Cancer Radiotherapie最新文献

{"title":"First experiences with an adaptive pelvic radiotherapy system: Analysis of treatment times and learning curve","authors":"David Benzaquen ,&nbsp;Daniel Taussky ,&nbsp;Vincent Fave ,&nbsp;Jarno Bouveret ,&nbsp;Farid Lamine ,&nbsp;Gladys Letenneur ,&nbsp;Amandine Halley ,&nbsp;Yusuf Solmaz ,&nbsp;Ambroise Champion","doi":"10.1016/j.canrad.2025.104647","DOIUrl":"10.1016/j.canrad.2025.104647","url":null,"abstract":"<div><h3>Purpose</h3><div>The Varian Ethos system allows not only on-treatment-table plan adaptation but also automated contouring with the aid of artificial intelligence. This study evaluates the initial clinical implementation of an adaptive pelvic radiotherapy system, focusing on the treatment times and the associated learning curve.</div></div><div><h3>Material and methods</h3><div>We analyzed the data from 903 consecutive treatments for most urogenital cancers at our center. The treatment time was calculated from the time of the first cone-beam computed tomography scan used for replanning until the end of treatment. To calculate whether treatments were generally shorter over time, we divided the date of the first treatment into 3-months quartiles. Differences between the groups were calculated using <em>t</em>-tests.</div></div><div><h3>Results</h3><div>The mean time from the first cone-beam computed tomography scan to the end of treatment was 25.9<!--> <!-->min (standard deviation: 6.9<!--> <!-->min). Treatment time depended on the number of planning target volumes and treatment of the pelvic lymph nodes. The mean time from cone-beam computed tomography to the end of treatment was 37 % longer if the pelvic lymph nodes were treated and 26 % longer if there were more than two planning target volumes. There was a learning curve: in linear regression analysis, both quartiles of months of treatment (odds ratio [OR]: 1.3, 95 % confidence interval [CI]: 1.8–0.70, <em>P</em> <!-->&lt;<!--> <!-->0.001) and the number of planning target volumes (OR: 3.0, 95 % CI: 2.6–3.4, <em>P</em> <!-->&lt;<!--> <!-->0.001) were predictive of treatment time.</div></div><div><h3>Conclusion</h3><div>Approximately two-thirds of the treatments were delivered within 33<!--> <!-->min. Treatment time was strongly dependent on the number of separate planning target volumes. There was a continuous learning curve.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 4","pages":"Article 104647"},"PeriodicalIF":1.5,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Qualitative evaluation of automatic liver segmentation in computed tomography images for clinical use in radiation therapy","authors":"Dorea Maria Khalal ,&nbsp;Souleyman Slimani ,&nbsp;Zine Eddine Bouraoui ,&nbsp;Hacene Azizi","doi":"10.1016/j.canrad.2025.104648","DOIUrl":"10.1016/j.canrad.2025.104648","url":null,"abstract":"<div><h3>Purpose</h3><div>Segmentation of target volumes and organs at risk on computed tomography (CT) images constitutes an important step in the radiotherapy workflow. Artificial intelligence-based methods have significantly improved organ segmentation in medical images. Automatic segmentations are frequently evaluated using geometric metrics. Before a clinical implementation in the radiotherapy workflow, automatic segmentations must also be evaluated by clinicians. The aim of this study was to investigate the correlation between geometric metrics used for segmentation evaluation and the assessment performed by clinicians.</div></div><div><h3>Materials and Methods</h3><div>In this study, we used the U-Net model to segment the liver in CT images from a publicly available dataset. The model's performance was evaluated using two geometric metrics: the Dice similarity coefficient and the Hausdorff distance. Additionally, a qualitative evaluation was performed by clinicians who reviewed the automatic segmentations to rate their clinical acceptability for use in the radiotherapy workflow. The correlation between the geometric metrics and the clinicians’ evaluations was studied.</div></div><div><h3>Results</h3><div>The results showed that while the Dice coefficient and Hausdorff distance are reliable indicators of segmentation accuracy, they do not always align with clinician segmentation. In some cases, segmentations with high Dice scores still required clinician corrections before clinical use in the radiotherapy workflow.</div></div><div><h3>Conclusion</h3><div>This study highlights the need for more comprehensive evaluation metrics beyond geometric measures to assess the clinical acceptability of artificial intelligence-based segmentation. Although the deep learning model provided promising segmentation results, the present study shows that standardized validation methodologies are crucial for ensuring the clinical viability of automatic segmentation systems.