Journal of Applied Clinical Medical Physics最新文献

Purpose: This study quantified inter- and intra-fractional setup accuracies in the upright posture and compared them among setups with different immobilization methods.

Methods: Two and four setups were examined for abdominal and head and neck (HN) cancer treatments, respectively. Fifteen asymptomatic volunteers were positioned to a replicated chair of an upright radiotherapy platform with leg immobilization devices, backrest attachments, thermoplastic masks, and vacuum cushions. The 3D positions of the subject body and masks were monitored by calculating 3D point clouds of 26 surface markers from three camera images. The inter-fractional setup errors were calculated by repeating the same setup five times. The intra-fractional displacements were evaluated while the subjects remained in the setups for 20 min. These setup errors and displacements were compared among the setups with different immobilization methods. The intra-fractional displacements were also compared between this study and previous studies in the supine posture.

Results: Inter-fractional setup errors in the abdominal setups were reduced from 6.6 ± 3.3 to 3.9 ± 1.7 mm by using the masks. The HN setup using both the leg immobilization devices and backrest attachments had the setup errors of 2.9 ± 1.7 mm. This was smaller than the setup errors observed in three other HN setups that did not use either or both of the devices together. Intra-fractional displacements of these abdominal and HN setups with the immobilization devices were 1.9 ± 1.1 and 1.8 ± 1.5 mm, respectively, which were smaller than those in the other setups. These displacements were equivalent to those in the previous studies.

Conclusions: Utilizing the masks increased upright setup accuracy in the abdominal setup. The leg immobilization devices and backrest attachments provided the highest setup accuracy in the upright HN setup. These findings will be useful to expand the applicability of upright radiotherapy for various cancer treatments.

Background: With improving survival for patients receiving whole-brain radiotherapy (WBRT), mitigating long-term toxicities like cataract and dry eye syndrome has become increasingly critical. The lens and lacrimal gland are highly radiosensitive and lie in close proximity to the target volume, posing a persistent challenge for achieving sharp dose gradients. While modern techniques like multileaf collimator (MLC) shaping offer some protection, the potential of classic geometric optimization principles, such as anterior beam shift, remains underexplored in contemporary treatment planning workflows.

Purpose: This study aimed to systematically translate, quantitatively validate, and integrate the classic geometric principle of anterior isocenter shift into the modern treatment planning workflow for the dual protection of the lens and lacrimal gland in WBRT, utilizing 3D-conformal radiotherapy (3D-CRT) and field-in-field (FIF) techniques.

Methods: For 40 patients, conventional and isocenter-optimized plans (involving an anterior shift of the isocenter within the PTV) were generated for both 3D-CRT and FIF. We compared dosimetric parameters for the planning target volume (PTV), lenses, lacrimal glands, and other organs at risk. Plan quality, normal tissue complication probability (NTCP) for cataract and dry eye syndrome, and clinical risk stratification were evaluated RESULTS: Isocenter optimization significantly reduced the median lens Dmax by 20% and PRV_lens D0.03 cm3 by 23% (p < 0.001). Lacrimal gland Dmean, V6Gy, and V10Gy were also significantly reduced. The strategy physically improved the dose gradient, narrowing the penumbra width by 31.25% and increasing the dose fall-off rate by 15%, while reducing low-dose irradiation volumes outside the PTV. These dosimetric benefits translated into meaningful reductions in projected NTCP for both complications. The 3D-FIF plans maintained target coverage and homogeneity, mitigating the heterogeneity increase observed in 3D-CRT plans.

Conclusion: Anterior isocenter optimization is a practical, and hardware-free technique that seamlessly synergizes with modern MLC-based planning to provide significant, concurrent sparing of the lens and lacrimal gland in WBRT. As a readily implementable modification within existing planning systems, this strategy can be adopted immediately to enhance treatment safety without requiring additional resources.

Purpose: Medical physicists are essential healthcare professionals who bridge the gap between technology and patient care, particularly in radiation oncology and medical imaging. With the profession expanding its clinical and global roles, the need for competencies beyond technical expertise-such as communication, leadership, and cultural awareness-is increasingly evident. These competencies, commonly referred to as soft skills, are critical for patient-centered care but remain insufficiently integrated into formal education and training pathways. The aim of the present work was to identify soft skills relevant to medical physics practice and investigate where in a career they are acquired and used.

Methods: This paper presents the views of a group of medical physicists affiliated with leading organizations in medical physics education and professional development. The group conducted a comprehensive analysis of the role and relevance of soft skills in clinical practice, academic settings, and international training programs. Their discussions led to the identification, classification, and mapping of essential soft skills across different career stages and professional roles within the field. The findings aim to inform curriculum development, professional standards, and capacity-building initiatives in medical physics worldwide.

