Efficacy of radiation attenuating caps in reducing radiation doses received at the cerebral level in interventional physicians: a systematic review

Background.Anecdotal reports are appearing in the scientific literature about cases of brain tumors in interventional physicians who are exposed to ionizing radiation. In response to this alarm, several designs of leaded caps have been made commercially available. However, the results reported on their efficacy are discordant.Objective.To synthesize, by means of a systematic review of the literature, the capacity of decreasing radiation levels conferred by radiation attenuating devices (RADs) at the cerebral level of interventional physicians.Methodology.A systematic review was performed including the following databases: MEDLINE, SCOPUS, EBSCO, Science Direct, Cochrane Controlled Trials Register (CENTRAL), WOS, WHO International Clinical Trials Register, Scielo and Google Scholar, considering original studies that evaluated the efficacy of RAD in experimental or clinical contexts from January 1990 to May 2023. Data selection and extraction were performed in triplicate, with a fourth author resolving discrepancies.Results.Twenty articles were included in the review from a total of 373 studies initially selected from the databases. From these, twelve studies were performed under clinical conditions encompassing 3801 fluoroscopically guided procedures, ten studies were performed under experimental conditions with phantoms, with a total of 88 procedures, four studies were performed using numerical calculations with a total of 63 procedures. The attenuation and effectiveness of provided by the caps analyzed in the present review varying from 12.3% to 99.9%, and 4.9% to 91% respectively.Conclusion.RAD were found to potentially provide radiation protection, but a high heterogeneity in the shielding afforded was found. This indicates the need for local assessment of cap efficiency according to the practice.

Mitigating the impact of image processing variations on tumour [18F]-FDG-PET radiomic feature robustness

Radiomics analysis of [18F]-fluorodeoxyglucose ([18F]-FDG) PET images could be leveraged for personalised cancer medicine. However, the inherent sensitivity of radiomic features to intensity discretisation and voxel interpolation complicates its clinical translation. In this work, we evaluated the robustness of tumour [18F]-FDG-PET radiomic features to 174 different variations in intensity resolution or voxel size, and determined whether implementing parameter range conditions or dependency corrections could improve their robustness. Using 485 patient images spanning three cancer types: non-small cell lung cancer (NSCLC), melanoma, and lymphoma, we observed features were more sensitive to intensity discretisation than voxel interpolation, especially texture features. In most of our investigations, the majority of non-robust features could be made robust by applying parameter range conditions. Correctable features, which were generally fewer than conditionally robust, showed systematic dependence on bin configuration or voxel size that could be minimised by applying corrections based on simple mathematical equations. Melanoma images exhibited limited robustness and correctability relative to NSCLC and lymphoma. Our study provides an in-depth characterisation of the sensitivity of [18F]-FDG-PET features to image processing variations and reinforces the need for careful selection of imaging biomarkers prior to any clinical application.

Dosimetric comparison of IMPT vs VMAT for multiple lung lesions: an NTCP model-based decision-making strategy

To compare the dosimetric differences in volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) in stereotactic body radiation therapy (SBRT) of multiple lung lesions and determine a normal tissue complication probability (NTCP) model-based decision strategy that determines which treatment modality the patient will use. A total of 41 patients were retrospectively selected for this study. The number of patients with 1-6 lesions was 5, 16, 7, 6, 3, and 4, respectively. A prescription dose of 70 GyRBE in 10 fractions was given to each lesion. SBRT plans were generated using VMAT and IMPT. All the IMPT plans used robustness optimization with ± 3.5% range uncertainties and 5 mm setup uncertainties. Dosimetric metrics and the predicted NTCP value of radiation pneumonitis (RP), esophagitis, and pericarditis were analyzed to evaluate the potential clinical benefits between different planning groups. In addition, a threshold for the ratio of PTV to lungs (%) to determine whether a patient would benefit highly from IMPT was determined using receiver operating characteristic curves. All plans reached target coverage (V70GyRBE ≥ 95%). Compared with VMAT, IMPT resulted in a significantly lower dose of most thoracic normal tissues. For the 1-2, 3-4 and 5-6 lesion groups, the lung V5 was 29.90 ± 9.44%, 58.33 ± 13.35%, and 81.02 ± 5.91% for VMAT and 11.34 ± 3.11% (p < 0.001), 21.45 ± 3.80% (p < 0.001), and 32.48 ± 4.90% (p < 0.001) for IMPT, respectively. The lung V20 was 12.07 ± 4.94%, 25.57 ± 6.54%, and 43.99 ± 11.83% for VMAT and 6.76 ± 1.80% (p < 0.001), 13.14 ± 2.27% (p < 0.01), and 19.62 ± 3.48% (p < 0.01) for IMPT. The Dmean of the total lung was 7.65 ± 2.47 GyRBE, 14.78 ± 2.75 GyRBE, and 21.64 ± 4.07 GyRBE for VMAT and 3.69 ± 1.04 GyRBE (p < 0.001), 7.13 ± 1.41 GyRBE (p < 0.001), and 10.69 ± 1.81 GyRBE (p < 0.001) for IMPT. Additionally, in the VMAT group, the maximum NTCP value of radiation pneumonitis was 73.91%, whereas it was significantly lower in the IMPT group at 10.73%. The accuracy of our NTCP model-based decision model, which combines the number of lesions and PTV/Lungs (%), was 97.6%. The study demonstrated that the IMPT SBRT for multiple lung lesions had satisfactory dosimetry results, even when the number of lesions reached 6. The NTCP model-based decision strategy presented in our study could serve as an effective tool in clinical practice, aiding in the selection of the optimal treatment modality between VMAT and IMPT.

Evaluation of the clinical outcomes and patient satisfaction related to the use of internal eye shields for electron external beam radiation therapy

INTRODUCTION

Cancers around the eye are often treated using orthovoltage machines or by plastic surgery, neither of which are widely available in regional Australia. External beam radiation therapy (EBRT) using electrons and an internal eye shield is an alternative, relatively underreported technique which can provide similar cosmetic and functional outcomes. This report aimed to describe the process for the use of internal eye shields at GenesisCare Fraser Coast Radiation Oncology (GCFCRO) and the associated clinical outcomes and patient perceptions of the delivery and results of this procedure.

METHODS

This project was conducted in two phases. Phase I was an audit of the departmental technique and short-term clinical outcomes of 17 patients who received EBRT for skin cancer near the eyes at GCFCRO in partnership with Wide Bay Hospital and Health Service (WBHHS). Phase II was a survey of nine of those patients to elicit the patient perspective of the delivery and long-term outcomes of the treatment.

RESULTS

Phase I revealed the departmental procedures for simulation, planning and treatment at GCFCRO are consistent with other departments published protocols. Phase II results detailed positive patient perspectives regarding cosmetic outcomes and receipt of EBRT for skin cancer near their eyes.

CONCLUSION

EBRT with an internal eye shield is an acceptable alternative modality to surgery for squamous cell carcinomas (SCC) and basal cell carcinomas (BCC) around the eye in the definitive and adjuvant setting. This is particularly important in regional locations to facilitate patients receiving high-quality care and outcomes locally.

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel theranostic agents, targeting increasingly complex targets, can be well served by comprehensive dosimetry. However, optimization in patient management and patient selection based on risk-factors predicting adverse events and built upon reliable dose-response relations is still an open demand. In this context, artificial intelligence methods, especially machine learning and deep learning algorithms, may play a crucial role. This review provides an overview of upcoming opportunities for integrating artificial intelligence methods into the field of dosimetry in nuclear medicine by improving bone marrow and blood dosimetry accuracy, enabling early identification of potential hematological risk-factors, and allowing for adaptive treatment planning. It will further exemplify inspirational success stories from neighboring disciplines that may be translated to nuclear medicine practices, and will provide conceptual suggestions for future directions. In the future, we expect artificial intelligence-assisted (predictive) dosimetry combined with clinical parameters to pave the way towards truly personalized theranostics in radioligand therapy.

Urethra-Sparing Prostate Cancer Stereotactic Body Radiation Therapy: Sexual Function and Radiation Dose to the Penile Bulb, the Crura, and the Internal Pudendal Arteries From a Randomized Phase 2 Trial

PURPOSE

Erectile dysfunction (ED) is a common side effect after prostate cancer stereotactic body radiation therapy (SBRT). We aimed to assess the correlation between the dose to the penile bulb (PB), internal pudendal arteries (IPA), and crura with the development of ED after ultrahypofractionation as part of a phase 2 clinical trial of urethra-sparing prostate SBRT.

METHODS AND MATERIALS

Among the 170 patients with localized prostate cancer from 9 centers included in the trial, 90 men with Common Terminology Criteria for Adverse Events version 4.03 grade 0 to 1 ED (ED-) at baseline treated with 36.25 Gy in 5 fractions were selected for the present analysis. Doses delivered to the PB, crura, and IPA were analyzed and correlated with grade 2 to 3 ED (ED+) development. The effect on quality of life, assessed by the European Organisation for Research and Treatment of Cancer (EORTC QLQ-PR25) questionnaire, was reported.

