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1.
Phys Med ; 114: 103146, 2023 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-37778208

RESUMEN

PURPOSE: To evaluate and characterize the overall clinical functionality and workflow of the newly released Varian Identify system (version 2.3). METHODS: Three technologies included in the Varian Identify system were evaluated: patient biometric authentication, treatment accessory device identification, and surface-guided radiation therapy (SGRT) function. Biometric authentication employs a palm vein reader. Treatment accessory device verification utilizes two technologies: device presence via Radio Frequency Identification (RFID) and position via optical markers. Surface-guidance was evaluated on both patient orthopedic setup at loading position and surface matching and tracking at treatment isocenter. A phantom evaluation of the consistency and accuracy for Identify SGRT function was performed, including a system consistency test, a translational shift and rotational accuracy test, a pitch and roll accuracy test, a continuous recording test, and an SGRT vs Cone-Beam CT (CBCT) agreement test. RESULTS: 201 patient authentications were verified successfully with palm reader. All patient treatment devices were successfully verified for their presences and positions (indexable devices). The patient real-time orthopedic pose was successfully adjusted to match the reference surface captured at simulation. SGRT-reported shift consistency against couch readout was within (0.1 mm, 0.030). The shift accuracy was within (0.3 mm, 0.10). In continuous recording mode, the maximum variation was 0.2 ± 0.12 mm, 0.030 ± 0.020. The difference between Identify SGRT offset and CBCT was within (1 mm, 10). CONCLUSIONS: This clinical evaluation confirms that Identify accurately functions for patient palm identification and patient treatment device presence and position verification. Overall SGRT consistency and accuracy was within (1 mm, 10), within the 2 mm criteria of AAPM TG302.


Asunto(s)
Radioterapia Guiada por Imagen , Humanos , Radioterapia Guiada por Imagen/métodos , Tomografía Computarizada de Haz Cónico/métodos , Fantasmas de Imagen , Simulación por Computador , Biometría , Planificación de la Radioterapia Asistida por Computador/métodos
2.
Med Phys ; 50(10): 5978-5986, 2023 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-37683108

RESUMEN

BACKGROUND: It has been shown that a significant reduction of mean heart dose and left anterior descending artery (LAD) dose can be achieved through the use of DIBH for left breast radiation therapy. Surface-guided DIBH has been widely adopted during the last decade, and there are mainly three commercially available SGRT systems. The reports of the performance of a newly released SGRT system for DIBH application are currently very limited. PURPOSE: To evaluate the clinical performance of a newly released SGRT system on DIBH for left breast radiation therapy. METHODS: Twenty-five left breast cancer patients treated with DIBH utilizing Varian's Identify system were included (total 493-fraction treatments). Four aspects of the clinical performance were evaluated: Identify offsets of free breathing post patient setup from tattoos, Identify offsets during DIBH, Identify agreement with radiographic ports during DIBH, and DIBH reference surface re-capture post patient shifts. The systematic and random errors of free breathing Identify offsets post patient setup were calculated for each patient, as well as for offsets during DIBH. Radiographic ports were taken when the patient's DIBH position was within the clinical tolerance of (± 0.3 cm, ± 30 ), and these were then compared with treatment field DRRs. If the ports showed that the patient alignment did not agree with the DRRs within 3 mm, a patient shift was performed. A new reference surface was captured and verification ports were taken. RESULTS: The all-patient average systematic and random errors of Identify offsets for free breathing were within (0.4 cm, 1.50 ) post tattoo setup. The maximum per-patient systematic and random errors were (1.1 cm, 6.20 ) and (0.9 cm, 20 ), and the maximum amplitude of Identify offsets were (2.59 cm, 90 ). All 493-fraction DIBH treatments were delivered and successfully guided by the Identify SGRT system. The systematic and random errors of Identify offsets for DIBH were within (0.2 cm, 2.30 ). Seven patients needed re-captured surface references due to surface variation or position shifts based on the ports. All patient DIBH verification ports guided by Identify were approved by attending physicians. CONCLUSION: This evaluation showed that the Identify system performed effectively for surface-guided patient setup and surface-guided DIBH imaging and treatment delivery. The feature of color-coded real-time patient surface matching feedback facilitated the evaluation of the patient alignment accuracy and the adjustment of the patient position to match the reference.


