late toxicity symptoms. Trigone motion is relative to prostate motion but further research is required to confirm if the prostate can be used as a reliable surrogate for trigone position. The dose tolerance given for specific trigone related toxicities is debated within the literature, and on analysis the authors of this review suggest bladder trigone dose limits: Dmean < 45.8 Gy, V61.0Gy < 40%, V59.8Gy < 25%, V42.5Gy-V41.0Gy < 91% and V47.4Gy-V43.2Gy < 91% with α/β of 3 Gy to reduce acute and late GU toxicities.

CONCLUSION

There is evidence to support further research into bladder trigone sparing radiotherapy to improve patient outcomes.

IMPLICATION FOR PRACTICE

Using the bladder trigone as an organ at risk is possible and the authors are currently seeking funding for a feasibility trial to further investigate this.

Dosimetric and NTCP advantages of robust proton therapy over robust VMAT for Stage III NSCLC in the immunotherapy era

AIMS

To assess the robustness and to define the dosimetric and NTCP advantages of pencil-beam-scanning proton therapy (PBSPT) compared with VMAT for unresectable Stage III non-small lung cancer (NSCLC) in the immunotherapy era.

MATERIAL AND METHODS

10 patients were re-planned with VMAT and PBSPT using: 1) ITV-based robust optimization with 0.5 cm setup uncertainties and (for PBSPT) 3.5 % range uncertainties on free-breathing CT 2) CTV-based RO including all 4DCTs anatomies. Target coverage (TC), organs at risk dose and TC robustness (TCR), set at V95%, were compared. The NTCP risk for radiation pneumonitis (RP), 24-month mortality (24MM), G2 + acute esophageal toxicity (ET), the dose to the immune system (EDIC) and the left anterior descending (LAD) coronary artery V15 < 10 % were registered. Wilcoxon test was used.

RESULTS

Both PBSPT methods improved TC and TCR (p < 0.01). The mean lung dose and lung V20 were lower with PBSPT (p < 0.01). Median mean heart dose reduction with PBSPT was 8 Gy (p < 0.001). PT lowered median LAD V15 (p = 0.004). ΔNTCP > 5 % with PBSPT was observed for two patients for RP and for five patients for 24 MM. ΔNTCP for ≥ G2 ET was not in favor of PBSPT for all patients. PBSPT halved median EDIC (4.9/5.1 Gy for ITV/CTV-based VMAT vs 2.3 Gy for both ITV/CTV-based PBSPT, p < 0.01).

CONCLUSIONS

PBSPT is a robust approach with significant dosimetric and NTCP advantages over VMAT; the EDIC reduction could allow for a better integration with immunotherapy. A clinical benefit for a subset of NSCLC patients is expected.

Professional ethics in the French medical physicist community: Survey results and implications

INTRODUCTION

Since 2017, in France, medical physicists (MP) are finally defined by law as health professionals and as such, the roles and responsibilities of an MP lean on those medical professional ethics but MPs lack initial or continuing training in this subject. In order to find out how our colleagues feel about this subject, the following survey was conducted.

METHODS

French Society of Medical Physics (SFPM) designed a web survey addressed to its members and non-members concerning ethics based on the 2013 AAPM work; experience and training were highlighted as particularly important within the survey structure.

RESULTS

249 answers were collected and showed a pronounced concern at the lack of initial and continuous training in this subject. Professional experience of non-ethical behaviour was attributed to the lack of training, resources or competences and hostile work environments.

CONCLUSION

To address the shortcomings highlighted in the survey, SFPM has created a dedicated voluntary working group aimed at producing a professional code of ethics for MP and training modules to be applied at entry level or as continuing professional development for education.

Radio-Guided Surgery with a New-Generation β-Probe for Radiolabeled Somatostatin Analog, in Patients with Small Intestinal Neuroendocrine Tumors

BACKGROUND

Radio-guided surgery (RGS) holds promise for improving surgical outcomes in neuroendocrine tumors (NETs). Previous studies showed low specificity (SP) using γ-probes to detect radiation emitted by radio-labeled somatostatin analogs.

OBJECTIVE

We aimed to assess the sensitivity (SE) and SP of the intraoperative RGS approach using a β-probe with a per-lesion analysis, while assessing safety and feasibility as secondary objectives.

METHODS

This prospective, single-arm, single-center, phase II trial (NCT05448157) enrolled 20 patients diagnosed with small intestine NETs (SI-NETs) with positive lesions detected at 68Ga-DOTA-TOC positron emission tomography/computed tomography (PET/CT). Patients received an intravenous injection of 1.1 MBq/Kg of 68Ga-DOTA-TOC 10 min prior to surgery. In vivo measurements were conducted using a β-probe. Receiver operating characteristic (ROC) analysis was performed, with the tumor-to-background ratio (TBR) as the independent variable and pathology result (cancer vs. non-cancer) as the dependent variable. The area under the curve (AUC), optimal TBR, and absorbed dose for the surgery staff were reported.

RESULTS

The intraoperative RGS approach was feasible in all cases without adverse effects. Of 134 specimens, the AUC was 0.928, with a TBR cut-off of 1.35 yielding 89.3% SE and 86.4% SP. The median absorbed dose for the surgery staff was 30 µSv (range 12-41 µSv).

CONCLUSION

This study reports optimal accuracy in detecting lesions of SI-NETs using the intraoperative RGS approach with a novel β-probe. The method was found to be safe, feasible, and easily reproducible in daily clinical practice, with minimal radiation exposure for the staff. RGS might potentially improve radical resection rates in SI-NETs.

CLINICAL TRIALS REGISTRATION

68Ga-DOTATOC Radio-Guided Surgery with β-Probe in GEP-NET (RGS GEP-NET) [NCT0544815; https://classic.

CLINICALTRIALS

gov/ct2/show/NCT05448157 ].

A deep learning-based 3D Prompt-nnUnet model for automatic segmentation in brachytherapy of postoperative endometrial carcinoma

PURPOSE

To create and evaluate a three-dimensional (3D) Prompt-nnUnet module that utilizes the prompts-based model combined with 3D nnUnet for producing the rapid and consistent autosegmentation of high-risk clinical target volume (HR CTV) and organ at risk (OAR) in high-dose-rate brachytherapy (HDR BT) for patients with postoperative endometrial carcinoma (EC).

METHODS AND MATERIALS

On two experimental batches, a total of 321 computed tomography (CT) scans were obtained for HR CTV segmentation from 321 patients with EC, and 125 CT scans for OARs segmentation from 125 patients. The numbers of training/validation/test were 257/32/32 and 87/13/25 for HR CTV and OARs respectively. A novel comparison of the deep learning neural network 3D Prompt-nnUnet and 3D nnUnet was applied for HR CTV and OARs segmentation. Three-fold cross validation and several quantitative metrics were employed, including Dice similarity coefficient (DSC), Hausdorff distance (HD), 95th percentile of Hausdorff distance (HD95%), and intersection over union (IoU).

RESULTS

The Prompt-nnUnet included two forms of parameters Predict-Prompt (PP) and Label-Prompt (LP), with the LP performing most similarly to the experienced radiation oncologist and outperforming the less experienced ones. During the testing phase, the mean DSC values for the LP were 0.96 ± 0.02, 0.91 ± 0.02, and 0.83 ± 0.07 for HR CTV, rectum and urethra, respectively. The mean HD values (mm) were 2.73 ± 0.95, 8.18 ± 4.84, and 2.11 ± 0.50, respectively. The mean HD95% values (mm) were 1.66 ± 1.11, 3.07 ± 0.94, and 1.35 ± 0.55, respectively. The mean IoUs were 0.92 ± 0.04, 0.84 ± 0.03, and 0.71 ± 0.09, respectively. A delineation time < 2.35 s per structure in the new model was observed, which was available to save clinician time.

CONCLUSION

The Prompt-nnUnet architecture, particularly the LP, was highly consistent with ground truth (GT) in HR CTV or OAR autosegmentation, reducing interobserver variability and shortening treatment time.

