ACR-ASTRO Practice Parameter for Image-guided Radiation Therapy (IGRT)

Towards equitable AI in oncology

Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with considerable potential to improve early cancer detection and risk assessment, and to enable more accurate personalized treatment recommendations. However, a notable imbalance exists in the distribution of the benefits of AI, which disproportionately favour those living in specific geographical locations and in specific populations. In this Perspective, we discuss the need to foster the development of equitable AI tools that are both accurate in and accessible to a diverse range of patient populations, including those in low-income to middle-income countries. We also discuss some of the challenges and potential solutions in attaining equitable AI, including addressing the historically limited representation of diverse populations in existing clinical datasets and the use of inadequate clinical validation methods. Additionally, we focus on extant sources of inequity including the type of model approach (such as deep learning, and feature engineering-based methods), the implications of dataset curation strategies, the need for rigorous validation across a variety of populations and settings, and the risk of introducing contextual bias that comes with developing tools predominantly in high-income countries.

A review on advancements in the application of starch-based nanomaterials in biomedicine: Precision drug delivery and cancer therapy

The burgeoning field of starch-based nanomaterials in biomedical applications has perceived notable progressions, with a particular emphasis on their pivotal role in precision drug delivery and the inhibition of tumor growth. The complicated challenges in current biomedical research require innovative approaches for improved therapeutic outcomes, prompting an exploration into the possible of starch-based nanomaterials. The conceptualization of this review emerged from recognizing the need for a comprehensive examination of the structural attributes, versatile properties, and mechanisms underlying the efficiency of starch-based nanomaterials in inhibiting tumor growth and enabling targeted drug delivery. This review delineates the substantial growth in utilizing starch-based nanomaterials, elucidating their small size, high surface-volume ratio, and biocompatibility, predominantly emphasizing their possible to actively recognize cancer cells, deliver anticancer drugs, and combat tumors efficiently. The investigation of these nanomaterials encompasses to improving biocompatibility and targeting specific tissues, thereby contributing to the evolving landscape of precision medicine. The review accomplishes by highlighting the auspicious strategies and modern developments in the field, envisioning a future where starch-based nanomaterials play a transformative role in molecular nanomaterials, evolving biomedical sciences. The translation of these advancements into clinical applications holds the potential to revolutionize targeted drug delivery and expand therapeutic outcomes in the realm of precision medicine.

Results of an Artificial Intelligence-Based Image Review System to Detect Patient Misalignment Errors in a Multi-institutional Database of Cone Beam Computed Tomography-Guided Radiation Therapy

PURPOSE

Present knowledge of patient setup and alignment errors in image guided radiation therapy (IGRT) relies on voluntary reporting, which is thought to underestimate error frequencies. A manual retrospective patient-setup misalignment error search is infeasible owing to the bulk of cases to be reviewed. We applied a deep learning-based misalignment error detection algorithm (EDA) to perform a fully automated retrospective error search of clinical IGRT databases and determine an absolute gross patient misalignment error rate.

METHODS AND MATERIALS

The EDA was developed to analyze the registration between planning scans and pretreatment cone beam computed tomography scans, outputting a misalignment score ranging from 0 (most unlikely) to 1 (most likely). The algorithm was trained using simulated translational errors on a data set obtained from 680 patients treated at 2 radiation therapy clinics between 2017 and 2022. A receiver operating characteristic analysis was performed to obtain target thresholds. DICOM Query and Retrieval software was integrated with the EDA to interact with the clinical database and fully automate data retrieval and analysis during a retrospective error search from 2016 to 2017 and from 2021 to 2022 for the 2 institutions, respectively. Registrations were flagged for human review using both a hard-thresholding method and a prediction trending analysis over each individual patient's treatment course. Flagged registrations were manually reviewed and categorized as errors (>1 cm misalignment at the target) or nonerrors.

RESULTS

A total of 17,612 registrations were analyzed by the EDA, resulting in 7.7% flagged events. Three previously reported errors were successfully flagged by the EDA, and 4 previously unreported vertebral body misalignment errors were discovered during case reviews. False positive cases often displayed substantial image artifacts, patient rotation, and soft tissue anatomy changes.