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 4","pages":"Article 104648"},"PeriodicalIF":1.5,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"First case report of radiation-recall myositis following trabectedin in patient with stage IV mesenchymal chondrosarcoma","authors":"Chiara Casale,&nbsp;Marie-Pierre Sunyach,&nbsp;Salvatore Cozzi,&nbsp;Camille Roukoz","doi":"10.1016/j.canrad.2025.104646","DOIUrl":"10.1016/j.canrad.2025.104646","url":null,"abstract":"<div><div>Radiation recall is a rare phenomenon in which inflammation ensues on a previously irradiated tissue after the administration of a precipitating systemic agent. This reaction may appear anytime between weeks to years after radiotherapy, and it can be caused by a variety of drugs (mainly cytotoxic agents). Skin is the most commonly involved organ and despite the poor insight regarding the pathophysiology of this phenomenon, many case reports have been published on radiation recall dermatitis. In one third of cases, however, radiation recall occurs within internal organs or subcutaneous tissues. Radiation recall myositis is a rare example of this, which has most frequently been reported after the administration of gemcitabine in oncologic patients. We report a case of trabectedin-induced radiation recall myositis occurring 5<!--> <!-->months after stereotactic body radiation therapy on a metastatic muscle lesion in a patient with stage IV mesenchymal chondrosarcoma. To our knowledge, this is the first published case of trabectedin-induced radiation recall myositis.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 4","pages":"Article 104646"},"PeriodicalIF":1.5,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for radiotherapy dose prediction: A comprehensive review","authors":"Arezoo Kazemzadeh ,&nbsp;Reza Rasti ,&nbsp;Mohammad Bagher Tavakoli","doi":"10.1016/j.canrad.2025.104630","DOIUrl":"10.1016/j.canrad.2025.104630","url":null,"abstract":"<div><div>Patient outcomes are significantly impacted by the effectiveness and quality of radiation treatment planning. Deep learning, a branch of artificial intelligence, is a potent tool for enhancing and automating dose prediction processes. This article provides a comprehensive and critical analysis of deep learning-based dose prediction methods in radiotherapy, with a focus on convolutional neural networks. A comprehensive search throughout Elsevier Scopus®, Medline, and Web of Science™ literature databases was conducted to locate relevant papers published between 2018 and 2024. The use of deep learning methods for dose prediction is thoroughly examined in this paper. Analysis of these dose prediction approaches provides valuable insights into the potential of this technology to improve radiation treatment planning, particularly in the critical area of automating the dose prediction process. The findings aim to guide future research and facilitate the safe and effective integration of artificial intelligence in clinical workflows.</div></div><div><div>Les résultats des traitements pour les patients sont fortement influencés par l’efficacité et la qualité de la planification du traitement par radiothérapie. L’apprentissage profond, une branche de l’intelligence artificielle, est un outil puissant pour améliorer et automatiser les processus de prédiction des doses. Cet article fournit une analyse complète et critique des méthodes de prédiction des doses basées sur l’apprentissage profond dans le cadre de la radiothérapie, en se concentrant sur les réseaux neuronaux convolutifs. Une recherche approfondie dans les bases de données bibliographiques Elsevier Scopus®, Medline et Web of Science™ a été effectuée pour localiser les articles pertinents publiés entre 2018 et 2024. L’utilisation des méthodes d’apprentissage profond pour la prédiction des doses a été examinée en détail dans cet article. L’analyse de ces approches de prédiction des doses offre des perspectives précieuses sur le potentiel de cette technologie pour améliorer la planification des traitements par irradiation, en particulier dans le domaine critique de l’automatisation du processus de prédiction des doses. Les résultats visent à guider les recherches futures et à faciliter l’intégration sûre et efficace de l’intelligence artificielle dans les flux de travail cliniques.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 4","pages":"Article 104630"},"PeriodicalIF":1.5,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144261911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive analysis of uveal mucosa-associated lymphoid tissue lymphomas: Epidemiological insights and radiotherapy utilization from the Surveillance, Epidemiology and End Results database","authors":"Pierre Loap ,&nbsp;Rémi Dendale ,&nbsp;Youlia Kirova","doi":"10.1016/j.canrad.2025.104629","DOIUrl":"10.1016/j.canrad.2025.104629","url":null,"abstract":"<div><h3>Purpose</h3><div>Uveal mucosa-associated lymphoid tissue lymphomas are rare, indolent ocular tumours affecting the choroid, ciliary body, or iris. Due to their rarity, demographic and treatment data remain limited.