SAAM II: A general mathematical modeling rapid prototyping environment

Simulation Analysis and Modeling II (SAAM II) is a graphical modeling software used in life sciences for compartmental model analysis, particularly, but not exclusively, appreciated in pharmacokinetics (PK) and pharmacodynamics (PD), metabolism, and tracer modeling. Its intuitive "circles and arrows" visuals allow users to easily build, solve, and fit compartmental models without the need for coding. It is suitable for rapid prototyping of models for complex kinetic analysis or PK/PD problems, and in educating students and non-modelers. Although it is straightforward in design, SAAM II incorporates sophisticated algorithms programmed in C to address ordinary differential equations, deal with complex systems via forcing functions, conduct multivariable regression featuring the Bayesian maximum a posteriori, perform identifiability and sensitivity analyses, and offer reporting functionalities, all within a single package. After 26 years from the last SAAM II tutorial paper, we demonstrate here SAAM II's updated applicability to current life sciences challenges. We review its features and present four contemporary case studies, including examples in target-mediated PK/PD, CAR-T-cell therapy, viral dynamics, and transmission models in epidemiology. Through such examples, we demonstrate that SAAM II provides a suitable interface for rapid model selection and prototyping. By enabling the fast creation of detailed mathematical models, SAAM II addresses a unique requirement within the mathematical modeling community.

Technical advances in motion-robust MR thermometry

Proton resonance frequency shift (PRFS) MR thermometry is the most common method used in clinical thermal treatments because of its fast acquisition and high sensitivity to temperature. However, motion is the biggest obstacle in PRFS MR thermometry for monitoring thermal treatment in moving organs. This challenge arises because of the introduction of phase errors into the PRFS calculation through multiple methods, such as image misregistration, susceptibility changes in the magnetic field, and intraframe motion during MRI acquisition. Various approaches for motion correction have been developed for real-time, motion-robust, and volumetric MR thermometry. However, current technologies have inherent trade-offs among volume coverage, processing time, and temperature accuracy. These tradeoffs should be considered and chosen according to the thermal treatment application. In hyperthermia treatment, precise temperature measurements are of increased importance rather than the requirement for exceedingly high temporal resolution. In contrast, ablation procedures require robust temporal resolution to accurately capture a rapid temperature rise. This paper presents a comprehensive review of current cutting-edge MRI techniques for motion-robust MR thermometry, and recommends which techniques are better suited for each thermal treatment. We expect that this study will help discern the selection of motion-robust MR thermometry strategies and inspire the development of motion-robust volumetric MR thermometry for practical use in clinics.

Accuracy of aortic valve calcification volume score for identification of significant aortic stenosis on non-electrocardiographic-gated computed tomography compared to the Agatston scoring system

BACKGROUND

Considering the absence of reports validating the precision of the volume score and the relationship between the volume and Agatston scores, this study evaluated the accuracy of the volume score compared to the Agatston score for the quantitative measurement of aortic valve calcification (AVC) on non-electrocardiographic-gated computed tomography (CT).

METHODS

We retrospectively analysed the AVC scores of 5385 patients who underwent transthoracic echocardiography between March 1, 2013 and December 26, 2019 ​at our institution, using non-contrast non-electrocardiographic-gated CT. The thresholds for significant aortic stenosis (AS) were computed using receiver operating characteristic curves based on the AVC scores. The area under the curve (AUC) of the Agatston and volume scores for significant AS were compared to evaluate the accuracy of the scoring method.

RESULTS

All sex-specific AVC thresholds of the volume score for significant AS (moderate and high AS severity, moderate and high AS severity without discordance, discordant severe AS, and concordant severe AS) showed high sensitivity and specificity (AUC, 0.978-0.996; sensitivity, 94.2-98.4%; specificity, 90.1-100%). No significant differences in the AUC were observed between the Agatston and volume scores for significant AS in male and female patients.

CONCLUSION

All volume score threshold values showed high sensitivity and specificity for identifying significant AS. The accuracy of the test for AVC thresholds of the volume score for significant AS was comparable to that of the Agatston score. Our findings raise questions about the significance of weighting calcium density in the Agatston score for assessing AS severity.

Repurposing DailyQA3 for an efficient and spot position sensitive daily quality assurance tool for proton therapy

INTRODUCTION

Daily quality assurance is an integral part of a radiotherapy workflow to ensure the dose is delivered safely and accurately to the patient. It is performed before the first treatment of the day and needs to be time and cost efficient for a multiple gantries proton center. In this study, we introduced an efficient method to perform QA for output constancy, range verification, spot positioning accuracy and imaging and proton beam isocenter coincidence with DailyQA3.

METHODS

A stepped acrylic block of specific dimensions is fabricated and placed on top of the DailyQA3 device. Treatment plans comprising of two different spread-out Bragg peaks and five individual spots of 1.0 MU each are designed to be delivered to the device. A mathematical framework to measure the 2D distance between the detectors and individual spot is introduced and play an important role in realizing the spot positioning and centering QA. Lastly, a 5 months trends of the QA for two gantries are presented.

RESULTS

The outputs are monitored by two ion chambers in the DailyQA3 and a tolerance of± 3 % $ \pm 3\% $ are used. The range of the SOBPs are monitored by the ratio of ion chamber signals and a tolerance of± 1 mm $ \pm 1\ {\mathrm{mm}}$ is used. Four diodes at± 10 cm $ \pm 10\ {\mathrm{cm}}$ from the central ion chambers are used for spot positioning QA, while the central ion chamber is used for imaging and proton beam isocenter coincidence QA. Using the framework, we determined the absolute signal threshold corresponding to the offset tolerance between the individual proton spot and the detector. A1.5 mm $1.5\ {\mathrm{mm}}$ tolerances are used for both the positioning and centering QA. No violation of the tolerances is observed in the 5 months trends for both gantries.

CONCLUSION

With the proposed approach, we can perform four QA items in the TG224 within 10 min.

Dosimetric evaluation of intensity modulated photon versus proton reirradiation of head and neck cancer

BACKGROUND

Reirradiation of head and neck cancer (HNC) became more accessible in the last decade, owing to modern irradiation techniques which offer a reduction in treatment related toxicities. The aim of this paper was to comparatively evaluate the dosimetric aspects derived from intensity modulated photon vs. proton treatment planning in reirradiated HNC patients.

METHODS

Six recurrent HNC patients were enrolled in this retrospective study. For each patient two treatment plans were created: one IMRT/VMAT and one IMPT plan. The prescribed dose for the second irradiation was between 50 and 70 Gy RBE. The study comparatively analyzed the CTV coverage, doses to organs at risk (OARs) and low doses received by the healthy tissue (other than OAR).

RESULTS

Similar CTV coverage was achieved for photon vs proton plans, with the latter presenting better homogeneity in four cases. Maximum dose to CTV was generally higher for photon plans, with differences ranging from 0.3 to 1.9%. For parotid glands and body, the mean dose was lower for proton plans. A notable reduction of low dose to healthy tissue (other than OARs) could be achieved with protons, with an average of 60% and 64% for D10% and Dmean, respectively.

CONCLUSION

The dosimetric comparison between photon and proton reirradiation of HNC showed a great need for treatment individualization, concluding that protons should be considered for reirradiation on an individual basis.

Mass-manufacturable scintillation-based optical fiber dosimeters for brachytherapy

Scintillation-based fiber dosimeters are a powerful tool for minimally invasive localized real-time monitoring of the dose rate during Low Dose Rate (LDR) and High Dose Rate (HDR) brachytherapy (BT). This paper presents the design, fabrication, and characterization of such dosimeters, consisting of scintillating sensor tips attached to polymer optical fiber (POF). The sensor tips consist of inorganic scintillators, i.e. Gd2O2S:Tb for LDR-BT, and Y2O3:Eu+4YVO4:Eu for HDR-BT, dispersed in a polymer host. The shape and size of the tips are optimized using non-sequential ray tracing simulations towards maximizing the collection and coupling of the scintillation signal into the POF. They are then manufactured by means of a custom moulding process implemented on a commercial hot embossing machine, paving the way towards series production. Dosimetry experiments in water phantoms show that both the HDR-BT and LDR-BT sensors feature good consistency in the magnitude of the average photon count rate and that the photon count rate signal is not significantly affected by variations in sensor tip composition and geometry. Whilst individual calibration remains necessary, the proposed dosimeters show great potential for in-vivo dosimetry for brachytherapy.

