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1.
Semin Radiat Oncol ; 34(3): 344-350, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38880543

RESUMEN

FLASH radiotherapy (RT) is emerging as a potentially revolutionary advancement in cancer treatment, offering the potential to deliver RT at ultra-high dose rates (>40 Gy/s) while significantly reducing damage to healthy tissues. Democratizing FLASH RT by making this cutting-edge approach more accessible and affordable for healthcare systems worldwide would have a substantial impact in global health. Here, we review recent developments in FLASH RT and present perspective on further developments that could facilitate the democratizing of FLASH RT. These include upgrading and validating current technologies that can deliver and measure the FLASH radiation dose with high accuracy and precision, establishing a deeper mechanistic understanding of the FLASH effect, and optimizing dose delivery conditions and parameters for different types of tumors and normal tissues, such as the dose rate, dose fractionation, and beam quality for high efficacy. Furthermore, we examine the potential for democratizing FLASH radioimmunotherapy leveraging evidence that FLASH RT can make the tumor microenvironment more immunogenic, and parallel developments in nanomedicine or use of smart radiotherapy biomaterials for combining RT and immunotherapy. We conclude that the democratization of FLASH radiotherapy represents a major opportunity for concerted cross-disciplinary research collaborations with potential for tremendous impact in reducing radiotherapy disparities and extending the cancer moonshot globally.


Asunto(s)
Neoplasias , Humanos , Neoplasias/radioterapia , Dosificación Radioterapéutica , Fraccionamiento de la Dosis de Radiación , Radioterapia/métodos , Microambiente Tumoral/efectos de la radiación
2.
IEEE Trans Med Imaging ; PP2024 Apr 11.
Artículo en Inglés | MEDLINE | ID: mdl-38602853

RESUMEN

Image-guided interventional oncology procedures can greatly enhance the outcome of cancer treatment. As an enhancing procedure, oncology smart material delivery can increase cancer therapy's quality, effectiveness, and safety. However, the effectiveness of enhancing procedures highly depends on the accuracy of smart material placement procedures. Inaccurate placement of smart materials can lead to adverse side effects and health hazards. Image guidance can considerably improve the safety and robustness of smart material delivery. In this study, we developed a novel generative deep-learning platform that highly prioritizes clinical practicality and provides the most informative intra-operative feedback for image-guided smart material delivery. XIOSIS generates a patient-specific 3D volumetric computed tomography (CT) from three intraoperative radiographs (X-ray images) acquired by a mobile C-arm during the operation. As the first of its kind, XIOSIS (i) synthesizes the CT from small field-of-view radiographs;(ii) reconstructs the intra-operative spacer distribution; (iii) is robust; and (iv) is equipped with a novel soft-contrast cost function. To demonstrate the effectiveness of XIOSIS in providing intra-operative image guidance, we applied XIOSIS to the duodenal hydrogel spacer placement procedure. We evaluated XIOSIS performance in an image-guided virtual spacer placement and actual spacer placement in two cadaver specimens. XIOSIS showed a clinically acceptable performance, reconstructed the 3D intra-operative hydrogel spacer distribution with an average structural similarity of 0.88 and Dice coefficient of 0.63 and with less than 1 cm difference in spacer location relative to the spinal cord.

3.
Cancers (Basel) ; 16(7)2024 Mar 22.
Artículo en Inglés | MEDLINE | ID: mdl-38610923

RESUMEN

To develop ultrasound-guided radiotherapy, we proposed an assistant structure with embedded markers along with a novel alternative method, the Aligned Peak Response (APR) method, to alter the conventional delay-and-sum (DAS) beamformer for reconstructing ultrasound images obtained from a flexible array. We simulated imaging targets in Field-II using point target phantoms with point targets at different locations. In the experimental phantom ultrasound images, image RF data were acquired with a flexible transducer with in-house assistant structures embedded with needle targets for testing the accuracy of the APR method. The lateral full width at half maximum (FWHM) values of the objective point target (OPT) in ground truth ultrasound images, APR-delayed ultrasound images with a flat shape, and images acquired with curved transducer radii of 500 mm and 700 mm were 3.96 mm, 4.95 mm, 4.96 mm, and 4.95 mm. The corresponding axial FWHM values were 1.52 mm, 4.08 mm, 5.84 mm, and 5.92 mm, respectively. These results demonstrate that the proposed assistant structure and the APR method have the potential to construct accurate delay curves without external shape sensing, thereby enabling a flexible ultrasound array for tracking pancreatic tumor targets in real time for radiotherapy.

