2020
DOI: 10.1007/s00520-020-05376-2
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Whole brain radiotherapy improves survival outcomes in primary CNS lymphoma patients ineligible for systemic therapy

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Cited by 10 publications
(10 citation statements)
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“… 20 , 21 With concerns over the long-term neurotoxicity of radiation, 22 oncologists have moved away from WBRT as consolidation in first-line therapy. 23 , 24 …”
Section: Discussionmentioning
confidence: 99%
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“… 20 , 21 With concerns over the long-term neurotoxicity of radiation, 22 oncologists have moved away from WBRT as consolidation in first-line therapy. 23 , 24 …”
Section: Discussionmentioning
confidence: 99%
“…20,21 With concerns over the long-term neurotoxicity of radiation, 22 oncologists have moved away from WBRT as consolidation in first-line therapy. 23,24 Given the rarity of PCNSL and the paucity of Phase III randomized clinical trials for potential treatments, no consensus exists on the optimal frontline regimens, chemotherapeutic agents in addition to HD-MTX, or consolidation therapy with WBRT versus high-dose chemotherapy and autologous stem cell transplant (ASCT). HD-MTX has been proven to reach a therapeutic concentration in the brain and is now considered the first-line treatment of PCNSL, 13 and doses of MTX in the range of 3-8 g/m 2 are frequently used.…”
Section: Discussionmentioning
confidence: 99%
“…96 Other multicentre retrospective studies of elderly PCNSL treated with upfront WBRT have shown OS ranging from seven to eight months. 95,97,98 Risk and benefit ratio should be carefully considered when offering WBRT in this clinical context.…”
Section: Role Of Palliative and Best Supportive Carementioning
confidence: 99%
“…It has recently been reported that deep-learning techniques provide improved workflow for radiation therapy. [14][15][16][17] The outcomes of the contouring tasks performed by deep-learning methods are improved consistency of contouring quality and reduced contouring time. [14][15][16] Also, the automated RTP with deep learning provides shorter planning time with lower error rate.…”
mentioning
confidence: 99%
“…[14][15][16][17] The outcomes of the contouring tasks performed by deep-learning methods are improved consistency of contouring quality and reduced contouring time. [14][15][16] Also, the automated RTP with deep learning provides shorter planning time with lower error rate. 17 In this study, we investigate the feasibility of an automated RTP for WBRT, designed using deep-learning techniques for predicting the multileaf collimator (MLC) shape bypassing the contouring processes.…”
mentioning
confidence: 99%