RESULTS

After a median follow-up of 6.5 years, 43% (n = 39) of the patients developed ED+, and 57% (n = 51) remained ED-. The dose delivered to the crura was significantly higher in ED+ patients than in ED- patients (7.7 vs 3.6 Gy [P = .014] for the Dmean and 18.5 vs 7.2 Gy [P = .015] for the D2%, respectively). No statistically significant difference between ED+ and ED- patients was observed for the dose delivered to the PB and IPA. The median ED+-free survival was worse in patients receiving a crura Dmean ≥ 4.7 versus < 4.7 Gy (51.5% vs 71.7%, P = .005) and a crura D2% > 12 versus ≤ 12 Gy (54.9% vs 68.9%, P = .015). No ED+-free survival differences were observed for doses delivered to the PB and IPA. Decline in EORTC QLQ-PR25 sexual functioning was significantly more pronounced in patients with higher doses to the crura.

CONCLUSIONS

By keeping a Dmean and D2% to crura below 4.7 and 12 Gy, respectively, the risk of developing ED+ after prostate SBRT may be significantly reduced.

Comparison of the dosimetry of scandium-43 and scandium-44 patient organ doses in relation to commonly used gallium-68 for imaging neuroendocrine tumours

BACKGROUND

Several research groups have explored the potential of scandium radionuclides for theragnostic applications due to their longer half-lives and equal or similar coordination chemistry between their diagnostic and therapeutic counterparts, as well as lutetium-177 and terbium-161, respectively. Unlike the gallium-68/lutetium-177 pair, which may show different in-vivo uptake patterns, the use of scandium radioisotopes promises consistent behaviour between diagnostic and therapeutic radiopeptides. An advantage of scandium's longer half-life over gallium-68 is the ability to study radiopeptide uptake over extended periods and its suitability for centralized production and distribution. However, concerns arise from scandium-44's decay characteristics and scandium-43's high production costs. This study aimed to evaluate the dosimetric implications of using scandium radioisotopes with somatostatin analogues against gallium-68 for PET imaging of neuroendocrine tumours.

METHODS

Absorbed dose per injected activity (AD/IA) from the generated time-integrated activity curve (TIAC) were estimated using the radiopeptides [43/44/44mSc]Sc- and [68Ga]Ga-DOTATATE. The kidneys, liver, spleen, and red bone marrow (RBM) were selected for dose estimation studies. The EGSnrc and MCNP6.1 Monte Carlo (MC) codes were used with female (AF) and male (AM) ICRP phantoms. The results were compared to Olinda/EXM software, and the effective dose concentrations assessed, varying composition between the scandium radioisotopes.

RESULTS

Our findings showed good agreement between the MC codes, with - 3 ± 8% mean difference. Kidneys, liver, and spleen showed differences between the MC codes (min and max) in a range of - 4% to 8%. This was observed for both phantoms for all radiopeptides used in the study. Compared to Olinda/EXM the largest observed difference was for the RBM, of 21% for the AF and 16% for the AM for scandium- and gallium-based radiopeptides. Despite the differences, our findings showed a higher absorbed dose on [43/44Sc]Sc-DOTATATE compared to its 68Ga-based counterpart.

CONCLUSION

This study found that [43/44Sc]Sc-DOTATATE delivers a higher absorbed dose to organs at risk compared to [68Ga]Ga-DOTATATE, assuming equal distribution. This is due to the longer half-life of scandium radioisotopes compared to gallium-68. However, calculated doses are within acceptable ranges, making scandium radioisotopes a feasible replacement for gallium-68 in PET imaging, potentially offering enhanced diagnostic potential with later timepoint imaging.

What proportion of CT scan patients are alive or deceased after 10 years?

PURPOSE

When discussing radiation risks for patients who undergo many CT examinations, some question the risks, believing that most of these patients are already very sick and likely to die within a few years, thus negating worry about radiation risk. This study seeks to evaluate the validity of this notion.

METHODS

In this retrospective single large-hospital study, patients who received CT exams in 2013 were sorted into four cumulative effective dose (CED) groups: Group A (>0 to <10 mSv), Group B (10 to <50 mSv), Group C (50 to < 100 mSv), and Group D (≥100 mSv). The death rates of patients in each group were analyzed, up to December 2023.

RESULTS

36,545 patients underwent CT examinations in 2013 (mean age, 56 ± 20 years, 51.4 % men). Death rates for all dose groups peaked in the year of imaging or 1 year after. At one year after imaging, Group D had 6.7 times and Group C had 4.3 times the death rate of Group A. However, a significant portion of these patients are alive after 10 years, with 1324/2756 patients (48.0 %) in Group C and 282/769 patients (36.7 %) in Group D with the potential to face radiation effects.

CONCLUSIONS

While it is true that patients receiving relatively higher doses (≥50 mSv) are more likely to die within the first two years of receiving such doses, nearly one-third to half remain alive a decade after their CT scans, potentially facing the effects of radiation. This knowledge may help policymakers and practitioners.

Voxel-Level Dosimetry for Combined Iodine 131 Radiopharmaceutical Therapy and External Beam Radiation Therapy Treatment Paradigms for Head and Neck Cancer

PURPOSE

Targeted radiopharmaceutical therapy (RPT) in combination with external beam radiation therapy (EBRT) shows promise as a method to increase tumor control and mitigate potential high-grade toxicities associated with re-treatment for patients with recurrent head and neck cancer. This work establishes a patient-specific dosimetry framework that combines Monte Carlo-based dosimetry from the 2 radiation modalities at the voxel level using deformable image registration (DIR) and radiobiological constructs for patients enrolled in a phase 1 clinical trial combining EBRT and RPT.

METHODS AND MATERIALS

Serial single-photon emission computed tomography (SPECT)/computed tomography (CT) patient scans were performed at approximately 24, 48, 72, and 168 hours postinjection of 577.2 MBq/m2 (15.6 mCi/m2) CLR 131, an iodine 131-containing RPT agent. Using RayStation, clinical EBRT treatment plans were created with a treatment planning CT (TPCT). SPECT/CT images were deformably registered to the TPCT using the Elastix DIR module in 3D Slicer software and assessed by measuring mean activity concentrations and absorbed doses. Monte Carlo EBRT dosimetry was computed using EGSnrc. RPT dosimetry was conducted using RAPID, a GEANT4-based RPT dosimetry platform. Radiobiological metrics (biologically effective dose and equivalent dose in 2-Gy fractions) were used to combine the 2 radiation modalities.

RESULTS

The DIR method provided good agreement for the activity concentrations and calculated absorbed dose in the tumor volumes for the SPECT/CT and TPCT images, with a maximum mean absorbed dose difference of -11.2%. Based on the RPT absorbed dose calculations, 2 to 4 EBRT fractions were removed from patient EBRT treatments. For the combined treatment, the absorbed dose to target volumes ranged from 57.14 to 75.02 Gy. When partial volume corrections were included, the mean equivalent dose in 2-Gy fractions to the planning target volume from EBRT + RPT differed -3.11% to 1.40% compared with EBRT alone.

CONCLUSIONS

This work demonstrates the clinical feasibility of performing combined EBRT + RPT dosimetry on TPCT scans. Dosimetry guides treatment decisions for EBRT, and this work provides a bridge for the same paradigm to be implemented within the rapidly emerging clinical RPT space.

Stereotactic Body Radiotherapy for Primary Renal Cell Carcinoma: A Case-Based Radiosurgery Society Practice Guide

Traditionally, renal cell carcinoma (RCC) was considered a radioresistant tumor, thereby limiting definitive radiation therapy management options. However, several recent studies have demonstrated that stereotactic body radiotherapy (SBRT) can achieve high rates of local control for the treatment of primary RCC. In the setting of an expanding use of SBRT for primary RCC, it is crucial to provide guidance on practical considerations such as patient selection, fractionation, target delineation, and response assessment. This is particularly important in challenging scenarios where a paucity of evidence exists, such as in patients with a solitary kidney, bulky tumors, or tumor thrombus. The Radiosurgery Society endorses this case-based guide to provide a practical framework for delivering SBRT to primary RCC, exemplified by three cases. This article explores topics of tumor size and dose fractionation, impact on renal function and treatment in the setting of a solitary kidney, and radiation's role in the management of inferior vena cava tumor thrombus. Additionally, we review existing evidence and expert opinion on target delineation, advanced techniques like MRI-guided SBRT, and SBRT response assessment.

Particle arc therapy: Status and potential

There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook.

Optimal virtual monochromatic images for assessing metastatic lateral cervical lymph nodes in patients with papillary thyroid carcinoma using dual‑layer spectral detector computed tomography

PURPOSE

To determine the optimal virtual monochromatic images (VMIs) from dual-layer spectral detector computed tomography for the visualization and diagnosis of metastatic lateral cervical lymph nodes (LNs) in patients with papillary thyroid carcinoma (PTC).

METHODS

Ninety-five lateral cervical LNs (49 metastatic and 46 non-metastatic) derived from 24 patients (16 females; mean age, 40.0 ± 13.4 years) were included. 40-100 kiloelectron voltage (keV) VMIs, 120 keV VMI and conventional 120 kV peak (kVp) polyenergetic image (PI) were reconstructed. Five-point scale of subjective image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of LNs were assessed and compared among each VMI and 120 kVp PI. Receiver operating characteristic (ROC) curves and Delong tests were used to assess and compare the diagnostic efficacy of arterial enhancement fraction (AEF) based on each VMI and 120 kVp PI.