CONCLUSIONS

Our results validated the clinical utility of the EDA for bulk image reviews and highlighted the reliability and safety of IGRT, with an absolute gross patient misalignment error rate of 0.04% ± 0.02% per delivered fraction.

Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO)

INTRODUCTION

The advent of image-guided radiation therapy (IGRT) has recently changed the workflow of radiation treatments by ensuring highly collimated treatments. Artificial intelligence (AI) and radiomics are tools that have shown promising results for diagnosis, treatment optimization and outcome prediction. This review aims to assess the impact of AI and radiomics on modern IGRT modalities in RT.

METHODS

A PubMed/MEDLINE and Embase systematic review was conducted to investigate the impact of radiomics and AI to modern IGRT modalities. The search strategy was "Radiomics" AND "Cone Beam Computed Tomography"; "Radiomics" AND "Magnetic Resonance guided Radiotherapy"; "Radiomics" AND "on board Magnetic Resonance Radiotherapy"; "Artificial Intelligence" AND "Cone Beam Computed Tomography"; "Artificial Intelligence" AND "Magnetic Resonance guided Radiotherapy"; "Artificial Intelligence" AND "on board Magnetic Resonance Radiotherapy" and only original articles up to 01.11.2022 were considered.

RESULTS

A total of 402 studies were obtained using the previously mentioned search strategy on PubMed and Embase. The analysis was performed on a total of 84 papers obtained following the complete selection process. Radiomics application to IGRT was analyzed in 23 papers, while a total 61 papers were focused on the impact of AI on IGRT techniques.

DISCUSSION

AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.

Automated review of patient position in DIBH breast hybrid IMRT with EPID images

Deep Inspiration Breath Hold (DIBH) is a respiratory-gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In this retrospective study, we developed a system capable of monitoring DIBH breast treatments by utilizing cine EPID images taken during treatment. Setup error and intrafraction motion were measured for all fractions of 20 left-sided breast patients. All patients were treated with a hybrid static-IMRT technique, with EPID images from the static fields analyzed. Ten patients had open static fields and the other ten patients had static fields partially blocked with the multileaf collimator (MLC). Three image-processing algorithms were evaluated on their ability to accurately measure the chest wall position (CWP) in EPID images. CWP measurements were recorded along a 61-pixel region of interest centered along the midline of the image. The median and standard deviation of the CWP were recorded for each image. The algorithm showing the highest agreement with manual measurements was then used to calculate intrafraction motion and setup error. To measure intrafraction motion, the median CWP of the first EPID frame was compared with that of the subsequent EPID images of the treatment. The maximum difference was recorded as the intrafraction motion. The setup error was calculated as the difference in median CWP between the MV DRR and the first EPID image of the lateral tangential field. The results showed that the most accurate image-processing algorithm can identify the chest wall within 1.2 mm on both EPID and MV DRR images, and measures intrafraction motion and setup errors within 1.4 mm.

Image-guided radiation therapy (IGRT) in prostate cancer in México, survey of SOMERA (Sociedad Mexicana de Radioterapeutas/Mexican Society of Radiation Oncologists) with recommendations on its implementation and process

Background

Prostate cancer is one of the main tumors worldwide, its treatment is multidisciplinary, includes radiotherapy in all stages: curative, radical, adjuvant, salvage and palliative. Technological advances in planning systems, image acquisition and treatment equipment have allowed the delivery of higher doses limiting toxicity in healthy tissues, distributing radiation optimally and ensuring reproducibility of conditions. Image-guided radiotherapy (IGRT) is not standard in guidelines, only recommended with heterogeneity in its own process.

Materials and methods

A survey was conducted to members of the Mexican Society of Radiation Oncologists (SOMERA), to know the current status and make recommendations about its implementation and use, taking into account existing resources.

Results

Responses of 541 patients were evaluated, 85% belonged to the intermediate-high risk group, 65% received adjuvant or salvage radiotherapy (RT), 80% received intensity-modulated radiation therapy (IMRT) using doses up to 80 Gy/2 Gy. Cone beam computed tomography (CBCT) was performed on 506 (93.5%), (100% IMRT) and 90% at a periodicity of 3-5/week. 3D treatment with 42% portal images 1/week. Online correction strategies (36% changes before treatment), following a diet and bladder and rectal control. Evidence and recommendations are reviewed.