</div></div><div><h3>Materials and methods</h3><div>This retrospective study analysed uveal mucosa-associated lymphoid tissue lymphoma cases diagnosed between 2000 and 2021 from the Surveillance, Epidemiology and End Results (SEER) database across 17 registries.</div></div><div><h3>Results</h3><div>Twenty-seven cases of uveal mucosa-associated lymphoid tissue lymphoma were identified from the SEER database (2000–2021), representing 0.12 % of 22,246 extra-nodal MALT lymphomas, with an age-adjusted incidence of 0.014 per 1,000,000 person-years. Median age was 65–69 years, with a near-equal sex ratio and 74 % of patients being Caucasian. Most cases were stage I (74.1 %) at diagnosis. Radiotherapy alone was the most common treatment (55.6 %). At a median follow-up of 69 months, the 5-year overall survival rate was 78.9 %, with no relapses or lymphoma-related deaths, yielding 100 % cancer-specific and relapse-free survival. Radiotherapy proved highly effective, supporting its role as a primary treatment.</div></div><div><h3>Conclusion</h3><div>This is the largest analysis to date, highlighting the excellent prognosis and suggesting potential for radiotherapy dose reduction to lower long-term toxicity.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104629"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiotherapy for adenoid cystic carcinoma of the lacrimal gland: Study on twelve patients","authors":"Sezin Yuce Sari ,&nbsp;Gozde Yazici ,&nbsp;Aysenur Elmali ,&nbsp;Pantea Bayatfard ,&nbsp;Irem Koc ,&nbsp;Hayyam Kiratli ,&nbsp;Mustafa Cengiz","doi":"10.1016/j.canrad.2025.104644","DOIUrl":"10.1016/j.canrad.2025.104644","url":null,"abstract":"<div><h3>Purpose</h3><div>Despite its slow growth pattern, adenoid cystic carcinoma of the lacrimal gland poses challenges due to its high recurrence rate. The rarity of this entity hinders the establishment of prospective studies and a consensus on optimal treatment strategies. Herein, we aim to report the results of patients with adenoid cystic carcinoma of the lacrimal gland treated with hypofractionated stereotactic body radiations or conventionally-fractionated radiations.</div></div><div><h3>Materials and methods</h3><div>This study included patients with non-metastatic adenoid cystic carcinoma of the lacrimal gland treated with a curative-intent from 2006 to 2019. Patient data, tumour characteristics, treatment details, and follow-up information were collected. Recurrence patterns, oncologic outcomes, and toxicity were assessed.</div></div><div><h3>Results</h3><div>We evaluated the data of 12 patients with a median 29<!--> <!-->years of age who received stereotactic body radiotherapy (<em>n</em> <!-->=<!--> <!-->5) or conventionally-fractionated radiotherapy (<em>n</em> <!-->=<!--> <!-->7). After a median follow-up of 98<!--> <!-->months, the overall local control rate was 50 %, with recurrences mostly marginal to the radiotherapy field. Although the 10-year overall survival rate was a promising 92 %, the respective rate for local recurrence-free survival was 37 %, which was significantly lower in patients who received stereotactic body radiotherapy (20 %) compared to patients who had with conventionally-fractionated radiotherapy (72 %). Although not statistically significant, patients in the stereotactic body radiotherapy arm encountered a higher rate of severe late toxicity (80 % versus 17 % in the conventionally-fractionated radiotherapy arm, <em>P</em> <!-->=<!--> <!-->0.07). The overall eye preservation rate was 64 %, all eye-losses due to local recurrence.</div></div><div><h3>Conclusion</h3><div>Our findings raise concerns about using stereotactic body radiotherapy for adenoid cystic carcinoma of the lacrimal gland based on increased rates of severe late toxicity and local recurrence. Conventional radiotherapy techniques should be applied to these patients to successfully control the local tumour with less toxicity.