RESULTS

40 keV VMI showed significantly higher SNR and CNR in both arterial and venous phases, and better image quality in arterial phase than 70-100 keV VMIs, 120 keV VMI, and 120 kVp PI (all p < 0.05). In all sets of images, AEF values of metastatic LNs were significantly higher than those of non-metastatic LNs (all p < 0.05). When using AEF value of 40 keV VMI to diagnose metastatic lateral cervical LNs, an area under ROC curve (AUC) of 0.878, sensitivity of 87.8 % and specificity of 80.4 % could be obtained, while the AUC of AEF value of 120 kVp PI was 0.815 (p = 0.154).

CONCLUSION

40 keV VMI might be optimal for displaying and diagnosing the metastatic lateral cervical LNs in patients with PTC.

Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy

PURPOSE

To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT) and radiation dose (RD) distribution images.

MATERIALS AND METHODS

A total of 273 EC patients underwent VMAT were retrospectively reviewed and enrolled from two centers and divided into training (n = 152), internal validation (n = 66), and external validation (n = 55) cohorts, respectively. Radiomic and dosiomic features along with DL features using convolutional neural networks were extracted and screened from CT and RD images to predict RE. The performance of these models was evaluated and compared using the area under curve (AUC) of the receiver operating characteristic curves (ROC).

RESULTS

There were 5 and 10 radiomic and dosiomic features were screened, respectively. XGBoost achieved a best AUC of 0.703, 0.694 and 0.801, 0.729 with radiomic and dosiomic features in the internal and external validation cohorts, respectively. ResNet34 achieved a best prediction AUC of 0.642, 0.657 and 0.762, 0.737 for radiomics based DL model (DLR) and RD based DL model (DLD) in the internal and external validation cohorts, respectively. Combined model of DLD + Dosiomics + clinical factors achieved a best AUC of 0.913, 0.821 and 0.805 in the training, internal, and external validation cohorts, respectively.

CONCLUSION

Although the dose was not responsible for the prediction accuracy, the combination of various feature extraction methods was a factor in improving the RE prediction accuracy. Combining DLD with dosiomic features was promising in the pretreatment prediction of RE for EC patients underwent VMAT.

Three-dimensional assessment of root changes after Le Fort I osteotomy

The study aim was to assess the volumetric, linear, and morphological changes of the maxillary incisor, canine, and premolar roots following Le Fort I osteotomy. Sixty patients (585 teeth) were included retrospectively from among individuals who underwent combined orthodontics and orthognathic surgery. The study group comprised 30 patients who underwent orthodontics and one-piece Le Fort I osteotomy, while the control group consisted of 30 patients who underwent orthodontics and bilateral sagittal split osteotomy but no maxillary surgery. CBCT scans were obtained at four time points: preoperative, 6 months, 1 year, and 2 years postoperative. A fully automated three-dimensional evaluation protocol was utilized to assess root changes of the maxillary teeth. Significant differences in the apical and middle parts of the teeth were observed between the study and control groups at 1 and 2 years postoperative, with greater percentage changes in the study group (all P < 0.05). Greater root remodelling in the canines, first and second premolars was observed in the study group (all P < 0.005). Spearman correlation analysis indicated a positive relationship between root remodelling and maxillary advancement, with larger advancements contributing to increased root remodelling in the apical and middle root parts (both P < 0.05). These findings can be valuable for surgeons and orthodontists in evaluating root changes.

Comprehensive assessment of nonuniform image quality: Application to imaging near metal

PURPOSE

Comprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal-to-noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal.

METHODS

A modular phantom design employing a gyroid lattice is developed to enable the co-registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D-FSE and MAVRIC-SL scan protocols on a 3T MRI scanner.

RESULTS

The spatial resolution method demonstrates a worst-case error of 0.17 pixels for measuring in-plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co-registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost.

CONCLUSION

The phantom and associated analysis methods can elucidate complex image quality trade-offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.

Generating Synthetic MR Spectroscopic Imaging Data with Generative Adversarial Networks to Train Machine Learning Models

PURPOSE

To develop a new method to generate synthetic MR spectroscopic imaging (MRSI) data for training machine learning models.

METHODS

This study targeted routine MRI examination protocols with single voxel spectroscopy (SVS). A novel model derived from pix2pix generative adversarial networks was proposed to generate synthetic MRSI data using MRI and SVS data as inputs. T1- and T2-weighted, SVS, and reference MRSI data were acquired from healthy brains with clinically available sequences. The proposed model was trained to generate synthetic MRSI data. Quantitative evaluation involved the calculation of the mean squared error (MSE) against the reference and metabolite ratio value. The effect of the location of and the number of the SVS data on the quality of the synthetic MRSI data was investigated using the MSE.

RESULTS

The synthetic MRSI data generated from the proposed model were visually closer to the reference. The 95% confidence interval (CI) of the metabolite ratio value of synthetic MRSI data overlapped with the reference for seven of eight metabolite ratios. The MSEs tended to be lower in the same location than in different locations. The MSEs among groups of numbers of SVS data were not significantly different.

CONCLUSION

A new method was developed to generate MRSI data by integrating MRI and SVS data. Our method can potentially increase the volume of MRSI data training for other machine learning models by adding SVS acquisition to routine MRI examinations.

Dose prescription for stereotactic body radiotherapy: general and organ-specific consensus statement from the DEGRO/DGMP Working Group Stereotactic Radiotherapy and Radiosurgery

PURPOSE AND OBJECTIVE

To develop expert consensus statements on multiparametric dose prescriptions for stereotactic body radiotherapy (SBRT) aligning with ICRU report 91. These statements serve as a foundational step towards harmonizing current SBRT practices and refining dose prescription and documentation requirements for clinical trial designs.

MATERIALS AND METHODS

Based on the results of a literature review by the working group, a two-tier Delphi consensus process was conducted among 24 physicians and physics experts from three European countries. The degree of consensus was predefined for overarching (OA) and organ-specific (OS) statements (≥ 80%, 60-79%, < 60% for high, intermediate, and poor consensus, respectively). Post-first round statements were refined in a live discussion for the second round of the Delphi process.

RESULTS

Experts consented on a total of 14 OA and 17 OS statements regarding SBRT of primary and secondary lung, liver, pancreatic, adrenal, and kidney tumors regarding dose prescription, target coverage, and organ at risk dose limitations. Degree of consent was ≥ 80% in 79% and 41% of OA and OS statements, respectively, with higher consensus for lung compared to the upper abdomen. In round 2, the degree of consent was ≥ 80 to 100% for OA and 88% in OS statements. No consensus was reached for dose escalation to liver metastases after chemotherapy (47%) or single-fraction SBRT for kidney primaries (13%). In round 2, no statement had 60-79% consensus.

CONCLUSION

In 29 of 31 statements a high consensus was achieved after a two-tier Delphi process and one statement (kidney) was clearly refused. The Delphi process was able to achieve a high degree of consensus for SBRT dose prescription. In summary, clear recommendations for both OA and OS could be defined. This contributes significantly to harmonization of SBRT practice and facilitates dose prescription and reporting in clinical trials investigating SBRT.

Mass detection in automated three dimensional breast ultrasound using cascaded convolutional neural networks

PURPOSE

Early detection of breast cancer has a significant effect on reducing its mortality rate. For this purpose, automated three-dimensional breast ultrasound (3-D ABUS) has been recently used alongside mammography. The 3-D volume produced in this imaging system includes many slices. The radiologist must review all the slices to find the mass, a time-consuming task with a high probability of mistakes. Therefore, many computer-aided detection (CADe) systems have been developed to assist radiologists in this task. In this paper, we propose a novel CADe system for mass detection in 3-D ABUS images.

METHODS

The proposed system includes two cascaded convolutional neural networks. The goal of the first network is to achieve the highest possible sensitivity, and the second network's goal is to reduce false positives while maintaining high sensitivity. In both networks, an improved version of 3-D U-Net architecture is utilized in which two types of modified Inception modules are used in the encoder section. In the second network, new attention units are also added to the skip connections that receive the results of the first network as saliency maps.

RESULTS

The system was evaluated on a dataset containing 60 3-D ABUS volumes from 43 patients and 55 masses. A sensitivity of 91.48% and a mean false positive of 8.85 per patient were achieved.

CONCLUSIONS

The suggested mass detection system is fully automatic without any user interaction. The results indicate that the sensitivity and the mean FP per patient of the CADe system outperform competing techniques.

How to accurately quantify brain magnetic susceptibility in the context of Parkinson's disease: Validation on phantoms and healthy volunteers at 1.5 and 3 T

Currently, brain iron content represents a new neuromarker for understanding the physiopathological mechanisms leading to Parkinson's disease (PD). In vivo quantification of biological iron is possible by reconstructing magnetic susceptibility maps obtained using quantitative susceptibility mapping (QSM). Applying QSM is challenging, as up to now, no standardization of acquisition protocols and phase image processing has emerged from referenced studies. Our objectives were to compare the accuracy and the sensitivity of 10 QSM pipelines built from algorithms from the literature, applied on phantoms data and on brain data. Two phantoms, with known magnetic susceptibility ranges, were created from several solutions of gadolinium chelate. Twenty healthy volunteers from two age groups were included. Phantoms and brain data were acquired at 1.5 and 3 T, respectively. Susceptibility-weighted images were obtained using a 3D multigradient-recalled-echo sequence. For brain data, 3D anatomical T1- and T2-weighted images were also acquired to segment the deep gray nuclei of interest. Concerning in vitro data, the linear dependence of magnetic susceptibility versus gadolinium concentration and deviations from the theoretically expected values were calculated. For brain data, the accuracy and sensitivity of the QSM pipelines were evaluated in comparison with results from the literature and regarding the expected magnetic susceptibility increase with age, respectively. A nonparametric Mann-Whitney U-test was used to compare the magnetic susceptibility quantification in deep gray nuclei between the two age groups. Our methodology enabled quantifying magnetic susceptibility in human brain and the results were consistent with those from the literature. Statistically significant differences were obtained between the two age groups in all cerebral regions of interest. Our results show the importance of optimizing QSM pipelines according to the application and the targeted magnetic susceptibility range, to achieve accurate quantification. We were able to define the optimal QSM pipeline for future applications on patients with PD.