Asunto(s)
Neoplasias de la Mama , Radioterapia Guiada por Imagen , Humanos , Femenino , Contencion de la Respiración , Planificación de la Radioterapia Asistida por Computador/métodos , Respiración , Radioterapia Guiada por Imagen/métodos , Corazón , Dosificación Radioterapéutica , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/radioterapia
3.
Neurooncol Pract ; 9(5): 380-389, 2022 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-36134015

RESUMEN

Background: A post-operative MRI (MRIpost-op) performed within 72 h is routinely used for radiation treatment planning in glioblastoma (GBM) patients, with radiotherapy starting about 4-6 weeks after surgery. Some patients undergo an additional pre-radiotherapy MRI (MRIpre-RT) about 2-6 weeks after surgery. We sought to analyze the incidence of rapid early progression (REP) between surgery and initiation of radiotherapy seen on MRIpre-RT and the impact on radiation target volumes. Methods: Patients with GBM diagnosed between 2018 and 2020 who had an MRIpost-op and MRIpre-RT were retrospectively identified. Criteria for REP was based on Modified RANO criteria. Radiation target volumes were created and compared using the MRIpost-op and MRIpre-RT. Results: Fifty patients met inclusion criteria. The median time between MRIpost-op and MRIpre-RT was 26 days. Indications for MRIpre-RT included clinical trial enrollment in 41/50 (82%), new symptoms in 5/50 (10%), and unspecified in 4/50 (8%). REP was identified in 35/50 (70%) of patients; 9/35 (26%) had disease progression outside of the MRIpost-op-based high dose treatment volumes. Treatment planning with MRIpost-op yielded a median undertreatment of 27.1% of enhancing disease and 11.2% of surrounding subclinical disease seen on MRIpre-RT. Patients without REP had a 38% median volume reduction of uninvolved brain if target volumes were planned with MRIpre-RT. Conclusion: Given the incidence of REP and its impact on treatment volumes, we recommend using MRIpre-RT for radiation treatment planning to improve coverage of gross and subclinical disease, allow for early identification of REP, and decrease radiation treatment volumes in patients without REP.

4.
Pract Radiat Oncol ; 11(2): e229-e235, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32919040

RESUMEN

PURPOSE: To evaluate the impact of Varian Identify, a novel combined radiofrequency identification, biometric and surface-matching technology, on its potential for patient safety and prevention of radiation therapy treatment deviations. METHODS AND MATERIALS: One hundred eight radiation therapy treatment deviation reports at our facility over the past 8 years were analyzed. Three major categories were defined based on the time point of occurrence: physician order deviations (19.4%), treatment-planning deviations (24.1%), and machine treatment deviations (56.5%). The impact of Identify on potential prevention of machine treatment deviations was analyzed. A failure mode and effects analysis was performed on the 5 most frequently occurring errors preventable with Identify. Safety analysis of the Identify system was reported based on 3.5 years of clinical data post-Identify system installation on 3 treatment vaults. RESULTS: Of the 61 machine treatment deviations, 47 (77%) were interpreted as being preventable by using Identify. Our failure mode and effects analysis showed reductions in all risk priority numbers post-Identify application. Safety analysis of the Identify system from our direct observation that for approximately 7 cumulative years of Identify use in 3 different treatment vaults, where 9 deviations would have been expected to occur over this combined period, zero machine treatment events occurred. CONCLUSIONS: The combination of Identify biometric, radiofrequency identification, and surface-matching technologies was observed to enable an effective process for enhancing safety and efficiency of radiation therapy treatment. A significant reduction in machine-related deviations was observed.


Asunto(s)
Identificación Biométrica , Planificación de la Radioterapia Asistida por Computador , Humanos , Seguridad del Paciente
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