Virtual Monoenergetic Images Facilitate Better Identification of the Arc of Riolan During Splenic Flexure Takedown

OBJECTIVE

This study aimed to investigate whether virtual monoenergetic images (VMIs) can aid radiologists and surgeons in better identifying the arc of Riolan (AOR) and to determine the optimal kilo electron volt (keV) level.

METHODS

Thirty-three patients were included. Conventional images (CIs) and VMI (40-100 keV) were reconstructed using arterial phase spectral-based images. The computed tomography (CT) attenuation and noise of the AOR, the CT attenuation of the erector spinal muscle, and the background noise on VMI and CI were measured, respectively. The signal-to-noise ratio, contrast-to-noise ratio (CNR), and signal intensity ratio were calculated. The image quality of the AOR was evaluated according to a 4-point Likert grade.

RESULTS

The CT attenuation, noise, CNR, and signal intensity ratio of the AOR were significantly higher in VMI at 40 and 50 keV compared with CI ( P < 0.001); VMI at 40 keV was significantly higher than 50 keV ( P < 0.05). No significant difference in signal-to-noise ratio, background noise, and CT attenuation of the spinal erector muscle was observed between VMI and CI ( P > 0.05). virtual monoenergetic image at 40 keV produced the best subjective scores.

CONCLUSIONS

Virtual monoenergetic image at 40 keV makes it easier to observe the AOR with optimized subjective and objective image quality. This may prompt radiologists and surgeons to actively search for it and encourage surgeons to preserve it during splenic flexure takedown.

Impact of the measurement conditions and compression paddle on mammography dosimeter response

The effect of mammography measurement conditions was investigated to evaluate their impact on measurement uncertainties in clinical practice. The most prominent physical X-ray beam quantities i.e., - air kerma, half-value layer, and X-ray tube voltage - were examined by measuring the response of two ionization chambers and six X-ray multimeters (XMMs) of different models. Measurements were performed using several anode/filter combinations and both with and without the compression paddle in the X-ray beam. Maximum differences of higher than 6 % were found for all quantities when the dosimeter displayed value was compared with the reference value or the variation within the clinical anode/filter combinations Mo/Mo and Mo/Rh were considered. The study showed that the calibration procedure with the W/Al anode/filter combination was reliable only for ionization chambers, and the response of XMMs varies in such a way that the calibration coefficient cannot be predicted between various measurement conditions used in calibration and clinical practices. XMM calibrations are typically performed without a compression paddle in the beam, and the response of the XMM changes when radiation quality is slightly altered. If XMM specific data is not available, based on this study, an additional uncertainty of 2 % (k = 1) could be used as a typical estimate, at least for air kerma measurements. XMMs should be used for clinical measurements in mammography only with correct settings. If the correct settings are not available, the XMMs should not be used or used only with extreme caution.

The use of dose surface maps as a tool to investigate spatial dose delivery accuracy for the rectum during prostate radiotherapy

PURPOSE

This study aims to address the lack of spatial dose comparisons of planned and delivered rectal doses during prostate radiotherapy by using dose-surface maps (DSMs) to analyze dose delivery accuracy and comparing these results to those derived using DVHs.

METHODS

Two independent cohorts were used in this study: twenty patients treated with 36.25 Gy in five fractions (SBRT) and 20 treated with 60 Gy in 20 fractions (IMRT). Daily delivered rectum doses for each patient were retrospectively calculated using daily CBCT images. For each cohort, planned and average-delivered DVHs were generated and compared, as were planned and accumulated DSMs. Permutation testing was used to identify DVH metrics and DSM regions where significant dose differences occurred. Changes in rectal volume and position between planning and delivery were also evaluated to determine possible correlation to dosimetric changes.

RESULTS

For both cohorts, DVHs and DSMs reported conflicting findings on how planned and delivered rectum doses differed from each other. DVH analysis determined average-delivered DVHs were on average 7.1% ± 7.6% (p ≤ 0.002) and 5.0 ± 7.4% (p ≤ 0.021) higher than planned for the IMRT and SBRT cohorts, respectively. Meanwhile, DSM analysis found average delivered posterior rectal wall dose was 3.8 ± 0.6 Gy (p = 0.014) lower than planned in the IMRT cohort and no significant dose differences in the SBRT cohort. Observed dose differences were moderately correlated with anterior-posterior rectal wall motion, as well as PTV superior-inferior motion in the IMRT cohort. Evidence of both these relationships were discernable in DSMs.

CONCLUSION

DSMs enabled spatial investigations of planned and delivered doses can uncover associations with interfraction motion that are otherwise masked in DVHs. Investigations of dose delivery accuracy in radiotherapy may benefit from using DSMs over DVHs for certain organs such as the rectum.

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning

Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequently used as a part of routine workups in patients presenting for coughing, respiratory distress, cardiovascular diseases, and for staging of neoplasia. Quality control is a critical aspect of radiology practice in preventing misdiagnosis and ensuring consistent, accurate, and reliable diagnostic imaging. Implementing an effective quality control procedure in radiology can impact patient outcomes, facilitate clinical decision-making, and decrease healthcare costs. In this study, a machine learning-based quality classification model is suggested for canine and feline thoracic radiographs captured in both ventrodorsal and dorsoventral positions. The problem of quality classification was divided into collimation, positioning, and exposure, and then an automatic classification method was proposed for each based on deep learning and machine learning. We utilized a dataset of 899 radiographs of dogs and cats. Evaluations using fivefold cross-validation resulted in an F1 score and AUC score of 91.33 (95% CI: 88.37-94.29) and 91.10 (95% CI: 88.16-94.03), respectively. Results indicated that the proposed automatic quality classification has the potential to be implemented in radiology clinics to improve radiograph quality and reduce nondiagnostic images.

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

PURPOSE

Further acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge.

METHODS

The effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis. ADC bias was assessed by Lin's Concordance correlation coefficient (CCC) followed by bootstrapping to calculate confidence intervals (CI). ADC random measurement error (RME) was assessed by the mean coefficient of variation (CV¯) and non-parametric statistical tests.

RESULTS

The simulations predicted increasingly negative bias and loss of precision towards lower SNR. These effects were confirmed in phantom measurements of increasing acceleration, for which CCC decreased from 0.947 to 0.279 and CV¯ increased from 0.043 to 0.439, and of decreasing flip angle, for which CCC decreased from 0.990 to 0.063 and CV¯ increased from 0.037 to 0.508. At high acceleration and low flip angle, C-SENSE AI reconstruction yielded best denoised ADC maps. For the lowest investigated flip angle, CCC = {0.630, 0.771 and 0.987} and CV¯={0.508, 0.426 and 0.254} were obtained for {SENSE, C-SENSE, C-SENSE AI}, the improvement by C-SENSE AI being significant as compared to the other methods (CV: p = 0.033 for C-SENSE AI vs. C-SENSE and p < 0.001 for C-SENSE AI vs. SENSE; CCC: non-overlapping CI between reconstruction methods). For the highest investigated acceleration factor, CCC = {0.479,0.926,0.960} and CV¯={0.519,0.119,0.118} were found, confirming the reduction of bias and RME by C-SENSE AI as compared to C-SENSE (by trend) and to SENSE (CV: p < 0.001; CCC: non-overlapping CI).

CONCLUSION

ADC bias and random measurement error in DWI at low SNR, typically associated with scan acceleration, can be effectively reduced by deep-learning based C-SENSE AI reconstruction.

Range shifter contribution to neutron exposure of patients undergoing proton pencil beam scanning

BACKGROUND

Superficial targets require the use of the lowest energies within the available energy range in proton pencil-beam scanning (PBS) technique. However, the lower efficiency of the energy selection system at these energies and the requirement of a greater number of layers may represent disadvantages for this approach. The alternative is to use a range shifter (RS) at nozzle exit. However, one of the concerns of using this beamline element is that it becomes an additional source of neutrons that could irradiate organs situated far from the target.

PURPOSE

The purpose of this study is to assess the increase in neutron dose due to the RS in proton PBS technique. Additionally, an analytical model for the neutron production is tested.