Comparison of the equivalent doses of the eye lenses, thyroid, and mammary gland among three pediatric and one adult anthropomorphic phantom during the chest CT examinations using a 40 mm volume helical scan

Equivalent doses for the eye lenses, thyroid, and mammary glands were measured and compared between one adult and three pediatric anthropomorphic phantoms during chest computed tomography (CT) using 40 mm volume helical scan on the Aquilion ONE GENESIS Edition CT equipment. Placing an optically stimulated luminescence dosemeter (OSLD) on the eye lenses, thyroid, and mammary gland, we measured and compared the equivalent dose of OSLD among different phantoms during chest CT using a helical scan. Compared with adults, the equivalent doses to the eye lens, thyroid, and mammary glands were ~81%, 77%, and 63% lower in newborns, 1-year-olds, and 5-year-olds using comparable image noise during chest CT.

Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare

AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases inherent within these models remains largely unexplored. This study tackles these concerns by thoroughly re-examining AI-driven segmentation for hip and knee bony anatomy. While advanced imaging modalities like CT and MRI offer comprehensive views, plain radiographs (X-rays) predominate the standard initial clinical assessment due to their widespread availability, low cost, and rapid acquisition. Hence, we focused on plain radiographs to ensure the utilization of our contribution in diverse healthcare settings, including those with limited access to advanced imaging technologies. This work provides insights into the underlying causes of biases in AI-based knee and hip image segmentation through an extensive evaluation, presenting targeted mitigation strategies to alleviate biases related to sex, race, and age, using an automatic segmentation that is fair, impartial, and safe in the context of AI. Our contribution can enhance inclusivity, ethical practices, equity, and an unbiased healthcare environment with advanced clinical outcomes, aiding decision-making and osteoarthritis research. Furthermore, we have made all the codes and datasets publicly and freely accessible to promote open scientific research.

Cardiorespiratory motion characteristics and their dosimetric impact on cardiac stereotactic body radiotherapy

BACKGROUND

Cardiac stereotactic body radiotherapy (CSBRT) is an emerging and promising noninvasive technique for treating refractory arrhythmias utilizing highly precise, single or limited-fraction high-dose irradiations. This method promises to revolutionize the treatment of cardiac conditions by delivering targeted therapy with minimal exposure to surrounding healthy tissues. However, the dynamic nature of cardiorespiratory motion poses significant challenges to the precise delivery of dose in CSBRT, introducing potential variabilities that can impact treatment efficacy. The complexities of the influence of cardiorespiratory motion on dose distribution are compounded by interplay and blurring effects, introducing additional layers of dose uncertainty. These effects, critical to the understanding and improvement of the accuracy of CSBRT, remain unexplored, presenting a gap in current clinical literature.

PURPOSE

To investigate the cardiorespiratory motion characteristics in arrhythmia patients and the dosimetric impact of interplay and blurring effects induced by cardiorespiratory motion on CSBRT plan quality.

METHODS

The position and volume variations in the substrate target and cardiac substructures were evaluated in 12 arrhythmia patients using displacement maximum (DMX) and volume metrics. Moreover, a four-dimensional (4D) dose reconstruction approach was employed to examine the dose uncertainty of the cardiorespiratory motion.

RESULTS

Cardiac pulsation induced lower DMX than respiratory motion but increased the coefficient of variation and relative range in cardiac substructure volumes. The mean DMX of the substrate target was 0.52 cm (range: 0.26-0.80 cm) for cardiac pulsation and 0.82 cm (range: 0.32-2.05 cm) for respiratory motion. The mean DMX of the cardiac structure ranged from 0.15 to 1.56 cm during cardiac pulsation and from 0.35 to 1.89 cm during respiratory motion. Cardiac pulsation resulted in an average deviation of -0.73% (range: -4.01%-4.47%) in V25 between the 3D and 4D doses. The mean deviations in the homogeneity index (HI) and gradient index (GI) were 1.70% (range: -3.10%-4.36%) and 0.03 (range: -0.14-0.11), respectively. For cardiac substructures, the deviations in D50 due to cardiac pulsation ranged from -1.88% to 1.44%, whereas the deviations in Dmax ranged from -2.96% to 0.88% of the prescription dose. By contrast, the respiratory motion led to a mean deviation of -1.50% (range: -10.73%-4.23%) in V25. The mean deviations in HI and GI due to respiratory motion were 4.43% (range: -3.89%-13.98%) and 0.18 (range: -0.01-0.47) (p < 0.05), respectively. Furthermore, the deviations in D50 and Dmax in cardiac substructures for the respiratory motion ranged from -0.28% to 4.24% and -4.12% to 1.16%, respectively.

CONCLUSIONS

Cardiorespiratory motion characteristics vary among patients, with the respiratory motion being more significant. The intricate cardiorespiratory motion characteristics and CSBRT plan complexity can induce substantial dose uncertainty. Therefore, assessing individual motion characteristics and 4D dose reconstruction techniques is critical for implementing CSBRT without compromising efficacy and safety.

An image quality assessment index based on image features and keypoints for X-ray CT images

Optimization tasks in diagnostic radiological imaging require objective quantitative metrics that correlate with the subjective perception of observers. However, although one such metric, the structural similarity index (SSIM), is popular, it has limitations across various aspects in its application to medical images. In this study, we introduce a novel image quality evaluation approach based on keypoints and their associated unique image feature values, focusing on developing a framework to address the need for robustness and interpretability that are lacking in conventional methodologies. The proposed index quantifies and visualizes the distance between feature vectors associated with keypoints, which varies depending on changes in the image quality. This metric was validated on images with varying noise levels and resolution characteristics, and its applicability and effectiveness were examined by evaluating images subjected to various affine transformations. In the verification of X-ray computed tomography imaging using a head phantom, the distances between feature descriptors for each keypoint increased as the image quality degraded, exhibiting a strong correlation with the changes in the SSIM. Notably, the proposed index outperformed conventional full-reference metrics in terms of robustness to various transformations which are without changes in the image quality. Overall, the results suggested that image analysis performed using the proposed framework could effectively visualize the corresponding feature points, potentially harnessing lost feature information owing to changes in the image quality. These findings demonstrate the feasibility of applying the novel index to analyze changes in the image quality. This method may overcome limitations inherent in conventional evaluation methodologies and contribute to medical image analysis in the broader domain.

Teaching Medical Devices through Interactive Innovation: Challenges and Rewards

Medical devices are manmade objects existing at the interface between numerous disciplines. They range from as simple as medical gloves to as complex as artificial limbs. This versatility of medical devices and their inherent interdisciplinary nature means that academic courses on them are attended by cohorts of students from varieties of academic backgrounds, who bring with them similarly broad spectra of interests. To satisfy the learning expectations of each and every student in such diverse classes is a daunting task for the instructor. After many years of teaching medical devices at undergraduate and graduate levels at three different universities in the states of Illinois and California, I have come up with an instructional method that solves this challenge by engaging students in the co-creation of the curriculum via selection of their own medical devices of interest and presentation to the class for collective analysis. The threefold presentations are designed so that they reflect an ascent along the hierarchy of a learning taxonomy extending from foundational concepts to critical assessment of knowledge to creative displays of it. In such a way, the students are acquainted with the ability of critical and creative thinking at the expense of rote memorization or inculcation and are prepared to enter the field of medical devices as innovation-centered individuals. The specifics of this new method of instruction are reported here, with the hope that they will be useful to fellow instructors in any interdisciplinary course that benefits from a balance between the rigorous coverage of the instructional material pertaining to engineering and medicine and the flexible selection of topics that comply with students' individual interests.

Molecular GBM versus Histopathological GBM: Radiology-Pathology-Genetic Correlation and the New WHO 2021 Definition of Glioblastoma

Given the recent advances in molecular pathogenesis of tumors, with better correlation with tumor behavior and prognosis, major changes were made to the new 2021 World Health Organization (WHO) classification of CNS tumors, including updated criteria for diagnosis of glioblastoma (GBM). Diagnosis of GBM now requires absence of isocitrate dehydrogenase and histone 3 mutations (IDH-wild-type and H3-wild-type) as the basic cornerstone, with elimination of the IDH-mutant category. The requirements for diagnosis were conventionally histopathological, based on the presence of pathognomonic features such as microvascular proliferation and necrosis. However, even if these histologic features are absent, many lower-grade (WHO grade 2/3) diffuse astrocytic gliomas behave clinically similar to GBM (grade 4). The 2021 WHO classification introduced new molecular criteria that can be used to upgrade the diagnosis of such histologically lower-grade, IDH-wild-type, astrocytomas to GBM. The 3 molecular criteria include: concurrent gain of whole chromosome 7 and loss of whole chromosome 10 (+7/-10); telomerase reverse transcriptase promoter mutation; and epidermal growth factor receptor amplification. Given these changes, it is now strongly recommended to have molecular analysis of WHO grade 2/3 diffuse astrocytic, IDH-wild-type, gliomas in adult patients, as identification of any of the above mutations allows for upgrading the tumor to WHO grade 4 ("molecular GBM") with important prognostic implications. Despite an early stage, there is active ongoing research on the unique MR imaging features of molecular GBM. This paper highlights the differences between "molecular" and "histopathological" GBM, with the aim of providing a basic understanding about these changes.