4.
Cancers (Basel) ; 16(6)2024 Mar 20.
Artículo en Inglés | MEDLINE | ID: mdl-38539546

RESUMEN

Globally, cervical cancer is the fourth leading cancer among women and is dominant in resource-poor settings in its occurrence and mortality. This study focuses on developing liquid immunogenic fiducial eluter (LIFE) Biomaterial with components that include biodegradable polymers, nanoparticles, and an immunoadjuvant. LIFE Biomaterial is designed to provide image guidance during radiotherapy similar to clinically used liquid fiducials while enhancing therapeutic efficacy for advanced cervical cancer. C57BL6 mice were used to grow subcutaneous tumors on bilateral flanks. The tumor on one flank was then treated using LIFE Biomaterial prepared with the immunoadjuvant anti-CD40, with/without radiotherapy at 6 Gy. Computed tomography (CT) and magnetic resonance (MR) imaging visibility were also evaluated in human cadavers. A pharmacodynamics study was also conducted to assess the safety of LIFE Biomaterial in healthy C57BL6 female mice. Results showed that LIFE Biomaterial could provide both CT and MR imaging contrast over time. Inhibition in tumor growth and prolonged significant survival (* p < 0.05) were consistently observed for groups treated with the combination of radiotherapy and LIFE Biomaterial, highlighting the potential for this strategy. Minimal toxicity was observed for healthy mice treated with LIFE Biomaterial with/without anti-CD40 in comparison to non-treated cohorts. The results demonstrate promise for the further development and clinical translation of this approach to enhance the survival and quality of life of patients with advanced cervical cancer.

5.
IEEE Trans Biomed Eng ; 71(4): 1298-1307, 2024 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-38048239

RESUMEN

Flexible array transducers can adapt to patient-specific geometries during real-time ultrasound (US) image-guided therapy monitoring. This makes the system radiation-free and less user-dependency. Precise estimation of the flexible transducer's geometry is crucial for the delay-and-sum (DAS) beamforming algorithm to reconstruct B-mode US images. The primary innovation of this research is to build a system named FLexible transducer with EXternal tracking (FLEX) to estimate the position of each element of the flexible transducer and reconstruct precise US images. FLEX utilizes customized optical markers and a tracker to monitor the probe's geometry, employing a polygon fitting algorithm to estimate the position and azimuth angle of each transducer element. Subsequently, the traditional DAS algorithm processes the delay estimation from the tracked element position, reconstructing US images from radio-frequency (RF) channel data. The proposed method underwent evaluation on phantoms and cadaveric specimens, demonstrating its clinical feasibility. Deviations in tracked probe geometry compared to ground truth were minimal, measuring 0.50 ± 0.29 mm for the CIRS phantom, 0.54 ± 0.35 mm for the deformable phantom, and 0.36 ± 0.24 mm on the cadaveric specimen. Reconstructing the US image using tracked probe geometry significantly outperformed the untracked geometry, as indicated by a Dice score of 95.1 ± 3.3% versus 62.3 ± 9.2% for the CIRS phantom. The proposed method achieved high accuracy (<0.5 mm error) in tracking the element position for various random curvatures applicable for clinical deployment. The evaluation results show that the radiation-free proposed method can effectively reconstruct US images and assist in monitoring image-guided therapy with minimal user dependency.


Asunto(s)
Algoritmos , Transductores , Humanos , Ultrasonografía , Fantasmas de Imagen , Cadáver
6.
Cancers (Basel) ; 15(13)2023 Jun 22.
Artículo en Inglés | MEDLINE | ID: mdl-37444403

RESUMEN

Pancreatic cancer with less than 10% 3-year survival rate is one of deadliest cancer types and greatly benefits from enhanced radiotherapy. Organ motion monitoring helps spare the normal tissue from high radiation and, in turn, enables the dose escalation to the target that has been shown to improve the effectiveness of RT by doubling and tripling post-RT survival rate. The flexible array transducer is a novel and promising solution to address the limitation of conventional US probes. We proposed a novel shape estimation for flexible array transducer using two sequential algorithms: (i) an optical tracking-based system that uses the optical markers coordinates attached to the probe at specific positions to estimate the array shape in real-time and (ii) a fully automatic shape optimization algorithm that automatically searches for the optimal array shape that results in the highest quality reconstructed image. We conducted phantom and in vivo experiments to evaluate the estimated array shapes and the accuracy of reconstructed US images. The proposed method reconstructed US images with low full-width-at-half-maximum (FWHM) of the point scatters, correct aspect ratio of the cyst, and high-matching score with the ground truth. Our results demonstrated that the proposed methods reconstruct high-quality ultrasound images with significantly less defocusing and distortion compared with those without any correction. Specifically, the automatic optimization method reduced the array shape estimation error to less than half-wavelength of transmitted wave, resulting in a high-quality reconstructed image.