METHODS

Two clinical plans, designed to achieve identical target coverage, were created for an anthropomorphic phantom. These plans consisted of a lateral field delivering an absorbed dose of 60 Gy (RBE) to the target. One of the plans employed the RS. The MCNP code was used to simulate the plans, evaluating the distribution of neutron dose equivalent (Hn) and the equivalent dose in organ. In the plan with the RS plan, neutron production from both the patient and the RS were assessed separately. Hn values were also fitted versus the distance to field edge using a Gaussian function.

RESULTS

Hn per prescription dose, in the plan using the RS, ranged between 1.4 and 3.7 mSv/Gy at the field edge, whereas doses at 40 cm from the edge ranged from 9.9 to 32 μSv/Gy. These values are 1.2 to 10 times higher compared to those obtained without the RS. Both this factor and the contribution of neutrons originating from the RS increases with the distance from field edge. A triple-Gaussian function was able to reproduce the equivalent dose in organs within a factor of 2, although underestimating the values.

CONCLUSIONS

The dose deposited in the patient by the neutrons originating from the RS predominantly affects areas away from the target (beyond approximately 25 cm from field edge), resulting in a neutron dose equivalent of the order of mSv. This indicates an overall low neutron contribution from the use of RS in PBS.

Correction for X-Ray Scatter and Detector Crosstalk in Dark-Field Radiography

Dark-field radiography, a new X-ray imaging method, has recently been applied to human chest imaging for the first time. It employs conventional X-ray devices in combination with a Talbot-Lau interferometer with a large field of view, providing both attenuation and dark-field radiographs. It is well known that sample scatter creates artifacts in both modalities. Here, we demonstrate that also X-ray scatter generated by the interferometer as well as detector crosstalk create artifacts in the dark-field radiographs, in addition to the expected loss of spatial resolution. We propose deconvolution-based correction methods for the induced artifacts. The kernel for detector crosstalk is measured and fitted to a model, while the kernel for scatter from the analyzer grating is calculated by a Monte-Carlo simulation. To correct for scatter from the sample, we adapt an algorithm used for scatter correction in conventional radiography. We validate the obtained corrections with a water phantom. Finally, we show the impact of detector crosstalk, scatter from the analyzer grating and scatter from the sample and their successful correction on dark-field images of a human thorax.

Accelerating the continuous community sharing of digital neuromorphology data

The tree-like morphology of neurons and glia is a key cellular determinant of circuit connectivity and metabolic function in the nervous system of essentially all animals. To elucidate the contribution of specific cell types to both physiological and pathological brain states, it is important to access detailed neuroanatomy data for quantitative analysis and computational modeling. NeuroMorpho.Org is the largest online collection of freely available digital neural reconstructions and related metadata and is continuously updated with new uploads. Earlier in the project, we released multiple datasets together yearly, but this process caused an average delay of several months in making the data public. Moreover, in the past 5 years, >80% of invited authors agreed to share their data with the community via NeuroMorpho.Org, up from <20% in the first 5 years of the project. In the same period, the average number of reconstructions per publication increased 600%, creating the need for automatic processing to release more reconstructions in less time. The progressive automation of our pipeline enabled the transition to agile releases of individual datasets as soon as they are ready. The overall time from data identification to public sharing decreased by 63.7%; 78% of the datasets are now released in less than 3 months with an average workflow duration below 40 days. Furthermore, the mean processing time per reconstruction dropped from 3 h to 2 min. With these continuous improvements, NeuroMorpho.Org strives to forge a positive culture of open data. Most importantly, the new, original research enabled through reuse of datasets across the world has a multiplicative effect on science discovery, benefiting both authors and users.

Impact of setup and geometric uncertainties on the robustness of free-breathing photon radiotherapy of small lung tumors

PURPOSE

Respiratory motion and patient setup error both contribute to the dosimetric uncertainty in radiotherapy of lung tumors. Managing these uncertainties for free-breathing treatments is usually done by margin-based approaches or robust optimization. However, breathing motion can be irregular and concerns have been raised for the robustness of the treatment plans. We have previously reported the dosimetric effects of the respiratory motion, without setup uncertainties, in lung tumor photon radiotherapy using free-breathing images. In this study, we include setup uncertainty.

METHODS

Tumor positions from cine-CT images acquired in free-breathing were combined with per-fraction patient shifts to simulate treatment scenarios. A total of 14 patients with 300 tumor positions were used to evaluate treatment plans based on 4DCT. Four planning methods aiming at delivering 54 Gy as median tumor dose in three fractions were compared. The planning methods were denoted robust 4D (RB4), isodose to the PTV with a central higher dose (ISD), the ISD method normalized to the intended median tumor dose (IRN) and homogeneous fluence to the PTV (FLU).

RESULTS

For all planning methods 95% of the intended dose was achieved with at least 90% probability with RB4 and FLU having equal CTV D50% values at this probability. FLU gave the most consistent results in terms of CTV D50% spread and dose homogeneity.

CONCLUSIONS

Despite the simulated patient shifts and tumor motions being larger than observed in the 4DCTs the dosimetric impact was suggested to be small. RB4 or FLU are recommended for the planning of free-breathing treatments.

Obesity, liver steatosis and metabolic syndrome: The hidden enemies in transfusion-dependent thalassaemia

In their paper, the authors quantified liver iron concentration (LIC) and hepatic steatosis (HS) using MRI-T2* technology in transfusion-dependent thalassaemia (TDT) patients and healthy controls and found that the prevalence of HS among patients with TDT was 36.4%. In comparison with healthy controls, the hepatic fat fraction (FF) was significantly higher in the TDT population (p = 0.013). Active hepatitis C virus infection, body mass index (BMI) and LIC were independent predictors of HS. An inverse correlation between hepatic FF and high-density lipoprotein cholesterol (p = 0.042) and a significant association of high glycaemia level (p = 0.037) with higher hepatic FF and a significant relationship (p = 0.026) between HS and higher BMI (though in a 'lean' group of patients) in TDT patients indicated that 'metabolic syndrome' was present in this subset with TDT. The impact of metabolic syndrome on TDT, including cardiac disease unrelated to iron overload, needs further study. Commentary on: Ricchi et al. Liver steatosis in patients with transfusion-dependent thalassaemia. Br J Haematol 2024;204:2458-2467.

Manipulating Radiation-Sensitive Z-DNA Conformation for Enhanced Radiotherapy

DNA double-strand breaks (DSBs) yield highly determines radiotherapy efficacy. However, improving the inherent radiosensitivity of tumor DNA to promote radiation-induced DSBs remains a challenge. Using theoretical and experimental models, the underexplored impact of Z-DNA conformations on radiosensitivity, yielding higher DSBs than other DNA conformations, is discovered. Thereout, a radiosensitization strategy focused on inducing Z-DNA conformation, utilizing CBL@HfO2 nanocapsules loaded with a Z-DNA inducer CBL0137, is proposed. A hollow mesoporous HfO2 (HM-HfO2) acts as a delivery and an energy depositor to promote Z-DNA breakage. The nanocapsule permits the smart DSBs accelerator that triggers its radiosensitization with irradiation stimulation. Impressively, the CBL@HfO2 facilitates the B-Z DNA conformational transition, augmenting DSBs about threefold stronger than irradiation alone, generating significant tumor suppression with a 30% cure rate. The approach enables DSBs augmentation by improving the inherent radiosensitivity of DNA. As such, it opens up an era of Z-DNA conformation manipulation in radiotherapy.

Integrating Computational and Biological Hemodynamic Approaches to Improve Modeling of Atherosclerotic Arteries

Atherosclerosis is the primary cause of cardiovascular disease, resulting in mortality, elevated healthcare costs, diminished productivity, and reduced quality of life for individuals and their communities. This is exacerbated by the limited understanding of its underlying causes and limitations in current therapeutic interventions, highlighting the need for sophisticated models of atherosclerosis. This review critically evaluates the computational and biological models of atherosclerosis, focusing on the study of hemodynamics in atherosclerotic coronary arteries. Computational models account for the geometrical complexities and hemodynamics of the blood vessels and stenoses, but they fail to capture the complex biological processes involved in atherosclerosis. Different in vitro and in vivo biological models can capture aspects of the biological complexity of healthy and stenosed vessels, but rarely mimic the human anatomy and physiological hemodynamics, and require significantly more time, cost, and resources. Therefore, emerging strategies are examined that integrate computational and biological models, and the potential of advances in imaging, biofabrication, and machine learning is explored in developing more effective models of atherosclerosis.

Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy

AIMS

Delineation variations and organ motion produce difficult-to-quantify uncertainties in planned radiation doses to targets and organs at risk. Similar to manual contouring, most automatic segmentation tools generate single delineations per structure; however, this does not indicate the range of clinically acceptable delineations. This study develops a method to generate a range of automatic cardiac structure segmentations, incorporating motion and delineation uncertainty, and evaluates the dosimetric impact in lung cancer.

MATERIALS AND METHODS

Eighteen cardiac structures were delineated using a locally developed auto-segmentation tool. It was applied to lung cancer planning CTs for 27 curative (planned dose ≥50 Gy) cases, and delineation variations were estimated by using ten mapping-atlases to provide separate substructure segmentations. Motion-related cardiac segmentation variations were estimated by auto-contouring structures on ten respiratory phases for 9/27 cases that had 4D-planning CTs. Dose volume histograms (DVHs) incorporating these variations were generated for comparison.

RESULTS

Variations in mean doses (Dmean), defined as the range in values across ten feasible auto-segmentations, were calculated for each cardiac substructure. Over the study cohort the median variations for delineation uncertainty and motion were 2.20-11.09 Gy and 0.72-4.06 Gy, respectively. As relative values, variations in Dmean were between 18.7%-65.3% and 7.8%-32.5% for delineation uncertainty and motion, respectively. Doses vary depending on the individual planned dose distribution, not simply on segmentation differences, with larger dose variations to cardiac structures lying within areas of steep dose gradient.

CONCLUSION

Radiotherapy dose uncertainties from delineation variations and respiratory-related heart motion were quantified using a cardiac substructure automatic segmentation tool. This predicts the 'dose range' where doses to structures are most likely to fall, rather than single DVH curves. This enables consideration of these uncertainties in cardiotoxicity research and for future plan optimisation. The tool was designed for cardiac structures, but similar methods are potentially applicable to other OARs.

Evaluating the performance of thermoplastic 3D bolus used in radiation therapy

A 3D-printed bolus is being developed to deliver accurate doses to superficial cancers. In this study, flexible thermoplastic filaments, specifically PLA, TPU, PETG, and HIPS, were fabricated into boluses and then compared to commercial bolus for the variation of the dose elevation region of photon beams. The experimental results indicate that the maximum dose depth is similar, and the consistent trend of the percentage depth dose confirms the potential usage as a build-up bolus.

Clinical evaluation of a deep learning CBCT auto-segmentation software for prostate adaptive radiation therapy

Purpose

Aim of the present study is to characterize a deep learning-based auto-segmentation software (DL) for prostate cone beam computed tomography (CBCT) images and to evaluate its applicability in clinical adaptive radiation therapy routine.

Materials and methods

Ten patients, who received exclusive radiation therapy with definitive intent on the prostate gland and seminal vesicles, were selected. Femoral heads, bladder, rectum, prostate, and seminal vesicles were retrospectively contoured by four different expert radiation oncologists on patients CBCT, acquired during treatment. Consensus contours (CC) were generated starting from these data and compared with those created by DL with different algorithms, trained on CBCT (DL-CBCT) or computed tomography (DL-CT). Dice similarity coefficient (DSC), centre of mass (COM) shift and volume relative variation (VRV) were chosen as comparison metrics. Since no tolerance limit can be defined, results were also compared with the inter-operator variability (IOV), using the same metrics.

Results

The best agreement between DL and CC was observed for femoral heads (DSC of 0.96 for both DL-CBCT and DL-CT). Performance worsened for low-contrast soft tissue organs: the worst results were found for seminal vesicles (DSC of 0.70 and 0.59 for DL-CBCT and DL-CT, respectively). The analysis shows that it is appropriate to use algorithms trained on the specific imaging modality. Furthermore, the statistical analysis showed that, for almost all considered structures, there is no significant difference between DL-CBCT and human operator in terms of IOV.

Conclusions

The accuracy of DL-CBCT is in accordance with CC; its use in clinical practice is justified by the comparison with the inter-operator variability.

Dosimetric advantages for cardiac substructures in radiotherapy of esophageal cancer in deep-inspiration breath hold

BACKGROUND

Radiotherapy is one of the main treatment options for patients with esophageal cancer; however, it has been linked with an increased risk of cardiac toxicities. In the current study, we evaluated the effect of planning the radiation in deep-inspiration breath hold (DIBH) on the dose sparing of cardiac substructures and lung.

MATERIALS AND METHODS

In this study, we analyzed 30 radiation therapy plans from 15 patients diagnosed with esophageal cancer planned for neoadjuvant radiotherapy. Radiation plans were generated for 41.4 Gy and delivered in 1.8 Gy per fraction for free-breathing (FB) and DIBH techniques. We then conducted a comparative dosimetric analysis, evaluating target volume coverage, the impact on cardiac substructures, and lung doses across the two planning techniques for each patient.

RESULTS

There was no significant disparity in target volume dose coverage between DIBH and FB plans. However, the Dmean, D2%, and V30% of the heart experienced substantial reductions in DIBH relative to FB, with values of 6.21 versus 7.02 Gy (p = 0.011), 35.28 versus 35.84 Gy (p = 0.047), and 5% versus 5.8% (p = 0.048), respectively. The Dmean of the left ventricle was notably lower in DIBH compared to FB (4.27 vs. 5.12 Gy, p = 0.0018), accompanied by significant improvements in V10. Additionally, the Dmean and D2% of the left coronary artery, as well as the D2% of the right coronary artery, were significantly lower in DIBH. The dosimetric impact of DIBH on cardiac substructures proved more advantageous for middle esophageal (ME) than distal esophageal (DE) tumors.

CONCLUSION

Radiotherapy in DIBH could provide a method to reduce the radiation dose to the left ventricle and coronaries, which could reduce the cardiac toxicity of the modality.

The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods

PURPOSE

This study aimed to examine the robustness of positron emission tomography (PET) radiomic features extracted via different segmentation methods before and after ComBat harmonization in patients with non-small cell lung cancer (NSCLC).

METHODS

We included 120 patients (positive recurrence = 46 and negative recurrence = 74) referred for PET scanning as a routine part of their care. All patients had a biopsy-proven NSCLC. Nine segmentation methods were applied to each image, including manual delineation, K-means (KM), watershed, fuzzy-C-mean, region-growing, local active contour (LAC), and iterative thresholding (IT) with 40, 45, and 50% thresholds. Diverse image discretizations, both without a filter and with different wavelet decompositions, were applied to PET images. Overall, 6741 radiomic features were extracted from each image (749 radiomic features from each segmented area). Non-parametric empirical Bayes (NPEB) ComBat harmonization was used to harmonize the features. Linear Support Vector Classifier (LinearSVC) with L1 regularization For feature selection and Support Vector Machine classifier (SVM) with fivefold nested cross-validation was performed using StratifiedKFold with 'n_splits' set to 5 to predict recurrence in NSCLC patients and assess the impact of ComBat harmonization on the outcome.

RESULTS

From 749 extracted radiomic features, 206 (27%) and 389 (51%) features showed excellent reliability (ICC ≥ 0.90) against segmentation method variation before and after NPEB ComBat harmonization, respectively. Among all, 39 features demonstrated poor reliability, which declined to 10 after ComBat harmonization. The 64 fixed bin widths (without any filter) and wavelets (LLL)-based radiomic features set achieved the best performance in terms of robustness against diverse segmentation techniques before and after ComBat harmonization. The first-order and GLRLM and also first-order and NGTDM feature families showed the largest number of robust features before and after ComBat harmonization, respectively. In terms of predicting recurrence in NSCLC, our findings indicate that using ComBat harmonization can significantly enhance machine learning outcomes, particularly improving the accuracy of watershed segmentation, which initially had fewer reliable features than manual contouring. Following the application of ComBat harmonization, the majority of cases saw substantial increase in sensitivity and specificity.

CONCLUSION

Radiomic features are vulnerable to different segmentation methods. ComBat harmonization might be considered a solution to overcome the poor reliability of radiomic features.