Utility of block-matching and 3D filter for reproducibility of lung density and denoising in low-dose chest CT: A pilot study

PURPOSE

This study aimed to acquire an image quality consistent with that of full-dose chest computed tomography (CT) when obtaining low-dose chest CT images and to analyze the effects of block-matching and 3D (BM3D) filters on lung density measurements and noise reduction in lung parenchyma.

METHODS

Using full-dose chest CT images, we evaluated lung density measurements and noise reduction in lung parenchyma images for low-dose chest CT. Three filters (median, Wiener, and the proposed BM3D) were applied to low-dose chest CT images for comparison and analysis with images from full-dose chest CT. To evaluate lung density measurements, we measured CT attenuation at the 15th percentile of the lung CT histogram. The coefficient of variation (COV) and contrast-to-noise ratio (CNR) were used to evaluate the noise level.

RESULTS

The 15th percentile of the lung CT histogram showed the smallest difference between full- and low-dose CT when applying the BM3D filter, and the highest difference between full- and low-dose CT without filters (full-dose =  - 926.28 ± 0.32, BM3D =  - 926.65 ± 0.32, and low-dose =  - 959.43 ± 0.95) (p < 0.05). The COV was smallest when applying the BM3D filter, whereas the CNR was the highest (p < 0.05).

CONCLUSIONS

The results of the study prove that the BM3D filter can reduce image noise while increasing the reproducibility of the lung density, even for low-dose chest CT.

Value of automated breast ultrasound in screening: Standalone and as a supplemental to digital breast tomosynthesis

We aimed to determine the value of standalone and supplemental automated breast ultrasound (ABUS) in detecting cancers in an opportunistic screening setting with digital breast tomosynthesis (DBT) and compare this combined screening method to DBT and ABUS alone in women older than 39 years with BI-RADS B-D density categories. In this prospective opportunistic screening study, 3466 women aged 39 or older with BI-RADS B-D density categories and with a mean age of 50 were included. The screening protocol consisted of DBT mediolateral-oblique views, 2D craniocaudal views, and ABUS with three projections for both breasts. ABUS was evaluated blinded to mammography findings. Statistical analysis evaluated diagnostic performance for DBT, ABUS, and combined workflows. Twenty-nine cancers were screen-detected. ABUS and DBT exhibited the same cancer detection rates (CDR) at 7.5/1000 whereas DBT + ABUS showed 8.4/1000, with ABUS contributing an additional CDR of 0.9/1000. Standalone ABUS outperformed DBT in detecting 12.5% more invasive cancers. DBT displayed better accuracy (95%) compared to ABUS (88%) and combined approach (86%). Sensitivities for DBT and ABUS were the same (84%), with DBT + ABUS showing a higher rate (94%). DBT outperformed ABUS in specificity (95% vs. 88%). DBT + ABUS exhibited a higher recall rate (14.89%) compared to ABUS (12.38%) and DBT (6.03%) (p < .001). Standalone ABUS detected more invasive cancers compared to DBT, with a higher recall rate. The combined approach showed a higher CDR by detecting one additional cancer per thousand.

Improving diagnostic confidence in low-dose dual-energy CTE with low energy level and deep learning reconstruction

OBJECTIVE

To demonstrate the value of using 50 keV virtual monochromatic images with deep learning image reconstruction (DLIR) in low-dose dual-energy CT enterography (CTE).

METHODS

In this prospective study, 114 participants (62 % M; 41.9 ± 16 years) underwent dual-energy CTE. The early-enteric phase was performed using standard-dose (noise index (NI): 8) and images were reconstructed at 70 keV and 50 keV with 40 % strength ASIR-V (ASIR-V40%). The late-enteric phase used low-dose (NI: 12) and images were reconstructed at 50 keV with ASIR-V40%, and DLIR at medium (DLIR-M) and high strength (DLIR-H). Image standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge-rise-slope (ERS) were computed. The quantitative comb sign score was calculated for the 27 patients with Crohn's disease. The subjective noise, image contrast, display of rectus artery were scored using a 5-point scale by two radiologists blindly.

RESULTS

Effective dose was reduced by 50 % (P < 0.001) in the late-enteric phase to 3.26 mSv. The lower-dose 50 keV-DLIR-H images (SD:17.7 ± 0.5HU) had similar image noise (P = 0.97) as the standard-dose 70 keV-ASIR-V40% images (SD:17.7 ± 0.73HU), but with higher (P < 0.001) SNR, CNR, ERS and quantitative comb sign score (5.7 ± 0.17, 1.8 ± 0.12, 156.04 ± 5.21 and 5.05 ± 0.73, respectively). Furthermore, the lower-dose 50 keV-DLIR-H images obtained the highest score in the rectus artery visibility (4.27 ± 0.6).

CONCLUSIONS

The 50 keV images in dual-energy CTE with DLIR provides high-quality images, with a 50 % reduction in radiation dose. Images with high contrast and density resolutions significantly enhance the diagnostic confidence of Crohn's disease and are essential for the clinical development of individualized treatment plans.

Secondary cancer risk in six anatomical sites when using PAT, IMPT, and VMAT/IMRT radiotherapy

BACKGROUND AND PURPOSE

Compared to intensity modulated proton therapy (IMPT), proton arc therapy (PAT) is expected to improve dose conformality, delivery efficiency, and provide a more favorable LET distribution. Alternatively, the low-dose bath is potentially spread over larger volumes, which could impact the likelihood of developing a radiation-induced, secondary cancer (SC). The goal of this study was to evaluate this risk in several anatomical sites using newly developed commercial tools.

MATERIALS AND METHODS

Treatment plans encompassing six anatomical sites, five patients per site, and three techniques per patient were created using RayStation. Techniques included PAT and IMPT for protons, and either volumetrically modulated radiotherapy (VMAT) or intensity modulated radiotherapy (IMRT) for photons. Risk estimates were based on the organ-equivalent dose (OED) concept using both Schneider's mechanistic dose-response model for carcinoma induction and a linear dose-response model.

RESULTS

With few exceptions, mean and integral dose were lowest with PAT. For protons, the factor OEDIMPT/OEDPAT ranged from 0.7 to 1.8 with both the mechanistic and linear model, while for photons OEDphoton/OEDPAT ranged from 1.5 to 10 using the mechanistic model and 1.3-9.6 using the linear model. A strong correlation was found between mean dose and OED for organs with significant repopulation/repair (high R value) and less cell death from single hit interactions (low α value).

CONCLUSION

Based results from both mechanistic and linear risk models, the transition from IMPT to PAT should not substantially affect SC risk in patients treated with proton therapy. Additionally, when using Schneider's model, the shapes of the dose-response curves can be used as a good predictor of how SC risk will respond to shifts from intermediate dose to low dose as anticipated when moving from IMPT to PAT.

Microstructure of the radial head: Insights into anatomical variations and implications for advanced interventions

Appropriate management of radial head fractures is integral to prevent long-term consequences like chronic pain and loss of motion. Advanced imaging systems, like micro-computed tomography (μCT), are valuable for understanding radial head fracture patterns as they utilize micrometer scale resolution to define important parameters of bone health like cortical density and trabecular thickness. The purpose of this study was to identify and describe the structural morphology of the radial head utilizing μCT. Nine fresh-frozen cadaveric human radii were divided into four equal quadrants, based, and labeled as posteromedial, posterolateral, anteromedial, and anterolateral. Quadrants were scanned with a SCANCO MicroCT40 with both cortical and cancellous bone density measurements at a resolution of 36.0 μm. Bone density, direct trabecular number, and trabecular thickness were recorded as milligrams of hydroxyapatite/cm3. A one-way repeated measures ANOVA was performed to compare the bone densities, trabecular number, and trabecular thickness of each of the four quadrants (p < 0.05). The posteromedial quadrant contained substantially more bone than other quadrants. Significantly greater bone densities were found in the posteromedial quadrant (148.1 mg of HA/cm3) compared to the anteromedial quadrant (54.6 mg of HA/cm3), posterolateral quadrant (137.5 mg of HA/cm3) compared to the anteromedial quadrant (54.6 mg of HA/cm3), and posterolateral quadrant (137.5 mg of HA/cm3) compared to the anterolateral quadrant (58.1 mg of HA/cm3). The trabecular number was not significantly different between quadrants. Trabecular thickness was significantly lower in the anterolateral (0.1417 mg of HA/cm3) and anteromedial (0.1416 mg of HA/cm3) quadrants compared to the posteromedial (0.1809 mg of HA/cm3) quadrant. The posterior half of the radial head was found to have a higher density of columns and arches compared to the anterior half. The microstructure of trabecular bone in the distal radius forms columns, struts, and arches, which allow for efficient transmission of stress through the bone. The microstructure of the radial head has similar microarchitecture to the distal radius with the present study identifying the presence of columns and arches in the radial head. These structures, along with trabecular density, in the posterior radial head may explain the lower incidence of fractures involving the posterior half of the radial head. Furthermore, our study supports the idea that the high incidence of fractures involving the anterolateral quadrant is due to microarchitecture characteristics and the relative lack of supportive structures compared to other areas. The novel insight gained from this study will aid in the development of advanced interventions for preventative measures and better treatment of radial head fractures like more satisfactory purchase when screws are directed towards the denser posteromedial quadrant.

