MR‐guided prostate interventions

Tempany, Clare M.; Straus, Sarah; Hata, Nobuhiko; Haker, Steven

doi:10.1002/jmri.21259

Cited by 57 publications

(38 citation statements)

References 79 publications

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“…CDash 9 is a web-based server that organizes the results of software testing. The Visualization Toolkit (VTK) 10 provides the key building blocks for 3D computer graphics and visualization. The Insight Toolkit (ITK) 11 is a library developed specifically for the tasks related to medical image registration and segmentation, and for implementing new image analysis algorithms.…”

Section: Overview Of 3d Slicermentioning

confidence: 99%

3D Slicer as an image computing platform for the Quantitative Imaging Network

Fedorov

Beichel

Kalpathy–Cramer

et al. 2012

Magnetic Resonance Imaging

6,320

3,722

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Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions.In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams,

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Section: Overview Of 3d Slicermentioning

confidence: 99%

3D Slicer as an image computing platform for the Quantitative Imaging Network

Fedorov

Beichel

Kalpathy–Cramer

et al. 2012

Magnetic Resonance Imaging

6,320

3,722

View full text Add to dashboard Cite

show abstract

“…TRUS-guided biopsy in patients with elevated PSA levels has low sensitivity of around 60% and a high false-negative rate of 15-30% [32,33]. DWI may be helpful in localising tumour in patients with previous failed TRUS biopsy, with the potential to improve rebiopsy success rates.…”

Section: Pre-treatment Detection: Tumour Localisation and Prognosticamentioning

confidence: 99%

Diffusion weighted imaging in prostate cancer

2010

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Diffusion-weighted imaging has generated substantial interest in the hope that it can be developed into a robust technique to improve the accuracy of MRI for the evaluation of prostate cancer. This technique has the advantages of short acquisition times, no need for intravenous administration of contrast medium, and the ability to study diffusion of water molecules that indirectly reflects tissue cellularity. In this article, we review the existing literature on the utility of DWI in tumour detection, localisation, treatment response, limitations of the technique, how it compares with other imaging techniques, technical considerations and future directions.

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“…Furthermore, biologic-metabolic MRI imaging methods like spectroscopy, dynamic contrastenhanced studies, and diffusion-weighted images are able to visualize the intraprostatic lesion, which makes targeted interventions, partial radiation dose delivery and dose painting possible [9][10][11]. The utility and clinical efficacy of MR-guided prostate BT has been demonstrated by an increasing number of groups [12][13][14][15][16][17][18][19].…”

Section: Hdrmentioning

confidence: 97%

Open MR-Guided High-Dose-Rate (HDR) Prostate Brachytherapy: Feasibility and Initial Experiences Open MR-Guided High-Dose-Rate (HDR) Prostate Brachytherapy

Lakosi

Antal

Vandulek

et al. 2011

Pathol. Oncol. Res.

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The aim of our pilot study was to demonstrate the feasibility and dosimetric quality of MR-guided HDR prostate brachytherapy in a low-field 0.35T open MRI scanner and to present our initial clinical experiences. 16 patients with intermediate- to high-risk localized prostate cancer were treated with 46-60 Gy of external beam radiotherapy preceded and/or followed by an 8 Gy MR-guided HDR boost. For interventions an MR compatible custom-made system, coaxial needles and plastic catheters were used. Template reconstruction, trajectory planning, image guidance, contouring and treatment planning were exclusively based on MR images. For treatment planning, dose-point- and anatomy-based inverse planning optimization was used. Image quality was found to be good to excellent in almost all cases. The mean catheter placement accuracy modeled by Rayleigh distribution was 2.9 mm with a sigma value of 2.3 mm. The mean and standard deviation (SD) of the dosimetric results for the target volume were the following: V100: 94.2 ± 4.3%, V150: 43.9 ± 6.8%, V200: 18.5 ± 5.9%. The mean D(0.1), D(1) and D1 values for the intraprostatic urethra were 117.6 ± 12.5%, 98.5 ± 19.9% and 122.3 ± 16.4%, respectively. Regarding the rectal wall the mean D(0.1), D(1) and D(2) values were 77.3 ± 7.2%, 64.8 ± 7.5%, and 53.2 ± 9.1%, respectively. The mean maximum dose for the inner rectal surface was 53.5 ± 9.2%. No RTOG Grade 3 or worse acute toxicities were observed. Our method seems to be a promising approach for performing feasible, accurate and high-quality MR-guided HDR prostate brachytherapy. To determine the long term side effects and outcome higher number of patients, additional follow-up is needed.

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MR‐guided prostate interventions

Cited by 57 publications

References 79 publications

3D Slicer as an image computing platform for the Quantitative Imaging Network

3D Slicer as an image computing platform for the Quantitative Imaging Network

Diffusion weighted imaging in prostate cancer

Open MR-Guided High-Dose-Rate (HDR) Prostate Brachytherapy: Feasibility and Initial Experiences Open MR-Guided High-Dose-Rate (HDR) Prostate Brachytherapy

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