Enhancing adaptive proton therapy through CBCT images: Synthetic head and neck CT generation based on 3D vision transformers

BACKGROUND

Proton therapy is a form of radiotherapy commonly used to treat various cancers. Due to its high conformality, minor variations in patient anatomy can lead to significant alterations in dose distribution, making adaptation crucial. While cone-beam computed tomography (CBCT) is a well-established technique for adaptive radiation therapy (ART), it cannot be directly used for adaptive proton therapy (APT) treatments because the stopping power ratio (SPR) cannot be estimated from CBCT images.

PURPOSE

To address this limitation, Deep Learning methods have been suggested for converting pseudo-CT (pCT) images from CBCT images. In spite of convolutional neural networks (CNNs) have shown consistent improvement in pCT literature, there is still a need for further enhancements to make them suitable for clinical applications.

METHODS

The authors introduce the 3D vision transformer (ViT) block, studying its performance at various stages of the proposed architectures. Additionally, they conduct a retrospective analysis of a dataset that includes 259 image pairs from 59 patients who underwent treatment for head and neck cancer. The dataset is partitioned into 80% for training, 10% for validation, and 10% for testing purposes.

RESULTS

The SPR maps obtained from the pCT using the proposed method present an absolute relative error of less than 5% from those computed from the planning CT, thus improving the results of CBCT.

CONCLUSIONS

We introduce an enhanced ViT3D architecture for pCT image generation from CBCT images, reducing SPR error within clinical margins for APT workflows. The new method minimizes bias compared to CT-based SPR estimation and dose calculation, signaling a promising direction for future research in this field. However, further research is needed to assess the robustness and generalizability across different medical imaging applications.

Federated learning for medical image analysis: A survey

Machine learning in medical imaging often faces a fundamental dilemma, namely, the small sample size problem. Many recent studies suggest using multi-domain data pooled from different acquisition sites/centers to improve statistical power. However, medical images from different sites cannot be easily shared to build large datasets for model training due to privacy protection reasons. As a promising solution, federated learning, which enables collaborative training of machine learning models based on data from different sites without cross-site data sharing, has attracted considerable attention recently. In this paper, we conduct a comprehensive survey of the recent development of federated learning methods in medical image analysis. We have systematically gathered research papers on federated learning and its applications in medical image analysis published between 2017 and 2023. Our search and compilation were conducted using databases from IEEE Xplore, ACM Digital Library, Science Direct, Springer Link, Web of Science, Google Scholar, and PubMed. In this survey, we first introduce the background of federated learning for dealing with privacy protection and collaborative learning issues. We then present a comprehensive review of recent advances in federated learning methods for medical image analysis. Specifically, existing methods are categorized based on three critical aspects of a federated learning system, including client end, server end, and communication techniques. In each category, we summarize the existing federated learning methods according to specific research problems in medical image analysis and also provide insights into the motivations of different approaches. In addition, we provide a review of existing benchmark medical imaging datasets and software platforms for current federated learning research. We also conduct an experimental study to empirically evaluate typical federated learning methods for medical image analysis. This survey can help to better understand the current research status, challenges, and potential research opportunities in this promising research field.

A comprehensive assessment of a prototype high ratio antiscatter grid in interventional cardiology using experimental measurements and Monte Carlo simulations

Objective. To assess the performance of a new antiscatter grid design in interventional cardiology for image quality improvement and dose reduction using experimental measurements and Monte Carlo (MC) simulation.Approach.Experimental measurements were performed on an angiography system, using a multi-layered tissue simulating composite phantom made from of poly(methyl methacrylate), aluminium and expanded polystyrene (2/0.2/0.7 cm). The total phantom thickness ranged from 20.3 cm to 40.6 cm. Four conditions were compared; (A) 105 cm source-image receptor distance (SID) without grid, (Bi) 105 cm SID with grid ratio (r) and strip density (N) (r15N80), (Bii) 120 cm SID without grid, and (Biii) 120 cm SID with high ratio grid (r29N80). The system efficiency (η), defined by the signal-to-noise ratio, was compared from theBconditions against caseA. These conditions were also simulated with MC techniques, allowing additional phantom compositions to be explored. Weighted image quality improvement factor (ηw(u)) was studied experimentally at a specific spatial frequency due to the SID change. Images were simulated with an anthropomorphic chest phantom for the different conditions, and the system efficiency was compared for the different anatomical regions.Main results.Good agreement was found between theηandηw(u) methods using both measured and simulated data, with average relative differences between 2%-11%. CaseBiiiprovided higherηvalues compared toA, andBifor thicknesses larger than 20.3 cm. In addition, caseBiiialso provided higherηvalues for high attenuating areas in the anthropomorphic phantom, such as behind the spine.Significance.The new antiscatter grid design provided higher system efficiency compared to the standard grid for the parameters explored in this work.

Radiographers' insights on the impact of their potential role in image interpretation within a low resource setting

INTRODUCTION

The global shortage of radiologists has led to a growing concern in medical imaging, prompting the exploration of strategies, such as including radiographers in image interpretation, to mitigate this challenge. However, in low-resource settings, progress in adopting similar approaches has been limited. This study aimed to explore radiographers' perceptions regarding the impact of their potential role in image interpretation within a low-resource setting.

METHODS

The study used a qualitative descriptive design and was conducted at two public referral hospitals. Radiographers with at least one year of experience were purposively sampled and interviewed using a semi-structured interview guide after consenting. Data saturation determined the sample size, and content analysis was applied for data analysis.

RESULTS

Two themes emerged from fourteen interviews conducted with two male and twelve female radiographers. Theme one revealed the potential for enhanced healthcare delivery through improved diagnostic support, bridging radiologist shortages, career development and fulfilment as positive outcomes of role extension. Theme two revealed possible implementation hurdles including radiographer resistance and reluctance, limited training, lack of professional trust, and legal and ethical challenges.

CONCLUSION

Radiographers perceived their potential participation positively, envisioning enhanced healthcare delivery, however, possible challenges like resistance and reluctance of radiographers, limited training, and legal/ethical issues pose hurdles. Addressing these challenges through tailored interventions, including formal education could facilitate successful implementation. Further studies are recommended to explore radiographers' competencies, providing empirical evidence for sustaining and expanding this role extension.

IMPLICATION FOR PRACTICE

The study further supports the integration of radiographers into image interpretation with the potential to enhance healthcare delivery, however, implementation challenges in low-resource settings require careful consideration.

A cone-beam optical CT based on a convergent light source - Characterization and optimization

PURPOSE

Employing a Fresnel lens and a point-like light source to create a convergent light beam for the camera effectively minimizes stray light and enhances image quality in optical computed tomography (OCT), benefiting 3D dosimetry applications. This study outlines the development of an economical cone-beam optical computed scanner for 3D dosimetry.

METHODS

Optical performance was assessed by calculating modulation transfer function (MTF) with pattern charts. Stray light was evaluated by imaging a cylinder flask and a square grid with 5 mm diameter holes to determine the stray-to-primary ratio. Reconstruction quality was determined using SIRT-TV and compared with spectrophotometry attenuation coefficients, with the best regularization parameter (λ = 0.01) chosen based on contrast-to-noise ratio (CNR). Dosimetry performance was assessed by determining percentage dose depth (PDD) for a 6MV beam with a 5 × 5 cm2 field using FXO-f gel dosimeter, compared with ionization chamber data.

RESULTS

MTF evaluation yielded ≥ 50 % agreement with pattern charts. Stray-to-primary ratio was less than 0.1 or 10 % of the total signal. Reconstruction showed low noise and artifacts, with optimal CNR at λ = 0.01. Attenuation coefficients from optical CT aligned with spectrometer measurements within 1.2 %. PDD calculated with FXO-f gel dosimeter closely matched ionization chamber data (<1.2 % difference), achieving a dose resolution of 0.1 Gy.

CONCLUSION

The built and optimization the de optical-CT based on a convergent beam is read to perform the 3D quality assurance in clinical applications.

Physics and small-scale dosimetry of α $\alpha$ -emitters for targeted radionuclide therapy: The case of 211 At $^{211}{\rm At}$

BACKGROUND

Monte Carlo simulations have been considered for a long time the gold standard for dose calculations in conventional radiotherapy and are currently being applied for the same purpose in innovative radiotherapy techniques such as targeted radionuclide therapy (TRT).