Self-supervised tomographic image noise suppression via residual image prior network

Computed tomography (CT) denoising is a challenging task in medical imaging that has garnered considerable attention. Supervised networks require a lot of noisy-clean image pairs, which are always unavailable in clinical settings. Existing self-supervised algorithms for suppressing noise with paired noisy images have limitations, such as ignoring the residual between similar image pairs during training and insufficiently learning the spectrum information of images. In this study, we propose a Residual Image Prior Network (RIP-Net) to sufficiently model the residual between the paired similar noisy images. Our approach offers new insights into the field by addressing the limitations of existing methods. We first establish a mathematical theorem clarifying the non-equivalence between similar-image-based self-supervised learning and supervised learning. It helps us better understand the strengths and limitations of self-supervised learning. Secondly, we introduce a novel regularization term to model a low-frequency residual image prior. This can improve the accuracy and robustness of our model. Finally, we design a well-structured denoising network capable of exploring spectrum information while simultaneously sensing context messages. The network has dual paths for modeling high and low-frequency compositions in the raw noisy image. Additionally, context perception modules capture local and global interactions to produce high-quality images. The comprehensive experiments on preclinical photon-counting CT, clinical brain CT, and low-dose CT datasets, demonstrate that our RIP-Net is superior to other unsupervised denoising methods.

Optimizing the feasibility of polyvinyl alcohol-potassium iodine gel for medical dosimeter

This work aims to improve the post stabilty of reusable potassium iodide hydrogel dosimter. A reusable and low-cost radiochromic dosimeter containing a gel matrix of polyvinyl alcohol, potassium iodide dye, froctose as reducing agent and glutaraldehyde as cross-linking agent was developed for dose calibration in radiotherapy. The gel samples were exposed to different absorbed doses using a medical linear acceleration. UV-vis Spectrophotometry was utilized to investigate the changes in optical-properties of irradiated gels with regard to peak wavelength of 353 nm. The stability of the gel (one of the most limitation of using this dosimeter) was improved significantly by the addition of certain concentrations of dimethyl sulfoxide. The two-dimensional optical imaging system of charge-coupled-device (CCD) camera with a uniform RGB light-emitting-diode (LED) array source was used for diffusion coefficient purpose using two dimensional gel template. The value of diffusion coefficient reported is significant and highly reduced compared with other dosimeters reported in the literatures. Moreover, heating the improved gels to certain temperatures results in resetting their optical properties, which makes it possible to reuse for multiple times.

Evaluation of the performance of digital x-ray systems in pelvis radiography

The aim of this study was to investigate the performance of eight digital radiography systems and to optimise the dose-image quality relationship for digital pelvis radiography. The study involved eight digital radiography systems used for general examinations at Vilnius University Hospital Santaros Klinikos. An anthropomorphic pelvic phantom (CIRS, US) was used to simulate a patient undergoing clinical pelvis radiography. Dose quantities entrance surface dose, dose area product (DAP) and exposure parameters (kVp, mA, mAs) were measured and the effects on the images were evaluated, considering physical contrast to noise ratio (CNR) and observer-based evaluations as image quality metrics. Increasing the tube voltage by 5 kVp from standard protocol led to a reduction in radiation dose (DAP) by 12%-20% with a slight impact on image quality (CNR decreases by 2%-10%). There was an inter-observer variability in image rating across different equipment (kappa value between 0 and 0.3); however, both observers agreed that increasing kVp up to 85-90 kV had no effect on perceived image quality. The results indicate that optimisation strategies should be tailored specifically for each x-ray system since significant performance differences and wide variations in radiation dose exist across various digital radiography systems used in clinical settings. The use of high kVp can be used for dose optimisation in digital pelvis radiography without compromising image diagnostic accuracy.

A rotating beam-blocker method for cone beam CT scatter correction

BACKGROUND

Cone beam CT (CBCT) is widely utilized in clinics. However, the scatter artifact degrades the CBCT image quality, hampering the expansion of CBCT applications. Recently, beam-blocker methods have been used for CBCT scatter correction and proved their high cost-effectiveness.

PURPOSE

A rotating beam-blocker (RBB) method for CBCT scatter correction was proposed to complete scatter correction and image reconstruction within a single scan in both full- and half-fan scan scenarios.

METHODS

The RBB consisted of two open regions and two blocked regions, and was designed as a centrosymmetric structure. The open and blocked projections could be alternatively obtained within one single rotation. The open projections were corrected with the scatter signal calculated from the blocked projections, and then used to reconstruct the 3D image via the Feldkamp-Davis-Kress algorithm. The performance of the RBB method was evaluated on head and pelvis phantoms in scenarios with and without a bowtie filter. The images obtained from nine repeated scans in each scenario were used to calculate the evaluation metrics including the CT number error, spatial nonuniformity (SNU) and contrast-to-noise ratio (CNR).

RESULTS

For the head phantom, the CT number error was decreased to <5 after scatter correction from >200 HU before correction when scanned without a bowtie filter, and to <4 from >160 HU when scanned with a full bowtie filter. For the pelvis phantom, the CT number error was reduced to <12 after scatter correction from >250 HU before correction when scanned without a bowtie filter, and to <10 from >190 HU when scanned with a half bowtie filter. After scatter correction, the uniformity and contrast were both improved, resulting in an SNU of >79% decrease and CNR of >2 times increase, respectively.

CONCLUSIONS

High-quality CBCT images could be obtained in a single scan after using the proposed RBB method for scatter correction, enabling more accurate image guidance for surgery and radiation therapy applications. With almost no time delay between the successive open and blocked projections, the RBB method could eliminate the motion-induced anatomical mismatches between the corresponding open and blocked projections and could find particular usefulness in thoracic and abdominal imaging.

Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

Proton spot dose estimation based on positron activity distributions with neural network

BACKGROUND

Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy.

PURPOSE

This study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U-Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice.

METHODS

Proton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one-dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics.

RESULTS

The U-Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases.

CONCLUSIONS

Both the U-Net and the Transformer have certain advantages in the proton dose estimation task. The U-Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose-guided proton therapy.

DeCoGAN: MVCT image denoising via coupled generative adversarial network

Objective.In helical tomotherapy, image-guided radiotherapy employs megavoltage computed tomography (MVCT) for precise targeting. However, the high voltage of megavoltage radiation introduces substantial noise, significantly compromising MVCT image clarity. This study aims to enhance MVCT image quality using a deep learning-based denoising method.Approach.We propose an unpaired MVCT denoising network using a coupled generative adversarial network framework (DeCoGAN). Our approach assumes that a universal latent code within a shared latent space can reconstruct any given pair of images. By employing an encoder, we enforce this shared-latent space constraint, facilitating the conversion of low-quality (noisy) MVCT images into high-quality (denoised) counterparts. The network learns the joint distribution of images from both domains by leveraging samples from their respective marginal distributions, enhanced by adversarial training for effective denoising.Main Results.Compared to an analytical algorithm (BM3D) and three deep learning-based methods (RED-CNN, WGAN-VGG and CycleGAN), the proposed method excels in preserving image details and enhancing human visual perception by removing most noise and retaining structural features. Quantitative analysis demonstrates that our method achieves the highest peak signal-to-noise ratio and Structural Similarity Index Measurement values, indicating superior denoising performance.Significance.The proposed DeCoGAN method shows remarkable MVCT denoising performance, making it a promising tool in the field of radiation therapy.

Technical note: Can photon-counting CT improve PET/CT's quantitative accuracy?

BACKGROUND

Linear attenuation coefficients (LACs) in positron emission tomography combined with computed tomography (PET/CT) are derived from CT scans that utilize energy-integrating detectors (EID-CT). These LACs are inaccurate when iodine contrast has been injected. Photon counting detector CT (PCD-CT) may be able to improve the accuracy.

PURPOSE

To investigate whether PCD-CT can improve PET/CT quantitative accuracy.

METHODS

Two experiments were performed: one with CT only and one that combined PET and CT. The first experiment used an electron density phantom whose inserts were imaged with EID-CT and PCD-CT. The inserts simulated normal human tissues, including bone and iodinated blood. In the case of PCD-CT, virtual-monoenergetic images at 190 keV were created. LACs were derived in each case and compared against known values. For inserts with iodine, more accurate LACs were expected with PCD-CT. The second experiment involved a custom PET phantom with various materials simulating human tissues (blood, iodinated blood, and bone) and 18F radioactivity. Data were first acquired with an EID-CT-based PET/CT system and then separately in a PCD-CT system without PET. PET images were reconstructed using LAC from EID-CT and PCD-CT. PET image values were compared against known activity values using recovery coefficients (RC).

RESULTS

In the first experiment, LAC based on EID-CT were in error by as much as 18%, whereas the corresponding PCD-CT based measurements were within 3%. In the second experiment, minimum, maximum, and mean RC were (96.1%, 115.4%, and 103.8%) for the EID-CT method, and (95.8%, 105.5%, and 101.0%) for the PCD-CT method. The consistency of PET images in body and head orientations was improved.