Results: A framework of core soft skills was developed and categorized into seven domains: professionalism, leadership, cultural/political awareness, communication, adaptability, emotional intelligence, and ethical reasoning. These skills were mapped to various career stages of medical physicists, from university coursework to clinical practice and international expert missions. The analysis demonstrated that soft skills are dynamic, teachable, and essential across academic, clinical, and global contexts. The study also reviewed current gaps and opportunities in integrating soft skills into medical physics curricula, clinical residency programs, and continuing professional development.

Conclusion: To meet the evolving demands of healthcare, soft skills may need to be embedded in the education, training, and professional development of medical physicists. These skills enhance interdisciplinary collaboration, patient engagement, and leadership capacity, positioning medical physicists as integral members of the healthcare team. Academic institutions, professional societies, and global organizations are encouraged to work together to define, teach, and assess these competencies in ways that are practical and culturally adaptable.

Background: In proton beam therapy (PBT), the analytical pencil beam (PB) algorithm involves dose uncertainties in inhomogeneous regions, making accurate Monte Carlo (MC) dose calculation desirable but time-consuming. Deep learning, converting the dose calculated by the PB algorithm into an MC-equivalent dose distribution, can resolve the trade-off between calculation accuracy and speed. Training a DL-based dose conversion model that can be applied to any tumor site would be ideal; however, the appropriate training regions and its generalizability remain unclear.

Purpose: We developed a DL-based dose conversion model trained on four representative tumor sites (i.e., head and neck, lung, liver, and prostate), and evaluated its generalizability.

Methods: Data from 339 patients (a total of 1147 beams) were used. PB doses were obtained from the treatment planning system, and MC doses were calculated using an in-house MC platform. Our developed DL-based dose conversion model was designed to input a treatment planning computed tomography image and PB dose in a single field and output an MC-equivalent dose. The model's generalizability was evaluated on untrained tumor sites, including the esophagus, pancreas, colorectum, brain, breast, cervix, and limb bone and soft tissue. The conversion performance was assessed using 3D γ-analysis and the Dice similarity coefficient (DSC) for isodose volumes.

Results: For most untrained tumor sites, the model achieved average γ-passing rates of ≥90% with a criterion of 3%/2 mm. The esophagus, breast, which are close to the lung, and limb bone and soft tissue showed slightly lower passing rates of 91.3%, 85.9%, and 89.1%, respectively. The average DSC values exceeded 0.8 for most untrained tumor sites.

Conclusion: The proposed DL-based dose conversion model demonstrated high accuracy and generalizability, even for untrained tumor sites. These findings suggest that the model can be adapted to biases in collecting disease data at each PBT center and for rare diseases.

Background: Magnetic resonance-guided radiation therapy (MRgRT) using the Elekta Unity MR-linac offers significant advantages for liver stereotactic body radiation therapy (SBRT). However, the Unity is limited by a low dose rate and the lack of volumetric-modulated arc therapy (VMAT), resulting in prolonged treatment times. Reducing monitor units per fraction (MU/Fx) by optimizing Monaco sequencing parameters may improve treatment efficiency.

Purpose: To evaluate the impact of Monaco sequencing parameters on MU/Fx, plan quality, and optimization time for Unity liver SBRT.

Methods: Ten liver SBRT patients previously treated on the Unity were replanned. For each patient, 33 plans were generated by varying one of five sequencing parameters: maximum number of segments per plan, minimum MU per segment, minimum segment width (MSW), minimum segment area (MSA), and fluence smoothing (FS). The MU/Fx, optimization time, and estimated delivery time were recorded for each plan. Dosimetric and hotspot constraint compliance and the RTOG 0915 conformality index (CI) and gradient index (RI) were used to assess plan quality.

Results: Reducing the maximum number of segments to no fewer than 30 and increasing the MSA produced the largest reductions in MU/Fx (3.4%-50.8% and 3.7%-43.2%, respectively) for all patients' clinically acceptable plans. Using a high FS yielded modest MU/Fx reductions (3.0%-17.6%) in eight patients. Minimum MU per segment and MSW showed negligible effects on MU/Fx among clinically acceptable plans. MSWs of 1.5 cm or greater resulted in degraded plan quality or clinically unacceptable plans. For the five patients with the largest planning target volumes (PTVs), optimization time decreased with fewer segments (1.1%-416%) and with increased MSA (22.5%-48.1%). Across all patients, optimization time decreased with increasing minimum MU per segment (3.0%-47.2%). Estimated delivery time strongly correlated with MU/Fx (R² = 0.8278).

Conclusions: Adjusting Monaco sequencing parameters-particularly lowering the maximum number of segments, increasing the MSA, or using a high FS-can reduce MU/Fx and treatment time while maintaining acceptable plan quality on a patient-specific basis.

Background and purpose: Manual planning in breast cancer radiotherapy is often time-consuming and operator-dependent, leading to inconsistencies in plan quality. This study validated an automated workflow using overlap volume histograms (OVH) to predict patient-specific dose-volume histogram (DVH) constraints, aiming to enhance cardiopulmonary sparing and planning efficiency.