PURPOSE

We present in this work a benchmarking study of the latest version of the Transport d'Ions Lourds Dans l'Aqua & Vivo (TILDA-V ) Monte Carlo track structure code, highlighting its capabilities for describing the full slowing down of α $\alpha$ -particles in water and the energy deposited in cells by α $\alpha$ -emitters in the context of TRT.

METHODS

We performed radiation transport simulations of α $\alpha$ -particles (10 keVu - 1 ${\rm u}^{-1}$ -100 MeVu - 1 ${\rm u}^{-1}$ ) in water with TILDA-V and the Particle and Heavy Ion Transport code System (PHITS) version 3.33. We compared the predictions of each code in terms of track parameters (stopping power, range and radial dose profiles) and cellular S-values of the promising radionuclide astatine-211 (211 At $^{211}{\rm At}$ ). Additional comparisons were made with available data in the literature.

RESULTS

The stopping power, range and radial dose profiles of α $\alpha$ -particles computed with TILDA-V were in excellent agreement with other calculations and available data. Overall, minor differences with PHITS were ascribed to phase effects, that is, related to the use of interaction cross sections computed for water vapor or liquid water. However, important discrepancies were observed in the radial dose profiles of monoenergetic α $\alpha$ -particles, for which PHITS results showed a large underestimation of the absorbed dose compared to other codes and experimental data. The cellular S-values of211 At $^{211}{\rm At}$ computed with TILDA-V  agreed within 4% with the values predicted by PHITS and MIRDcell.

CONCLUSIONS

The validation of the TILDA-V code presented in this work opens the possibility to use it as an accurate simulation tool for investigating the interaction of α $\alpha$ -particles in biological media down to the nanometer scale in the context of medical research. The code may help nuclear medicine physicians in their choice of α $\alpha$ -emitters for TRT. Further research will focus on the application of TILDA-V for quantifying radioinduced damage on the deoxyribonucleic acid (DNA) molecule.

Clinical outcomes of pelvic bone marrow sparing radiotherapy for cervical cancer: A systematic review and meta-analysis of randomised controlled trials

Background

Concurrent chemoradiotherapy (CRT) is the standard treatment for locally advanced cervical cancer. We investigated how additional bone marrow sparing (BMS) affects the clinical outcomes.

Methods

We queried MEDLINE, Embase, Web of Science Core Collection, Google Scholar, Sinomed, CNKI, and Wanfang databases for articles published in English or Chinese between 2010/01/01 and 2023/10/31. Full-text manuscripts of prospective, randomised trials on BMS in cervical cancer patients treated with definitive or postoperative CRT were included. Risk of bias (RoB) was assessed using Cochrane Collaboration's RoB tool. Random-effects models were used for the meta-analysis.

Results

A total of 17 trials encompassing 1297 patients were included. The majority were single-centre trials (n = 1268) performed in China (n = 1128). Most trials used CT-based anatomical BMS (n = 1076). There was a comparable representation of trials in the definitive (n = 655) and postoperative (n = 582) settings, and the remaining trials included both.Twelve studies reported data on G ≥ 3 (n = 782) and G ≥ 2 (n = 754) haematologic adverse events. Both G ≥ 3 (OR 0.39; 95 % CI 0.28-0.55; p < 0.001) and G ≥ 2 (OR 0.29; 95 % CI 0.18-0.46; p < 0.001) toxicity were significantly lowered, favouring BMS. Seven studies (n = 635) reported data on chemotherapy interruptions, defined as receiving less than five cycles of cisplatin, which were significantly less frequent in patients treated with BMS (OR 0.44; 95 % CI 0.24-0.81; p = 0.016). There was no evidence of increased gastrointestinal or genitourinary toxicity.There were no signs of significant heterogeneity. Four studies were assessed as high RoB; sensitivity analyses excluding these provided comparable results for main outcomes. The main limitations include heterogeneity in BMS methodology between studies, low representation of populations most affected by cervical cancer, and insufficient data to assess survival outcomes.

Conclusions

The addition of BMS to definitive CRT in cervical cancer patients decreases hematologic toxicity and the frequency of interruptions in concurrent chemotherapy. However, data are insufficient to verify the impact on survival and disease control.

Cone-Beam Computed Tomography (CBCT)-Based Diagnosis of Dental Bone Defects

Cone Beam Computed Tomography (CBCT) has completely changed the way that bone disorders are diagnosed and treated, especially in the dental and maxillofacial domains. This article examines the diverse applications of computed tomography (CBCT) in the diagnosis and treatment of facial trauma, including mandibular, dentoalveolar, and other facial fractures, as well as bone abnormalities like dislocations and fractures. CBCT is useful for a wide range of dental conditions and greatly improves diagnostic accuracy in periodontics, orthodontics, endodontics, and dental implantology. Additionally, a comparison between CBCT and conventional imaging methods was conducted, emphasizing the latter's inferior 3D imaging capabilities, allowing for more precise treatment planning and better patient outcomes with CBCT. Although CBCT has many benefits, it also has some drawbacks, such as requiring specific training for accurate interpretation, cost considerations, and a higher radiation exposure than with traditional dental X-rays. In order to optimize benefits and reduce risks, the conclusion highlights CBCT's revolutionary influence on clinical practice while arguing for its prudent and responsible application.

Proposed Diagnostic Reference Levels in the Missouri/Southern Illinois Region Associated with Cone-beam Computed Tomography Use in Endodontics

INTRODUCTION

Diagnostic reference levels (DRLs) are intended to improve patient safety and ensure that patient ionizing radiation doses are as low as reasonably achievable. The purpose of this dosimetry study was to establish regional DRL levels for cone-beam computed tomography (CBCT) imaging for specialty endodontics. Another aim was to compare phantom-measured ionizing radiation dose index 1 (DI1) index doses to the manufacturer-provided dose area product (DAP) radiation output values for each of the CBCT machines studied, to ascertain their degree of correlation. DAP refers to the dose area product, a measure of radiation dose monitoring which represents the dose within the beam times the area within the beam at that position.

METHODS

A thimble ionization chamber and polymethyl methacrylate phantom were used to obtain DI1 values using the SEDENTEXTCT method from 21 different CBCT units. DRLs were calculated based on the 75th percentile (third quartile) of the median output values.

RESULTS

The proposed DRL from the CBCT units surveyed has a DAP value of 838 mGy cm2 and a DI1 value of 3.924 mGy. DAP versus DI1 values of 500.6 mGy cm2 versus 2.006 mGy, and 838 mGy cm2 versus 3.906 mGy represented the third quartile of the median values for the 4-cm × 4-cm and 5-cm × 5-cm field of views (FOVs), respectively.

CONCLUSIONS

The DI1 and DAP values strongly correlated when 3 outlier CBCT machines (J Morita Veraview X800) using a novel 360° (full rotation) acquisition mode were excluded. The importance of selectable exposure parameters as directly related to ionizing radiation output is illustrated among the CBCT units surveyed. Although the actual FOV that is selected is ultimately dictated by the specific clinical requirements, a 4-cm × 4-cm FOV is recommended for specialist endodontics practice, whenever clinically practical, based on the decreased ionizing radiation output, as compared to that from a 5-cm × 5-cm FOV.

Detection of extracranial and intracranial calcified carotid artery atheromas in cone beam computed tomography using a deep learning convolutional neural network image segmentation approach

OBJECTIVE

We leveraged an artificial intelligence deep-learning convolutional neural network (DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed tomography (CBCT) images.

STUDY DESIGN

We obtained 137 full-volume CBCT scans with previously diagnosed CCAAs. The DL model was trained on 170 single axial CBCT slices, 90 with extracranial CCAAs and 80 with intracranial CCAAs. A board-certified oral and maxillofacial radiologist confirmed the presence of each CCAA. Transfer learning through a U-Net-based CNN architecture was utilized. Data allocation was 60% training, 10% validation, and 30% testing. We determined the accuracy of the DL model in detecting CCAA by calculating the mean training and validation accuracy and the area under the receiver operating characteristic curve (AUC). We reserved 5 randomly selected unseen full CBCT volumes for final testing.