Conclusions

IGRT should be performed in patients with prostate cancer. In Mexico, despite limitations in the distribution of human and technological resources, it is routinely applied. More information is still needed on clinical evidence of its benefits and the process should be implemented according to infrastructure, following institutional guidelines, recommending to report the initial experience that helps to standardize national conduct.

Safety in radiation oncology (SAFRON): Learning about incident causes and safety barriers in external beam radiotherapy

PURPOSE

Safety in Radiation Oncology (SAFRON) is a reporting and learning system on radiotherapy and radionuclide therapy incidents and near misses. The primary aim of this paper is to examine whether any discernible patterns exist in the causes of reported incidents and safety barriers within the SAFRON system concerning external beam radiotherapy.

METHODS AND MATERIALS

This study focuses on external beam radiotherapy incidents, reviewing 1685 reports since the inception of SAFRON until December 2021. Reports that did not identify causes of incidents and safety barriers were excluded from the final study population.

RESULTS

Simple two-dimensional radiotherapy or electron beam therapy were represented by 97 reports, three-dimensional conformal radiotherapy by 39 reports, modulated arc therapy by 12 reports, intensity modulated radiation therapy by 11 reports, stereotactic radiosurgery by 4 reports, and radiotherapy with protons or other particles by 1 report, while for 92 of them, no information on treatment method had been provided. Most of the reported incidents were minor incidents and were discovered by the radiation therapist. Inadequate direction/information in staff communication was the most frequently reported cause of incident, and regular independent chart check was the most common safety barrier.

CONCLUSIONS

The results indicate that the majority of incidents were reported by radiation therapists, and the majority of these incidents were classified as minor. Communication problems and failure to follow standards/procedures/practices were the most frequent causes of incidents. Furthermore, regular independent chart checking was the most frequently identified safety barrier.

Quality and Safety Considerations in Image Guided Radiation Therapy: An ASTRO Safety White Paper Update

PURPOSE

This updated report on image guided radiation therapy (IGRT) is part of a series of consensus-based white papers previously published by the American Society for Radiation Oncology addressing patient safety. Since the first white papers were published, IGRT technology and procedures have progressed significantly such that these procedures are now more commonly used. The use of IGRT has now extended beyond high-precision treatments, such as stereotactic radiosurgery and stereotactic body radiation therapy, and into routine clinical practice for many treatment techniques and anatomic sites. Therefore, quality and patient safety considerations for these techniques remain an important area of focus.

METHODS AND MATERIALS

The American Society for Radiation Oncology convened an interdisciplinary task force to assess the original IGRT white paper and update content where appropriate. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters who selected "strongly agree" or "agree" indicated consensus.

SUMMARY

This IGRT white paper builds on the previous version and uses other guidance documents to primarily focus on processes related to quality and safety. IGRT requires an interdisciplinary team-based approach, staffed by appropriately trained specialists, as well as significant personnel resources, specialized technology, and implementation time. A thorough feasibility analysis of resources is required to achieve the clinical and technical goals and should be discussed with all personnel before undertaking new imaging techniques. A comprehensive quality-assurance program must be developed, using established guidance, to ensure IGRT is performed in a safe and effective manner. As IGRT technologies continue to improve or emerge, existing practice guidelines should be reviewed or updated regularly according to the latest American Association of Physicists in Medicine Task Group reports or guidelines. Patient safety in the application of IGRT is everyone's responsibility, and professional organizations, regulators, vendors, and end-users must demonstrate a clear commitment to working together to ensure the highest levels of safety.

As Easy as 1, 2, 3? How to Determine CBCT Frequency in Adjuvant Breast Radiotherapy

The current study aims to assess the suitability of setup errors during the first three treatment fractions to determine cone-beam computed tomography (CBCT) frequency in adjuvant breast radiotherapy. For this, 45 breast cancer patients receiving non-hypofractionated radiotherapy after lumpectomy, including a simultaneous integrated boost (SIB) to the tumor bed and daily CBCT imaging, were retrospectively selected. In a first step, mean and maximum setup errors on treatment days 1–3 were correlated with the mean setup errors during subsequent treatment days. In a second step, dose distribution was estimated using a dose accumulation workflow based on deformable image registration, and setup errors on treatment days 1–3 were correlated with dose deviations in the clinical target volumes (CTV) and organs at risk (OAR). No significant correlation was found between mean and maximum setup errors on treatment days 1–3 and mean setup errors during subsequent treatment days. In addition, mean and maximum setup errors on treatment days 1–3 correlated poorly with dose coverage of the CTVs and dose to the OARs. Thus, CBCT frequency in adjuvant breast radiotherapy should not be determined solely based on the magnitude of setup errors during the first three treatment fractions.