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104644"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Four-dimensional computed tomography scan-based evaluation of intrinsic lung tumour motion and hysteresis using tumour centroid: Implication towards high-precision radiotherapy for lung cancer","authors":"Saikat Das ,&nbsp;Suriya Prakash ,&nbsp;Vaibhav Koutu ,&nbsp;Deepak Rawat ,&nbsp;Sunil Chauhan ,&nbsp;Srivathsan Vasudevan ,&nbsp;Rajesh Pasricha ,&nbsp;Manish Gupta ,&nbsp;Vipin Kharade","doi":"10.1016/j.canrad.2025.104624","DOIUrl":"10.1016/j.canrad.2025.104624","url":null,"abstract":"<div><h3>Purpose</h3><div>Predicting the target position accurately based on an external surrogate with quantifiable correlation is important for high-precision radiation in lung cancer. This study aimed to quantify the amount of movement of the lung tumours and understand the pattern of hysteresis based on four-dimensional (4D) computed tomography (CT) imaging compared to the chest wall movement.</div></div><div><h3>Materials and methods</h3><div>From the radiotherapy four-dimensional computed tomography (4DCT) scan images, a total of 43 lung tumours from 21 patients were contoured, and movement in mediolateral (<em>X</em>), anteroposterior (<em>Z</em>), and superoinferior (<em>Y</em>) directions were calculated based on tumour centroid of the smart breath cine mode of the 4DCT scan. The tumour motion in different phases of the breathing cycle was calculated, and the deformation of the shape was illustrated using a 3D slicer. The nonlinear trajectory of the tumour motion resulting in tumour hysteresis was computed.</div></div><div><h3>Result</h3><div>Tumour motion calculated from the 4DCT images in <em>X</em>, <em>Z</em>, and <em>Y</em> directions were 0.21<!--> <!-->±<!--> <!-->0.22 (range: 0.01–1.20), 0.18<!--> <!-->±<!--> <!-->0.15 (range: 0.01–0.49), 0.77<!--> <!-->±<!--> <!-->0.33 (range: 0.24–1.80) respectively. The mean three-dimensional radial motion vector was 0.85<!--> <!-->±<!--> <!-->0.31 (range: 0.21–1.81). No significant correlation between the magnitude of chest wall movement and three-dimensional radial vector was observed. Hysteresis in <em>XZ</em> plane was calculated to be 0.56<!--> <!-->±<!--> <!-->0.61<!--> <!-->cm² (range: 0.01–3.03). A statistically significant difference in hysteresis was observed between central and peripheral tumours (0.19<!--> <!-->±<!--> <!-->0.31<!--> <!-->cm² vs. 0.94<!--> <!-->±<!--> <!-->0.63<!--> <!-->cm², <em>P</em> <!-->&lt;<!--> <!-->0.01).</div></div><div><h3>Conclusion</h3><div>4DCT-based tumour motion estimation is a feasible method, and the predictability of tumour motion by chest wall movement was not optimal. The movement was more for peripheral tumours compared to centrally located lesions. Location relative to midline was the most critical predictor of hysteresis. Considerable shape deformation in different phases of respiration was observed, and peripheral tumours had more than two times the motion during the breathing cycle compared to the central tumours.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104624"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns of relapse after postoperative radiotherapy in patients with oral cavity cancer and a flap","authors":"Alice Blache ,&nbsp;Justine Lequesne ,&nbsp;François Christy ,&nbsp;Renaud Preudhomme ,&nbsp;Dylan James ,&nbsp;Mélanie Doré ,&nbsp;Romain Mony ,&nbsp;Laure Hily ,&nbsp;Nazim Khalladi ,&nbsp;Sébastien Guihard ,&nbsp;Alessia Di Rito ,&nbsp;Alexandre Coutte ,&nbsp;Arnaud Beddok ,&nbsp;Juliette Thariat","doi":"10.1016/j.canrad.2025.104642","DOIUrl":"10.1016/j.canrad.2025.104642","url":null,"abstract":"<div><h3>Purpose</h3><div>Reconstructive surgery with a flap is standard practice in advanced oral cavity squamous cell carcinoma to restore essential functions. However, these functions may be compromised by postoperative radiotherapy. This study evaluates relapse patterns and treatment-related toxicity in these patients.</div></div><div><h3>Methods and materials</h3><div>A multicentre 2018–2023 study included 247 patients with oral cavity squamous cell carcinoma. Uni- and multivariate analyses estimated the cumulative incidence of locoregional failures, survival rates, and prognostic factors.</div></div><div><h3>Results</h3><div>Among the patients, 74.0 % had pT3-4 tumours, 78.5 % had free flaps, regional pedicled flaps (12.6 %), or local flaps (8.5 %). Flaps were not delineated on planning CTs. Median follow-up for living patient was 36.8<!--> <!-->months. Fifty-eight patients (23.0 %) had involved soft-tissue margins; no correlation was found between margin involvement, stage, or flap type. Forty patients experienced local relapse within a median of 8.23<!--> <!-->months. Local relapse rates were higher in patients with involved (28.6 %) versus clear margins (9.3 %, <em>P</em> <!-->&lt;<!--> <!-->0.004). Two-year locoregional relapse and survival rates were 17.8 %, and 74.3 %, respectively. Performance status greater than 1, locoregional relapse, and distant relapse were associated with poorer survival. Coregistration of planning-relapse CTs is challenging due to flap changes, limiting relapse pattern analysis. Subgroup analysis of locoregional relapses (14 out of 53) at the main contributing centre revealed that five relapses occurred at the native tissue-flap junction, with minor flap involvement in two cases and no intraflap failure. All other relapses occurred outside the flap.