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1.
Brachytherapy ; 23(3): 274-281, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38418362

RESUMO

BACKGROUND AND PURPOSE: Although MRI-based image guided adaptive brachytherapy (IGABT) for locally advanced cervical cancer (LACC) has resulted in favorable outcomes, it can be logistically complex and time consuming compared to 2D image-based brachytherapy, and both physically and emotionally intensive for patients. This prospective study aims to perform time-action and patient experience analyses during IGABT to guide further improvements. MATERIALS AND METHODS: LACC patients treated with IGABT were included for the time-action (56 patients) and patient experience (29 patients) analyses. Times per treatment step were reported on a standardized form. For the patient experience analysis, a baseline health status was established with the EQ-5D-5L questionnaire and the perceived pain, anxiety and duration for each treatment step were assessed with the NRS-11. RESULTS: The median total procedure time from arrival until discharge was 530 (IQR: 480-565) minutes. Treatment planning (delineation, reconstruction, optimization) required the most time and took 175 (IQR: 145-195) minutes. Highest perceived pain was reported during applicator removal and treatment planning, anxiety during applicator removal, and duration during image acquisition and treatment planning. Perceived pain, anxiety and duration were correlated. Higher pre-treatment pain and anxiety scores were associated with higher perceived pain, anxiety and duration. CONCLUSION: This study highlights the complexity, duration and impact on patient experience of the current IGABT workflow. Patient reported pre-treatment pain and anxiety can help identify patients that may benefit from additional support. Research and implementation of measures aiming at shortening the overall procedure duration, which may include logistical, staffing and technological aspects, should be prioritized.


Assuntos
Braquiterapia , Neoplasias do Colo do Útero , Humanos , Feminino , Neoplasias do Colo do Útero/radioterapia , Neoplasias do Colo do Útero/diagnóstico por imagem , Pessoa de Meia-Idade , Estudos Prospectivos , Idoso , Radioterapia Guiada por Imagem/métodos , Adulto , Fatores de Tempo , Ansiedade , Satisfação do Paciente , Planejamento da Radioterapia Assistida por Computador , Imagem por Ressonância Magnética Intervencionista
2.
Med Phys ; 51(5): 3698-3710, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38226798

RESUMO

BACKGROUND: The steep radiation dose gradients in cervical cancer brachytherapy (BT) necessitate a thorough understanding of the behavior of afterloader source cables or needles in the curved channels of (patient-tailored) applicators. PURPOSE: The purpose of this study is to develop and validate computer models to simulate: (1) BT source positions, and (2) insertion forces of needles in curved applicator channels. The methodology presented can be used to improve the knowledge of instrument behavior in current applicators and aid the development of novel (3D-printed) BT applicators. METHODS: For the computer models, BT instruments were discretized in finite elements. Simulations were performed in SPACAR by formulating nodal contact force and motion input models and specifying the instruments' kinematic and dynamic properties. To evaluate the source cable model, simulated source paths in ring applicators were compared with manufacturer-measured source paths. The impact of discrepancies on the dosimetry was estimated for standard plans. To validate needle models, simulated needle insertion forces in curved channels with varying curvature, torsion, and clearance, were compared with force measurements in dedicated 3D-printed templates. RESULTS: Comparison of simulated with manufacturer-measured source positions showed 0.5-1.2 mm median and <2.0 mm maximum differences, in all but one applicator geometry. The resulting maximum relative dose differences at the lateral surface and at 5 mm depth were 5.5% and 4.7%, respectively. Simulated insertion forces for BT needles in curved channels accurately resembled the forces experimentally obtained by including experimental uncertainties in the simulation. CONCLUSION: The models developed can accurately predict source positions and insertion forces in BT applicators. Insights from these models can aid novel applicator design with improved motion and force transmission of BT instruments, and contribute to the estimation of overall treatment precision. The methodology presented can be extended to study other applicator geometries, flexible instruments, and afterloading systems.


Assuntos
Braquiterapia , Neoplasias do Colo do Útero , Braquiterapia/instrumentação , Humanos , Neoplasias do Colo do Útero/radioterapia , Feminino , Simulação por Computador , Análise de Elementos Finitos , Agulhas , Dosagem Radioterapêutica , Radiometria/instrumentação
3.
Cancers (Basel) ; 14(6)2022 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-35326577

RESUMO

The most important prognostic factor for the survival of advanced-stage epithelial ovarian cancer (EOC) is the completeness of cytoreductive surgery (CRS). Therefore, an intraoperative technique to detect microscopic tumors would be of great value. The aim of this pilot study is to assess the feasibility of near-infrared hyperspectral imaging (HSI) for EOC detection in ex vivo tissue samples. Images were collected during CRS in 11 patients in the wavelength range of 665−975 nm, and processed by calibration, normalization, and noise filtering. A linear support vector machine (SVM) was employed to classify healthy and tumorous tissue (defined as >50% tumor cells). Classifier performance was evaluated using leave-one-out cross-validation. Images of 26 tissue samples from 10 patients were included, containing 26,446 data points that were matched to histopathology. Tumorous tissue could be classified with an area under the curve of 0.83, a sensitivity of 0.81, a specificity of 0.70, and Matthew's correlation coefficient of 0.41. This study paves the way to in vivo and intraoperative use of HSI during CRS. Hyperspectral imaging can scan a whole tissue surface in a fast and non-contact way. Our pilot study demonstrates that HSI and SVM learning can be used to discriminate EOC from surrounding tissue.

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