Special stereotactic radiotherapy techniques: procedures and equipment for treatment simulation and dose delivery

Stereotactic radiotherapy (SRT ) is a multi-step procedure with each step requiring extreme accuracy. Physician-dependent accuracy includes appropriate disease staging, multi-disciplinary discussion with shared decision-making, choice of morphological and functional imaging methods to identify and delineate the tumor target and organs at risk, an image-guided patient set-up, active or passive management of intra-fraction movement, clinical and instrumental follow-up. Medical physicist-dependent accuracy includes use of advanced software for treatment planning and more advanced Quality Assurance procedures than required for conventional radiotherapy. Consequently, all the professionals require appropriate training in skills for high-quality SRT.

Thanks to the technological advances, SRT has moved from a “frame-based” technique, i.e. the use of stereotactic coordinates which are identified by means of rigid localization frames, to the modern “frame-less” SRT which localizes the target volume directly, or by means of anatomical surrogates or fiducial markers that have previously been placed within or near the target. This review describes all the SRT steps in depth, from target simulation and delineation procedures to treatment delivery and image-guided radiation therapy. Target movement assessment and management are also described.

Stereotactic radiotherapy for lung oligometastases

30–60% of cancer patients develop lung metastases, mostly from primary tumors in the colon-rectum, lung, head and neck area, breast and kidney. Nowadays, stereotactic radiotherapy (SRT ) is considered the ideal modality for treating pulmonary metastases.

When lung metastases are suspected, complete disease staging includes a total body computed tomography (CT ) and/or positron emission tomography-computed tomography (PET -CT ) scan. PET -CT has higher specificity and sensitivity than a CT scan when investigating mediastinal lymph nodes, diagnosing a solitary lung lesion and detecting distant metastases. For treatment planning, a multi-detector planning CT scan of the entire chest is usually performed, with or without intravenous contrast media or esophageal lumen opacification, especially when central lesions have to be irradiated. Respiratory management is recommended in lung SRT, taking the breath cycle into account in planning and delivery. For contouring, co-registration and/or matching planning CT and diagnostic images (as provided by contrast enhanced CT or PET-CT ) are useful, particularly for central tumors. Doses and fractionation schedules are heterogeneous, ranging from 33 to 60 Gy in 3–6 fractions. Independently of fractionation schedule, a BED₁₀ > 100 Gy is recommended for high local control rates. Single fraction SRT (ranges 15–30 Gy) is occasionally administered, particularly for small lesions. SRT provides tumor control rates of up to 91% at 3 years, with limited toxicities.

The present overview focuses on technical and clinical aspects related to treatment planning, dose constraints, outcome and toxicity of SRT for lung metastases.

PCXMC cone beam computed tomography dosimetry investigations

With cone beam computed tomography (CBCT) in image guided radiation therapy being amongst the most widely used imaging modalities, there has been an increasing interest in quantifying the concomitant dose and risk. Whilst there have been several studies on this topic, there remains a lack of standardisation and knowledge on dose variations and the impact of patient size. Recently, PCXMC (a Monte Carlo simulator) has been used to assess both the concomitant dose and dosimetric impact of patient size variations for CBCT. The scopes of these studies, however, have included only a limited range of imaging manufacturers, protocols, and patient sizes. An approach using PCXMC and MATLAB was developed to enable a generalised method for rapidly quantifying and formulating the concomitant dose as a function of patient size across numerous CBCT vendors and protocols. The method was investigated using the Varian on board imaging 1.6 default pelvis and pelvis spotlight protocols, for 94 adult and paediatric phantoms over 6 age groups with extensive height and mass variations. It was found that dose varies significantly with patient size, as much as doubling and halving the average for patients of lower and higher mass, respectively. These variations, however, can be formulated and accounted for using the method developed, across a wide range of patient sizes for all CBCT vendors and protocols. This will enable the development of a comprehensive catalogue to account for concomitant doses in almost any clinically relevant scenario.