Materials and methods: A historical database of 322 patients was stratified into four groups: left/right post-mastectomy radiotherapy (PMRMRT) and left/right breast-conserving radiotherapy (BCRT). Linear regression models were established to correlate OVH-derived geometric metrics (L_x) with corresponding DVH-based dose constraints (D_x). These predictive models were integrated into the Monaco treatment planning system via a custom Python script to provide an improved automated planning workflow. The workflow's performance was prospectively validated on 80 independent testing cases (20 per group). Automated plans were generated using the predicted constraints and compared dosimetrically against clinically approved manual plans.

Results: Significant linear correlations were observed between L_x and D_x for all OARs (r² = 0.51-0.72, p < 0.001). In the PMRMRT testing cohorts, the automated workflow significantly reduced doses to the heart and ipsilateral lung compared to manual planning (p < 0.05). For left-sided PMRMRT, the heart dose was reduced by 15.6% (D₁₀), 18.7% (D₅), and 9.8% (D_mean), while the ipsilateral lung dose decreased by up to 6.3% (D_mean). In BCRT cases, automated plans were not significant improved compared to manual plans. Importantly, all automated plans maintained target volume coverage and dose homogeneity comparable to manual plans (p > 0.05).

Conclusion: The OVH-based framework effectively translated anatomy into achievable objectives, significantly improving heart and lung sparing for complex PMRMRT cases while streamlining clinical workflows.

Backgroud: The expanding clinical use of helical tomotherapy (HT) has raised concerns regarding its potential to increase low-dose lung exposure and the risk of radiation pneumonitis (RP) in thoracic radiotherapy. While a few retrospective studies have compared dosimetric parameters and RP rates between HT and fixed-field intensity-modulated radiation therapy (IMRT), their findings remain inconsistent, necessitating a prospective randomized controlled trial for clarification.

Purpose: To prospectively compare dosimetric parameters and the incidence of RP between HT and IMRT in patients with lung or esophageal cancer.

Methods: Patients eligible for thoracic radiotherapy were enrolled. Both HT and IMRT plans were designed and optimized for each patient, with a prescription equivalent dose in 2 Gy /fraction (EQD2) ≥50 Gy to the gross tumor volume (GTV). Plans were evaluated based on target dose coverage, dose-volume histograms, and other dosimetric indices. RP was diagnosed and graded according to the Common Terminology Criteria for Adverse Events (version 5.0). Risk factors for RP were identified using univariate analysis.

Results: Between February and September 2022, 110 consecutive patients with lung or esophageal cancer were enrolled and randomly assigned in a 1:1 ratio to either the HT group (n = 54) or the IMRT group (n = 56). Compared with IMRT, HT had a significant reduction in lung V20 (p = 0.002) and mean lung dose (p = 0.013). Furthermore, the HT group exhibited a superior conformity index for the planning gross tumor volume of the primary lesion (PGTVp) (p = 0.004) and a lower homogeneity index for all planning target volumes (PTVs) (p < 0.001). At a median follow-up of 14.0 months, the rate of grade≥2 RP for the entire cohort was 14.5%, with no significant differences between the HT and IMRT groups (p = 0.61).

Conclusions: Compared with fixed-field IMRT, HT provided superior dose distribution to the PTVs while maintaining a comparable incidence of RP in patients undergoing thoracic radiotherapy.

Purpose: To present the clinical commissioning of the world's first multi-room Varian ProBeam 360° proton pencil beam scanning system.

Methods: The state-of-the-art system includes two clinical treatment rooms with 360° rotating gantries, a superconducting cyclotron, an energy selection system, a beam transport system and scanning nozzles. These components deliver proton spots ranging from 3.97 to 30.03 g/cm² to arbitrarily shaped target volumes over a scanning area of 25 cm × 25 cm at isocenter. Proton beam ranges (R₈₀) were measured and verified independently in both gantry rooms to ensure agreement with beam specifications. Dosimetric parameters, including depth dose curves, in-air spot profiles and dose per monitor unit (MU) as a function of energy, were measured and used to create a dose calculation model in the RayStation treatment planning system (TPS). Treatment plans with various sizes of spread-out Bragg peaks (SOBPs) and simulated patient plans for a range of clinical sites were created and measured at various depths to validate the TPS's beam model accuracy. Additionally, beam matching between the two rooms was performed and validated.

Results: Across the full energy range of 69-218 MeV, the measured R₈₀ in both rooms were identical within 0.4 ± 0.2 mm deviation from the expected nominal range. In-air spot sizes agreed within 5.7 ± 1.8% while outputs matched within 1.0 ± 0.5%. The average point dose difference was 0.2 ± 0.7% for over 80 measurements of SOBP validation plans from the TPS calculations and all planar dose measurements matched TPS calculations with over 90% of data passing a 2mm/2% gamma criterion. All patient plans were validated at a 3mm/3% criterion and demonstrated over 90% of data passing.

Conclusion: Both gantry systems were successfully commissioned for clinical use. Accurate measurements with robust validation ensured essential parameters for beam delivery and dosimetry were characterized for safe patient treatments.