RESULTS

The mean training and validation accuracy of the model in detecting extracranial CCAAs was 92% and 82%, respectively, and the AUC was 0.84 with 1.0 sensitivity and 0.69 specificity. The mean training and validation accuracy in detecting intracranial CCAAs was 61% and 70%, respectively, and the AUC was 0.5 with 0.93 sensitivity and 0.08 specificity. Testing of full-volume scans yielded an AUC of 0.72 and 0.55 for extracranial and intracranial CCAAs, respectively.

CONCLUSION

Our DL model showed excellent discrimination in detecting extracranial CCAAs on axial CBCT images and acceptable discrimination on full-volumes but poor discrimination in detecting intracranial CCAAs, for which further research is required.

Development of a dental digital data set for research in artificial intelligence: the importance of labeling performed by radiologists

OBJECTIVE

The aim of this study was to present the development of a database (dataset) of panoramic radiographs.

STUDY DESIGN

Three radiologists labeled an image set consisting of 936 panoramic radiographs. Labeling includes tooth numbering (including teeth present and missing) and annotation of dental conditions (e.g., caries, dental restoration, residual root, endodontic treatment, implant, fixed prosthesis, incisal wear). The annotation process was performed in a Picture Archive and Communication System software customized for the study purposes using a small bounding box to delimit the entire tooth and items for radiographic diagnosis and a large bounding box to simultaneously delimit the 2 dental arches (maxilla and mandible). A JSON file was generated for each annotation.

RESULTS

The database encompassed 23,619 annotations; disagreement between radiologists occurred in 0.7% of the notes.

CONCLUSIONS

This work aimed to inform researchers about the importance of the labeling process, in addition to providing the scientific community with a bank of labeled images to implement artificial intelligence systems in clinical practice.

First Monte Carlo beam model for ultra-high dose rate radiotherapy with a compact electron LINAC

BACKGROUND

FLASH radiotherapy based on ultra-high dose rate (UHDR) is actively being studied by the radiotherapy community. Dedicated UHDR electron devices are currently a mainstay for FLASH studies.

PURPOSE

To present the first Monte Carlo (MC) electron beam model for the UHDR capable Mobetron (FLASH-IQ) as a dose calculation and treatment planning platform for preclinical research and FLASH-radiotherapy (RT) clinical trials.

METHODS

The initial beamline geometry of the Mobetron was provided by the manufacturer, with the first-principal implementation realized in the Geant4-based GAMOS MC toolkit. The geometry and electron source characteristics, such as energy spectrum and beamline parameters, were tuned to match the central-axis percentage depth dose (PDD) and lateral profiles for the pristine beam measured during machine commissioning. The thickness of the small foil in secondary scatter affected the beam model dominantly and was fine tuned to achieve the best agreement with commissioning data. Validation of the MC beam modeling was performed by comparing the calculated PDDs and profiles with EBT-XD radiochromic film measurements for various combinations of applicators and inserts.

RESULTS

The nominal 9 MeV electron FLASH beams were best represented by a Gaussian energy spectrum with mean energy of 9.9 MeV and variance (σ) of 0.2 MeV. Good agreement between the MC beam model and commissioning data were demonstrated with maximal discrepancy < 3% for PDDs and profiles. Hundred percent gamma pass rate was achieved for all PDDs and profiles with the criteria of 2 mm/3%. With the criteria of 2 mm/2%, maximum, minimum and mean gamma pass rates were (100.0%, 93.8%, 98.7%) for PDDs and (100.0%, 96.7%, 99.4%) for profiles, respectively.

CONCLUSIONS

A validated MC beam model for the UHDR capable Mobetron is presented for the first time. The MC model can be utilized for direct dose calculation or to generate beam modeling input required for treatment planning systems for FLASH-RT planning. The beam model presented in this work should facilitate translational and clinical FLASH-RT for trials conducted on the Mobetron FLASH-IQ platform.

A machine learning-based approach to predict energy layer for each field in spot-scanning proton arc therapy for lung cancer: A feasibility study

BACKGROUND

Determining the optimal energy layer (EL) for each field, under considering both dose constraints and delivery efficiency, is crucial to promoting the development of proton arc therapy (PAT) technology.

PURPOSE

This study aimed to explore the feasibility and potential clinical benefits of utilizing machine learning (ML) technique to automatically select EL for each field in PAT plans of lung cancer.

METHODS

Proton Bragg peak position (BPP) was employed to characterize EL. The ground truth BPPs for each field were determined using the modified ELO-SPAT framework. Features in geometric, water-equivalent thicknesses (WET) and beamlet were defined and extracted. By analyzing the relationship between the extracted features and ground truth, a polynomial regression model with L2-norm regularization (Ridge regression) was constructed and trained. The performance of the regression model was reported as an error between the predictions and the ground truth. Besides, the predictions were used to make PAT plans (PAT_PRED). These plans were compared with those using the ground truth BPPs (PAT_TRUTH) and the mid-WET of the target volumes (PAT_MID) in terms of relative biological effectiveness-weighted dose (RWD) distributions. One hundred ten patients with lung cancer, a total of 7920 samples, were enrolled retrospectively, with 5940 cases randomly selected as the training set and the remaining 1980 cases as the testing set. Nine patients (648 samples) were collected additionally to evaluate the regression model in terms of plan quality and robustness.

RESULTS

With regard to the prediction errors, the root mean squared errors and mean absolute errors between the ML-predicted and ground truth BPPs for the testing set were 9.165 and 6.572 mm, respectively, indicating differences of approximately two to three ELs. As for plan quality, the PAT_TRUTH and PAT_PRED plans performed similarly in terms of plan robustness, target coverage and organs at risk (OARs) protection, with differences smaller than 0.5 Gy(RBE). This trend was also observed for dose conformity and uniformity. The PAT_MID plans produced the lowest robustness index and lowest doses to OARs, along with the highest heterogeneity index, indicating better protection for OARs, improved plan robustness, but compromised dose homogeneity. Additionally, for relatively small tumor sizes, the PAT_MID plan demonstrated a notably poor dose conformity index.

CONCLUSIONS

Within this cohort under investigation, our study demonstrated the feasibility of using ML technique to predict ELs for each field, offering a fast (within 2 s) and memory-efficient reduced way to select ELs for PAT plan.

Electron streaming dose measurements and calculations on a 1.5 T MR-Linac

PURPOSE

To evaluate the accuracy of different dosimeters and the treatment planning system (TPS) for assessing the skin dose due to the electron streaming effect (ESE) on a 1.5 T magnetic resonance (MR)-linac.

METHOD

Skin dose due to the ESE on an MR-linac (Unity, Elekta) was investigated using a solid water phantom rotated 45° in the x-y plane (IEC61217) and centered at the isocenter. The phantom was irradiated with 1 × 1, 3 × 3, 5 × 5, 10 × 10, and 22 × 22 cm2 fields, gantry at 90°. Out-of-field doses (OFDs) deposited by electron streams generated at the entry and exit surface of the angled phantom were measured on the surface of solid water slabs placed ±20.0 cm from the isocenter along the x-direction. A high-resolution MOSkin™ detector served as a benchmark due to its shallower depth of measurement that matches the International Commission on Radiological Protection (ICRP) recommended depth for skin dose assessment (0.07 mm). MOSkin™ doses were compared to EBT3 film, OSLDs, a diamond detector, and the TPS where the experimental setup was modeled using two separate calculation parameters settings: a 0.1 cm dose grid with 0.2% statistical uncertainty (0.1 cm, 0.2%) and a 0.2 cm dose grid with 3.0% statistical uncertainty (0.2 cm, 3.0%).

RESULTS

OSLD, film, the 0.1 cm, 0.2%, and 0.2 cm, 3.0% TPS ESE doses, underestimated skin doses measured by the MOSkin™ by as much as -75.3%, -7.0%, -24.7%, and -41.9%, respectively. Film results were most similar to MOSkin™ skin dose measurements.

CONCLUSIONS

These results show that electron streams can deposit significant doses outside the primary field and that dosimeter choice and TPS calculation settings greatly influence the reported readings. Due to the steep dose gradient of the ESE, EBT3 film remains the choice for accurate skin dose assessment in this challenging environment.