Validation of T2- and diffusion-weighted magnetic resonance imaging for mapping intra-prostatic tumour prior to focal boost dose-escalation using intensity-modulated radiotherapy (IMRT)

Alexander, E.; Murray, Julia; Morgan, Veronica A.; Giles, Sharon; Riches, Sophie F.; Hazell, Stephen; Thomas, Karen; Sohaib, S.A.; Thompson, Alan; Gao, Annie; Dearnaley, David P.; deSouza, Nandita M.

doi:10.1016/j.radonc.2019.07.030

Cited by 11 publications

(9 citation statements)

References 47 publications

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“…The accuracy of mp-MRI against a template biopsy gold standard has been reported in a subset of these patients. 18 All patients commenced hormone therapy after the mp-MRI. ADT was prescribed in accordance with local guidelines, giving short or long course ADT with initial bicalutamide for prevention of testosterone flare.…”

Section: Protocol Interventionmentioning

confidence: 99%

Standard and Hypofractionated Dose Escalation to Intraprostatic Tumor Nodules in Localized Prostate Cancer: Efficacy and Toxicity in the DELINEATE Trial

Murray

Tree

Alexander

et al. 2020

International Journal of Radiation Oncology*Biology*Physics

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Purpose: To report a planned analysis of the efficacy and toxicity of dose escalation to the intraprostatic dominant nodule identified on multiparametric magnetic resonance imaging using standard and hypofractionated external beam radiation therapy. Methods and Materials: DELINEATE is a single centre prospective phase 2 multicohort study including standard (cohort A: 74 Gy in 37 fractions) and moderately hypofractionated (cohort B: 60 Gy in 20 fractions) prostate image guided intensity modulated radiation therapy in patients with National Comprehensive Cancer Network intermediate-and high-risk disease. Patients received an integrated boost of 82 Gy (cohort A) and 67 Gy (cohort B) to lesions visible on multiparametric magnetic

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Section: Protocol Interventionmentioning

confidence: 99%

Standard and Hypofractionated Dose Escalation to Intraprostatic Tumor Nodules in Localized Prostate Cancer: Efficacy and Toxicity in the DELINEATE Trial

Murray

Tree

Alexander

et al. 2020

International Journal of Radiation Oncology*Biology*Physics

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“…(2) While the dose delivered to the prostate is typically homogenous in external RT compared to brachytherapy, recent studies have shown that dose escalation to the dominant intraprostatic lesion (DIL), detected via multi-parametric MRI (mp-MRI) scans (3,4), could increase the tumor control probability (TCP). (5,6) Such dose escalation has been shown to be feasible with brachytherapy (3,(7)(8)(9)(10)(11)(12) and photon X-ray beams using volumetric modulated arc therapy (VMAT), (4,8,(13)(14)(15) Tomotherapy, (16) particle therapy, (9,17) and Cyberknife. (18) Proton therapy provides superior dose distributions and dosimetric advantages over photon X-ray beams in many sites.…”

Section: Introductionmentioning

confidence: 99%

Dosimetric Uncertainties in Dominant Intraprostatic Lesion Simultaneous Boost Using Intensity Modulated Proton Therapy

Zhou

Yang

Chang

et al. 2022

Advances in Radiation Oncology

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“…2,5,26 Therefore, segmentation of suspicious MRI lesions as an alternative strategy is meaningful and is needed in clinical practice, based on the clinically acceptable correlation between the two kinds of lesions. [26][27][28] This study first paid attention to the deep learning-based segmentation of suspicious MRI lesions, contributing to the clinical practice of boosting these lesions during radiation delivery. An MRI database with manual contours was created from our clinical data for this objective.…”

Section: Introductionmentioning

confidence: 99%

“…Under the assumption that the visible MRI lesion is at higher risk of local failure than the other part of the prostate gland, some groups have looked at intraprostatic lesion boosts by dose‐escalation to the MRI visible lesion 2,5,26 . Therefore, segmentation of suspicious MRI lesions as an alternative strategy is meaningful and is needed in clinical practice, based on the clinically acceptable correlation between the two kinds of lesions 26–28 …”

Section: Introductionmentioning

confidence: 99%

Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet

Chen

et al. 2020

Medical Physics

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Purpose Contouring intraprostatic lesions is a prerequisite for dose‐escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning‐based approach was developed for automatic intraprostatic lesion segmentation in multiparametric magnetic resonance imaging (mpMRI) images contributing to clinical practice. Methods Multiparametric magnetic resonance imaging images from 136 patient cases were collected from our institution, and all these cases contained suspicious lesions with Prostate Imaging Reporting and Data System (PI‐RADS) score ≥ 4. The contours of the lesion and prostate were manually created on axial T2‐weighted (T2W), apparent diffusion coefficient (ADC) and high b‐value diffusion‐weighted imaging (DWI) images to provide the ground truth data. Then a multiple branch UNet (MB‐UNet) was proposed for the segmentation of an indistinct target in multi‐modality MRI images. An encoder module was designed with three branches for the three MRI modalities separately, to fully extract the high‐level features provided by different MRI modalities; an input module was added by using three sub‐branches for three consecutive image slices, to consider the contour consistency among different image slices; deep supervision strategy was also integrated into the network to speed up the convergency of the network and improve the performance. The probability maps of the background, normal prostate and lesion were output by the network to generate the segmentation of the lesion, and the performance was evaluated using the dice similarity coefficient (DSC) as the main metric. Results A total of 162 lesions were contoured on 652 image slices, with 119 lesions in the peripheral zone, 38 in the transition zone, four in the central zone and one in the anterior fibromuscular stroma. All prostates were also contoured on 1,264 image slices. As for the segmentation of lesions in the testing set, MB‐UNet achieved a per case DSC of 0.6333, specificity of 0.9993, sensitivity of 0.7056; and global DSC of 0.7205, specificity of 0.9993, sensitivity of 0.7409. All the three deep learning strategies adopted in this study contributed to the performance promotion of the MB‐UNet. Missing the DWI modality would degrade the segmentation performance more markedly compared with the other two modalities. Conclusions A deep learning‐based approach with proposed MB‐UNet was developed to automatically segment suspicious lesions in mpMRI images. This study makes it feasible to adopt boosting intraprostatic lesions in clinical practice to achieve better outcomes.

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Validation of T2- and diffusion-weighted magnetic resonance imaging for mapping intra-prostatic tumour prior to focal boost dose-escalation using intensity-modulated radiotherapy (IMRT)

Cited by 11 publications

References 47 publications

Standard and Hypofractionated Dose Escalation to Intraprostatic Tumor Nodules in Localized Prostate Cancer: Efficacy and Toxicity in the DELINEATE Trial

Standard and Hypofractionated Dose Escalation to Intraprostatic Tumor Nodules in Localized Prostate Cancer: Efficacy and Toxicity in the DELINEATE Trial

Dosimetric Uncertainties in Dominant Intraprostatic Lesion Simultaneous Boost Using Intensity Modulated Proton Therapy

Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet

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