7.
IEEE J Biomed Health Inform ; 23(3): 1110-1118, 2019 05.
Artículo en Inglés | MEDLINE | ID: mdl-30113902

RESUMEN

Ultrasound (US) is widely used as a low-cost alternative to computed tomography or magnetic resonance and primarily for preliminary imaging. Since speckle intensity in US images is inherently stochastic, readers are often challenged in their ability to identify the pathological regions in a volume of a large number of images. This paper introduces a generalized approach for volumetric segmentation of structures in US images and volumes. We employ an iterative random walks (IRW) solver, a random forest learning model, and a gradient vector flow (GVF) based interframe belief propagation technique for achieving cross-frame volumetric segmentation. At the start, a weak estimate of the tissue structure is obtained using estimates of parameters of a statistical mechanics model of US tissue interaction. Ensemble learning of these parameters further using a random forest is used to initialize the segmentation pipeline. IRW is used for correcting the contour in various steps of the algorithm. Subsequently, a GVF-based interframe belief propagation is applied to adjacent frames based on the initialization of contour using information in the current frame to segment the complete volume by frame-wise processing. We have experimentally evaluated our approach using two different datasets. Intravascular ultrasound (IVUS) segmentation was evaluated using 10 pullbacks acquired at 20 MHz and thyroid US segmentation is evaluated on 16 volumes acquired at [Formula: see text] MHz. Our approach obtains a Jaccard score of [Formula: see text] for IVUS segmentation and [Formula: see text] for thyroid segmentation while processing each frame in [Formula: see text] for the IVUS and in [Formula: see text] for thyroid segmentation without the need of any computing accelerators such as GPUs.


Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Modelos Estadísticos , Ultrasonografía/métodos , Abdomen/diagnóstico por imagen , Algoritmos , Humanos , Fantasmas de Imagen , Procesos Estocásticos , Glándula Tiroides/diagnóstico por imagen
8.
Int J Comput Assist Radiol Surg ; 12(4): 539-552, 2017 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-28070776

RESUMEN

PURPOSE: Diffusion-weighted imaging (DWI) is a widely used medical imaging modality for diagnosis and monitoring of cerebral stroke. The identification of exact location of stroke lesion helps in perceiving its characteristics, an essential part of diagnosis and treatment planning. This task is challenging due to the typical shape of the stroke lesion. This paper proposes an efficient method for computer-aided delineation of stroke lesions from DWI images. METHOD: Proposed methodology comprises of three steps. At the initial step, image contrast has been improved by applying fuzzy intensifier leading to the better visual quality of the stroke lesion. In the following step, a two-class (stroke lesion area vs. non-stroke lesion area) segmentation technique based on Gaussian mixture model has been designed for the localization of stroke lesion. To eliminate the artifacts which would appear during segmentation process, a binary morphological post-processing through area operator has been defined for exact delineation of the lesion area. RESULT: The performance of the proposed methodology has been compared with the manually delineated images (ground truth) obtained from different experts, individually. Quantitative evaluation with respect to various performance measures (such as dice coefficient, Jaccard score, and correlation coefficient) shows the efficient performance of the proposed technique.


Asunto(s)
Imagen de Difusión por Resonancia Magnética/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Accidente Cerebrovascular/diagnóstico por imagen , Bases de Datos Factuales , Humanos
9.
Annu Int Conf IEEE Eng Med Biol Soc ; 2016: 4125-4128, 2016 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-28269190

RESUMEN

This paper presents a novel methodology for automated detection and extraction of the lumen wall from Intravascular Ultrasound (IVUS) frames. IVUS is an in-vivo pull back imaging technique and provides a sequential frame of images for diagnosis of atherosclerotic heart disease. The detection and segmentation of lumen wall is necessary for predicting the arterial wall blockage. Lumen wall is recognized and segmented with the help of seed refinement and random walks algorithms, in tunica and lumen area. The proposed methodology was tested on 147 frames of 13 patients. Proposed method achieves significant performances for automated lumen wall detection and extraction as compared with existing literature.


Asunto(s)
Algoritmos , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Vasos Coronarios/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Ultrasonografía/métodos , Automatización , Humanos
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