</div></div><div><h3>Conclusions</h3><div>Involved margin rates correlating with increased local relapse risk and were not different according flap type. Further investigation into flap segmentation and planning optimization is needed. The OPTIFLAP trial (<span><span>NCT06798922</span><svg><path></path></svg></span>, PHRC2024) aims to determine whether radiotherapy can be optimized to spare flaps without increasing the risk of locoregional failure.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104642"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Specific radiosensitivity of brain structures (areas or regions) and cognitive impairment after focal or whole brain radiotherapy: A review","authors":"Emmanuel Mesny ,&nbsp;Julian Jacob ,&nbsp;Georges Noël ,&nbsp;Marie-Odile Bernier ,&nbsp;Damien Ricard","doi":"10.1016/j.canrad.2025.104625","DOIUrl":"10.1016/j.canrad.2025.104625","url":null,"abstract":"<div><div>Delayed neurocognitive impairment is observed following encephalic radiotherapy, including brain parts (areas), leading to a substantial deterioration of the quality of life. These delayed radiotherapy side effects are variable in terms of intensity of symptoms and time of occurrence, characterized by minor-to-severe cognitive deficits, such as attention or memory disorders and/or dysexecutive syndrome. However, the precise mechanisms leading to these cognitive disorders remain mostly unknown. Various tissue alterations have been reported after brain radiotherapy, in specific brain structures as the hippocampus, the cerebral white matter or the cerebral cortex. Sparing these structures during brain radiotherapy may be a potential approach to limit the development of late cognitive impairment; however, few dose constraints have been published regarding brain areas (regions) involved in cognitive functions. The main purposes of this literature review are to report the pathophysiological process leading to the radiation-induced cognitive impairment, to describe the tolerance and radiological modifications induced by radiation of specific healthy cerebral tissues, to better understand their radiosensitivity and to describe potential improvements.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104625"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pulmonary extramedullary haematopoiesis managed by radiation therapy: A case report and review of literature","authors":"Alexander Bennassi,&nbsp;Kamel Debbi,&nbsp;Fatima Zahra Bellefkih,&nbsp;Gonzalo De Luna,&nbsp;Gabriele Coraggio,&nbsp;Yazid Belkacémi","doi":"10.1016/j.canrad.2025.104628","DOIUrl":"10.1016/j.canrad.2025.104628","url":null,"abstract":"<div><div>Extramedullary haematopoiesis is a very rare non-oncologic entity, occurring in multiple blood disorders. It refers to haematopoiesis occurring outside the bone marrow. Here we report a patient with an extramedullary haematopoiesis lung mass managed by radiation therapy delivering 20<!--> <!-->Gy in ten fractions. To the best of our knowledge, this is the first case managed with this scheme. A 54-year-old man was referred for acute hypercapnic respiratory failure. A computed tomography scan (CT-scan) had demonstrated 16 years ago bilateral pulmonary masses. The patient was diagnosed with extramedullary haematopoiesis based on concordant haematological history and typical paravertebral masses. The patient had a previous history of clear cell carcinoma of the right kidney, managed by surgery 5 years ago (pT1aN0M0 on histologic examination). The acute hypercapnic respiratory failure was suggested to be secondary to his pulmonary extramedullary haematopoiesis lesions. After multidisciplinary board discussion, radiation therapy was decided to treat the right extramedullary haematopoiesis lung mass, delivering 20<!--> <!-->Gy in ten fractions. At 3 months, the patient experienced excellent tolerance with a significant improvement in respiratory symptoms. Tramadol and non-invasive ventilation could be stopped. CT-imaging at 6 months was consistent with partial response and decrease in arteriovenous circulation within the right mass. At 12-months follow-up, patient presented with no thoracic symptoms. Pulmonary extramedullary haematopoiesis is a very rare entity. Its diagnosis should not be underestimated. Radiation therapy delivering 20<!--> <!-->Gy in ten fractions is a reasonable and safe therapeutic option.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"29 3","pages":"Article 104628"},"PeriodicalIF":1.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}