An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of [Formula: see text] mm and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.
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http://dx.doi.org/10.1088/1361-6560/aa875f | DOI Listing |
J Imaging Inform Med
December 2024
Biomedical Data Analysis and Visualisation (BDAV) Lab, School of Computer Science, The University of Sydney, Camperdown, NSW, 2050, Australia.
In surgical stabilization of rib fractures (SSRF), the current standard relies on preoperative CT imaging and often incorporates ultrasound (US) imaging. As an alternative, mixed reality (MR) technology holds promise for improving rib fracture localization. This study presents an MR-based visualization system designed for SSRF in a clinical setting.
View Article and Find Full Text PDFTransl Lung Cancer Res
November 2024
Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
IEEE Trans Ultrason Ferroelectr Freq Control
August 2024
Transcranial-focused ultrasound (tFUS) procedures such as neuromodulation and blood-brain barrier (BBB) opening require precise focus placement within the brain. MRI is currently the most reliable tool for focus localization but can be prohibitive for procedures requiring recurrent therapies. We designed, fabricated, and characterized a patient-specific, 3-D-printed, stereotactic frame for repeated tFUS therapy.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
July 2024
Leiden University Medical Center, Department of Ophthalmology, Leiden, the Netherlands.
Background & Purpose: Magnetic resonance imaging (MRI) is increasingly used in treatment preparation of ocular proton therapy, but its spatial accuracy might be limited by geometric distortions due to susceptibility artefacts. A correct geometry of the MR images is paramount since it defines where the dose will be delivered. In this study, we assessed the geometrical accuracy of ocular MRI.
View Article and Find Full Text PDFInsights Imaging
June 2024
Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Objectives: To construct and validate multiparametric MR-based radiomic models based on primary tumors for predicting lymph node metastasis (LNM) following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) patients.
Methods: A total of 150 LARC patients from two independent centers were enrolled. The training cohort comprised 100 patients from center A.
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