CONCLUSIONS

PCD-CT can acquire the information needed for accurate LAC for PET reconstruction in a single spiral acquisition.

Reading of gafchromic EBT-3 film using an overhead scanner

Gafchromic film, a commercially available radiochromic film, has been developed and widely used as an effective tool for radiation dose verification and quality assurance in radiotherapy. However, the orientation effect in scanning a film remains a concern for practical application in beam profile monitoring. To resolve this issue, the authors introduced a novel method using an overhead scanner (OHS) coupled with a tracing light board instead of a conventional flatbed scanner (FBS) to read Gafchromic EBT3 films. We investigated the orientation effect of the EBT3 film with a regular hexagonal shape after irradiation with 5 Gy x-rays (160 kV, 6.3 mA) and compared the digitized images acquired using a commercially available OHS (CZUR Aura) and a conventional FBS (EPSON GT-X980). As a result, RGB color intensities acquired from the OHS showed significantly lower orientation effect of the color intensities of RGB components than those from FBS. This finding indicates the high potential of the proposed method for achieving more precise two-dimensional dosimetry. Further studies are required to confirm the effectiveness of this method under different irradiation conditions over a wider dose range.

A new model of electrosurgical tissue damage for neurosurgery simulation

BACKGROUND

Bipolar hemostasis electrocoagulation is a fundamental procedure in neurosurgery. A precise electrocoagulation model is essential to enable realistic visual feedback in virtual neurosurgical simulation. However, existing models lack an accurate description of the heat damage and irreversible tissue deformation caused by electrocoagulation, thus diminishing the visual realism. This work focuses on the electrocoagulation model for neurosurgery simulation.

METHOD

In this paper, a position-based dynamics (PBD) model with a bioheat transfer and damage prediction (BHTDP) method is developed for simulating the deformation of brain tissue caused by electrocoagulation. The presented BTHDP method uses the Arrhenius equation to predict thermal damage of brain tissue. A deformation model with energy and thermal damage constraints is developed to characterize soft tissue deformation during heat absorption before and after thermal injury. Visual effect of damaged brain tissue is re-rendered.

RESULT

To evaluate the accuracy of the proposed method, numerical simulations were conducted and compared with commercial finite element software. The maximum normalized error of the proposed model for predicting midpoint temperature is 10.3 % and the maximum error for predicting the thermal damage is 5.4 %. The contraction effects of heat-exposed anisotropic tissues are also simulated. The results indicate that the presented electrocoagulation model provides stable and realistic visual effects, making it applicable for simulating the electrocoagulation process in virtual neurosurgery.

AAPM WGTG51 Report 385: Addendum to the AAPM's TG-51 protocol for clinical reference dosimetry of high-energy electron beams

An Addendum to the AAPM's TG-51 protocol for the determination of absorbed dose to water is presented for electron beams with energies between 4 MeV and 22 MeV (1.70 cm ≤ R 50 ≤ 8.70 cm $1.70\nobreakspace {\rm cm} \le R_{\text{50}} \le 8.70\nobreakspace {\rm cm}$ ). This updated formalism allows simplified calibration procedures, including the use of calibrated cylindrical ionization chambers in all electron beams without the use of a gradient correction. Newk Q $k_{Q}$ data are provided for electron beams based on Monte Carlo simulations. Implementation guidance is provided. Components of the uncertainty budget in determining absorbed dose to water at the reference depth are discussed. Specifications for a reference-class chamber in electron beams include chamber stability, settling, ion recombination behavior, and polarity dependence. Progress in electron beam reference dosimetry is reviewed. Although this report introduces some major changes (e.g., gradient corrections are implicitly included in the electron beam quality conversion factors), they serve to simplify the calibration procedure. Results for absorbed dose per linac monitor unit are expected to be up to approximately 2 % higher using this Addendum compared to using the original TG-51 protocol.

Optimizing angular range in digital breast tomosynthesis: A phantom study investigating lesion detection across varied breast density and thickness

PURPOSE

To determine the optimal angular range (AR) for digital breast tomosynthesis (DBT) systems that provides highest lesion visibility across various breast densities and thicknesses.

METHOD

A modular DBT phantom, consisting of tissue-equivalent adipose and glandular modules, along with a module embedded with test objects (speckles, masses, fibers), was used to create combinations simulating different breast thicknesses, densities, and lesion locations. A prototype DBT system operated at four ARs (AR±7.5°, AR±12.5°, AR±19°, and AR±25°) to acquire 11 projection images for each combination, with separate fixed doses for thin and thick combinations. Three blinded radiologists independently assessed lesion visibility in reconstructed images; assessments were averaged and compared using linear mixed models.

RESULTS

Speckle visibility was highest with AR±7.5° or AR±12.5°, decreasing with wider ARs in all density and thickness combinations. The difference between AR±7.5° and AR±12.5° was not statistically significant, except for the tube-side speckles in thin-fatty combinations (5.83 [AR±7.5°] vs. 5.39 [AR±12.5°], P = 0.019). Mass visibility was not affected by AR in thick combinations, while AR±12.5° exhibited the highest mass visibility for both thin-fatty and thin-dense combinations (P = 0.032 and 0.007, respectively). Different ARs provided highest fiber visibility for different combinations; however, AR±12.5° consistently provided highest or comparable visibility. AR±12.5° showed highest overall lesion visibility for all density and thickness combinations.

CONCLUSIONS

AR±12.5° exhibited the highest overall lesion visibility across various phantom thicknesses and densities using a projection number of 11.

Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis

BACKGROUND

Radiogenomics is an emerging technology that integrates genomics and medical image-based radiomics, which is considered a promising approach toward achieving precision medicine.

OBJECTIVE

The aim of this study was to quantitatively analyze the research status, dynamic trends, and evolutionary trajectory in the radiogenomics field using bibliometric methods.

METHODS

The relevant literature published up to 2023 was retrieved from the Web of Science Core Collection. Excel was used to analyze the annual publication trend. VOSviewer was used for constructing the keywords co-occurrence network and the collaboration networks among countries and institutions. CiteSpace was used for citation keywords burst analysis and visualizing the references timeline.

RESULTS

A total of 3237 papers were included and exported in plain-text format. The annual number of publications showed an increasing annual trend. China and the United States have published the most papers in this field, with the highest number of citations in the United States and the highest average number per item in the Netherlands. Keywords burst analysis revealed that several keywords, including "big data," "magnetic resonance spectroscopy," "renal cell carcinoma," "stage," and "temozolomide," experienced a citation burst in recent years. The timeline views demonstrated that the references can be categorized into 8 clusters: lower-grade glioma, lung cancer histology, lung adenocarcinoma, breast cancer, radiation-induced lung injury, epidermal growth factor receptor mutation, late radiotherapy toxicity, and artificial intelligence.

CONCLUSIONS

The field of radiogenomics is attracting increasing attention from researchers worldwide, with the United States and the Netherlands being the most influential countries. Exploration of artificial intelligence methods based on big data to predict the response of tumors to various treatment methods represents a hot spot research topic in this field at present.

Comparative transcriptomics reveal a novel tardigrade-specific DNA-binding protein induced in response to ionizing radiation

Tardigrades are microscopic animals renowned for their ability to withstand extreme conditions, including high doses of ionizing radiation (IR). To better understand their radio-resistance, we first characterized induction and repair of DNA double- and single-strand breaks after exposure to IR in the model species Hypsibius exemplaris. Importantly, we found that the rate of single-strand breaks induced was roughly equivalent to that in human cells, suggesting that DNA repair plays a predominant role in tardigrades' radio-resistance. To identify novel tardigrade-specific genes involved, we next conducted a comparative transcriptomics analysis across three different species. In all three species, many DNA repair genes were among the most strongly overexpressed genes alongside a novel tardigrade-specific gene, which we named Tardigrade DNA damage Response 1 (TDR1). We found that TDR1 protein interacts with DNA and forms aggregates at high concentration suggesting it may condensate DNA and preserve chromosome organization until DNA repair is accomplished. Remarkably, when expressed in human cells, TDR1 improved resistance to Bleomycin, a radiomimetic drug. Based on these findings, we propose that TDR1 is a novel tardigrade-specific gene conferring resistance to IR. Our study sheds light on mechanisms of DNA repair helping cope with high levels of DNA damage inflicted by IR.

Generating 3D images of VMAT plans for predictive models and activation maps associated with plan deliverability

BACKGROUND

Intensity modulation with dynamic multi-leaf collimator (MLC) and monitor unit (MU) changes across control points (CPs) characterizes volumetric modulated arc therapy (VMAT). The increased uncertainty in plan deliverability required patient-specific quality assurance (PSQA), which remained inefficient upon Quality Assurance (QA) failure. To prevent waste before QA, plan complexity metrics (PCMs) and machine learning models with the metrics were generated, which were lack of providing CP-specific information upon QA failures.

PURPOSE

By generating 3D images from digital imaging and comminications in medicine in radiation therapy (DICOM RT) plan, we proposed a predictive model that can estimate the deliverability of VMAT plans and visualize CP-specific regions associated with plan deliverability.