Impact of CBCT frequency on target coverage and dose to the organs at risk in adjuvant breast cancer radiotherapy

The current study aims to assess the effect of cone beam computed tomography (CBCT) frequency during adjuvant breast cancer radiotherapy with simultaneous integrated boost (SIB) on target volume coverage and dose to the organs at risk (OAR). 50 breast cancer patients receiving either non-hypofractionated or hypofractionated radiotherapy after lumpectomy including a SIB to the tumor bed were selected for this study. All patients were treated in volumetric modulated arc therapy (VMAT) technique and underwent daily CBCT imaging. In order to estimate the delivered dose during the treatment, the applied fraction doses were recalculated on daily CBCT scans and accumulated using deformable image registration. Based on a total of 2440 dose recalculations, dose coverage in the clinical target volumes (CTV) and OAR was compared depending on the CBCT frequency. The estimated delivered dose (V95%) for breast-CTV and SIB-CTV was significantly lower than the planned dose distribution, irrespective of the CBCT-frequency. Between daily CBCT and CBCT on alternate days, no significant dose differences were found regarding V95% for both, breast-CTV and SIB-CTV. Dose distribution in the OAR was similar for both imaging protocols. Weekly CBCT though led to a significant decrease in dose coverage compared to daily CBCT and a small but significant dose increase in most OAR. Daily CBCT imaging might not be necessary to ensure adequate dose coverage in the target volumes while efficiently sparing the OAR during adjuvant breast cancer radiotherapy with SIB.

Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods

Radiomics converts medical images into mineable data via a high-throughput extraction of quantitative features used for clinical decision support. However, these radiomic features are susceptible to variation across scanners, acquisition protocols, and reconstruction settings. Various investigations have assessed the reproducibility and validation of radiomic features across these discrepancies. In this narrative review, we combine systematic keyword searches with prior domain knowledge to discuss various harmonization solutions to make the radiomic features more reproducible across various scanners and protocol settings. Different harmonization solutions are discussed and divided into two main categories: image domain and feature domain. The image domain category comprises methods such as the standardization of image acquisition, post-processing of raw sensor-level image data, data augmentation techniques, and style transfer. The feature domain category consists of methods such as the identification of reproducible features and normalization techniques such as statistical normalization, intensity harmonization, ComBat and its derivatives, and normalization using deep learning. We also reflect upon the importance of deep learning solutions for addressing variability across multi-centric radiomic studies especially using generative adversarial networks (GANs), neural style transfer (NST) techniques, or a combination of both. We cover a broader range of methods especially GANs and NST methods in more detail than previous reviews.

Target coverage of daily cone-beam computed tomography in breath-hold image-guided radiotherapy for gastric lymphoma

Objectives

We evaluated retrospectively the daily target coverage using cone-beam computed tomography (CBCT) in breath-hold image-guided radiotherapy (BH-IGRT) for gastric lymphoma.

Methods

BH-IGRT was performed using a prescribed dose of 30.6 Gy in 17 fractions for the whole stomach. We assessed the target coverage of the whole stomach on daily CBCT images [daily clinical target volume (CTV)], which was delineated individually by two observers. We evaluated V_95% (percentage of volume receiving ≥95% of the prescribed dose) of daily CTV.

Results

In total, 102 fractions from 6 patients were assessed. The mean V_95% of daily CTV was 97.2%, which was over 95%. In two of six patients, the V_95% of daily CTV was over 95% for either observer in all fractions. One patient had significant interobserver variation (p = 0.013). In 95 fractions (93%), the V_95% of daily CTV was over 95% for either observer.

Conclusion

Daily target coverage for CTV in BH-IGRT for gastric lymphoma seems to be favorable, even when using CBCT.

Advances in knowledge

A previous study ascertained good daily target coverage in BH-IGRT for gastric lymphoma using in-room CT. Even when using CBCT in our study, daily target coverage for CTV in BH-IGRT for gastric lymphoma seems to be favorable.