METHODS

The patient cohort consisted of 259 and 190 cases for left- and right-breast VMAT treatments, which were split into 235 and 166 cases for training and 24 cases from each treatment for testing the networks. Three-channel 3D images generated from DICOM RT plans were fed into a DenseNet-based deep learning network. To reflect VMAT plan complexity as an image, the first two channels described MLC and MU variations between two consecutive CPs, while the last channel assigned the beam field size. The network output was defined as binary classified PSQA results, indicating deliverability. The predictive performance was assessed by accuracy, sensitivity, specificity, F1-score, and area under the curve (AUC). The gradient-weighted class activation map (Grad-CAM) highlighted the regions of CPs in VMAT plans associated with deliverability, compared against PCMs by Spearman correlation.

RESULTS

The DenseNet-based predictive model yielded AUCs of 92.2% and 93.8%, F1-scores of 97.0% and 93.8% and accuracies of 95.8% and 91.7% for the left- and right-breast VMAT cases. Additionally, the specificity of 87.5% for both cases indicated that the predictive model accurately detected QA failing cases. The activation maps significantly differentiated QA failing-labeled from passing-labeled classes for the non-deliverable cases. The PCM with the highest correlation to the Grad-CAM varied from patient cases, implying that plan deliverability would be considered patient-specific.

CONCLUSION

This work demonstrated that the deep learning-based network based on visualization of dynamic VMAT plan information successfully predicted plan deliverability, which also provided control-point specific planning parameter information associated with plan deliverability in a patient-specific manner.

Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy

Background

Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown.

Objective

This study investigated the effect of cardiorespiratory motion on intensity-modulated proton therapy (IMPT) and the effectiveness of motion-encompassing methods.

Methods

We retrospectively included 12 patients with refractory arrhythmia who underwent CSBRT with four-dimensional computed tomography (4DCT) and 4D cardiac CT (4DcCT). Proton plans were simulated using an IBA accelerator based on the 4D average CT. The prescription was 25 Gy in a single fraction, with all plans normalized to ensure that 95% of the target volume received the prescribed dose. 4D dose reconstruction was performed to generate 4D accumulated and dynamic doses. Furthermore, dose uncertainties due to the interplay effect of the substrate target and organs at risk (OARs) were assessed. The differences between internal organs at risk volume (IRV) and OARreal (manually contoured on average CT) were compared. In 4D dynamic dose, meeting prescription requirements entails V25 and D95 reaching 95% and 25 Gy, respectively.

Results

The 4D dynamic dose significantly differed from the 3D static dose. The mean V25 and D95 were 89.23% and 24.69 Gy, respectively, in 4DCT and 94.35% and 24.99 Gy, respectively, in 4DcCT. Eleven patients in 4DCT and six in 4DcCT failed to meet the prescription requirements. Critical organs showed varying dose increases. All metrics, except for Dmean and D50, significantly changed in 4DCT; in 4DcCT, only D50 remained unchanged with regards to the target dose uncertainties induced by the interplay effect. The interplay effect was only significant for the Dmax values of several OARs. Generally, respiratory motion caused a more pronounced interplay effect than cardiac pulsation. Neither IRV nor OARreal effectively evaluated the dose discrepancies of the OARs.

Conclusions

Complex cardiorespiratory motion can introduce dose uncertainties during IMPT. Motion-encompassing techniques may mitigate but cannot entirely compensate for the dose discrepancies. Individualized 4D dose assessments are recommended to verify the effectiveness and safety of CSBRT.

Effect of different optimization parameters in single isocenter multiple brain metastases radiosurgery

PURPOSE

Automated treatment planning for multiple brain metastases differs from traditional planning approaches. It is therefore helpful to understand which parameters for optimization are available and how they affect the plan quality. This study aims to provide a reference for designing multi-metastases treatment plans and to define quality endpoints for benchmarking the technique from a scientific perspective.

METHODS

In all, 20 patients with a total of 183 lesions were retrospectively planned according to four optimization scenarios. Plan quality was evaluated using common plan quality parameters such as conformity index, gradient index and dose to normal tissue. Therefore, different scenarios with combinations of optimization parameters were evaluated, while taking into account dependence on the number of treated lesions as well as influence of different beams.

RESULTS

Different scenarios resulted in minor differences in plan quality. With increasing number of lesions, the number of monitor units increased, so did the dose to healthy tissue and the number of interlesional dose bridging in adjacent metastases. Highly modulated cases resulted in 4-10% higher V10% compared to less complex cases, while monitor units did not increase. Changing the energy to a flattening filter free (FFF) beam resulted in lower local V12Gy (whole brain-PTV) and even though the number of monitor units increased by 13-15%, on average 46% shorter treatment times were achieved.

CONCLUSION

Although no clinically relevant differences in parameters where found, we identified some variation in the dose distributions of the different scenarios. Less complex scenarios generated visually more dose overlap; therefore, a more complex scenario may be preferred although differences in the quality metrics appear minor.

Improvement of accumulated dose distribution in combined cervical cancer radiotherapy with deep learning-based dose prediction

Purpose

Difficulties remain in dose optimization and evaluation of cervical cancer radiotherapy that combines external beam radiotherapy (EBRT) and brachytherapy (BT). This study estimates and improves the accumulated dose distribution of EBRT and BT with deep learning-based dose prediction.

Materials and methods

A total of 30 patients treated with combined cervical cancer radiotherapy were enrolled in this study. The dose distributions of EBRT and BT plans were accumulated using commercial deformable image registration. A ResNet-101-based deep learning model was trained to predict pixel-wise dose distributions. To test the role of the predicted accumulated dose in clinic, each EBRT plan was designed using conventional method and then redesigned referencing the predicted accumulated dose distribution. Bladder and rectum dosimetric parameters and normal tissue complication probability (NTCP) values were calculated and compared between the conventional and redesigned accumulated doses.

Results

The redesigned accumulated doses showed a decrease in mean values of V50, V60, and D2cc for the bladder (-3.02%, -1.71%, and -1.19 Gy, respectively) and rectum (-4.82%, -1.97%, and -4.13 Gy, respectively). The mean NTCP values for the bladder and rectum were also decreased by 0.02‰ and 0.98%, respectively. All values had statistically significant differences (p < 0.01), except for the bladder D2cc (p = 0.112).

Conclusion

This study realized accumulated dose prediction for combined cervical cancer radiotherapy without knowing the BT dose. The predicted dose served as a reference for EBRT treatment planning, leading to a superior accumulated dose distribution and lower NTCP values.

"dsbandrepair" - An updated Geant4-DNA simulation tool for evaluating the radiation-induced DNA damage and its repair

PURPOSE

Interdisciplinary scientific communities have shown large interest to achieve a mechanistic description of radiation-induced biological damage, aiming to predict biological results produced by different radiation quality exposures. Monte Carlo track-structure simulations are suitable and reliable for the study of early DNA damage induction used as input for assessing DNA damage. This study presents the most recent improvements of a Geant4-DNA simulation tool named "dsbandrepair".

METHODS

"dsbandrepair" is a Monte Carlo simulation tool based on a previous code (FullSim) that estimates the induction of early DNA single-strand breaks (SSBs) and double-strand breaks (DSBs). It uses DNA geometries generated by the DNAFabric computational tool for simulating the induction of early single-strand breaks (SSBs) and double-strand breaks (DSBs). Moreover, the new tool includes some published radiobiological models for survival fraction and un-rejoined DSB. Its application for a human fibroblast cell and human umbilical vein endothelial cell containing both heterochromatin and euchromatin was conducted. In addition, this new version offers the possibility of using the new IRT-syn method for computing the chemical stage.

RESULTS

The direct and indirect strand breaks, SSBs, DSBs, and damage complexity obtained in this work are equivalent to those obtained with the previously published simulation tool when using the same configuration in the physical and chemical stages. Simulation results on survival fraction and un-rejoined DSB are in reasonable agreement with experimental data.

CONCLUSIONS

"dsbandrepair" is a tool for simulating DNA damage and repair, benchmarked against experimental data. It has been released as an advanced example in Geant4.11.2.

Urinary organs-at-risk for prostate cancer external beam radiotherapy: contouring guidelines on behalf of the Francophone Group of Urological Radiation Therapy (GFRU)

PURPOSE

Occurrence of genitourinary (GU) toxicity is a common adverse event observed after external beam radiotherapy (EBRT) for prostate cancer (PCa). Recent findings suggest that the dose delivered to specific urinary organs-at-risk (OARs) such as ureters, bladder trigone, and urethra is involved in the development of GU toxicity.

METHODS AND MATERIALS

A multidisciplinary task force including three radiation oncologists, a uroradiologist, and a urologist was created in 2022. First, OARs potentially involved in GU toxicity were identified and discussed. A literature review was performed, addressing several questions relative to urinary OARs: anatomical and radiological definition, radiation-induced injury, dose-volume parameters. Secondly, results were presented and discussed with a panel of radiation oncologists, members of the "Francophone Group of Urological Radiation Therapy" (GFRU). Thereafter, GFRU experts were asked to answer a dedicated questionnaire, including 35 questions on the controversial issues related to the delineation of urinary OARs.

RESULTS

The following structures were identified as critical for PCa EBRT: ureters, bladder, bladder neck, bladder trigone, urethra (intraprostatic, membranous, spongious), striated sphincter, and post-enucleation or post-transurethral resection of the prostate (TURP) cavity. A consensus was obtained for 32 out of 35 items.

CONCLUSION

This consensus highlights contemporary urinary structures in both upper and lower urinary tract to be considered for EBRT treatment planning of PCa. The current recommendations also propose a standardized definition of urinary OARs, for both daily practice and future clinical trials.