Giovanni Parrella , Letizia Morelli , Silvia Molinelli , Giuseppe Magro , Lars Glimelius , Jakob Ödén , Mario Ciocca , Sara Imparato , Marco Rotondi , Maria Rosaria Fiore , Ester Orlandi , Guido Baroni , Chiara Paganelli
{"title":"结合先进显微结构模型的碳离子放疗治疗大骶脊索瘤的肿瘤控制概率","authors":"Giovanni Parrella , Letizia Morelli , Silvia Molinelli , Giuseppe Magro , Lars Glimelius , Jakob Ödén , Mario Ciocca , Sara Imparato , Marco Rotondi , Maria Rosaria Fiore , Ester Orlandi , Guido Baroni , Chiara Paganelli","doi":"10.1016/j.ejmp.2025.105038","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>To integrate patient-specific cell count data from diffusion-weighted MRI (DWI) into the linear-quadratic (LQ) Poisson tumor control probability (TCP) model for sacral chordomas (SC) treated with carbon ion radiotherapy (CIRT), aiming to improve local control (LC) and local relapse (LR) prediction.</div></div><div><h3>Materials and Methods</h3><div>We considered data from 37 of the first 50 SC patients consecutively treated at the National Centre for Oncological Hadrontherapy (CNAO, Pavia, Italy). LQ Poisson formalism was revised to integrate either a linear (TCP<sub>LIN</sub>) or logarithmic (TCP<sub>LOG</sub>) dependence on clonogenic cell count, derived from baseline DWI through an optimal match with <em>in</em>-<em>silico</em> simulations. The models were compared with the case of a uniform cell density of 10<sup>7</sup> cells/cm<sup>3</sup>, as widely adopted in the literature. All models were fitted on 27 patients and tested on 10 held-out cases to assess the performance, both in terms of area under the receiver-operator curve (AUC) and considering the statistical differences in TCP between LR and LC.</div></div><div><h3>Results</h3><div>In contrast to the constant cell density model, DWI-based models significantly separated the TCP of LC and LR patients, with TCP<sub>LOG</sub> describing an average TCP of 71.3 % ± 9.56 % for LC patients, compared to 48.9 % ± 9.49 % for LR test cases. AUC values of 0.92 and 0.96 were respectively achieved by TCP<sub>LIN</sub> and TCP<sub>LOG</sub>, compared to 0.88 for constant cell density, on the test set.</div></div><div><h3>Conclusion</h3><div>DWI-based cell count data can significantly improve the performance of TCP models in predicting the probability of LC of SC treated with CIRT.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"136 ","pages":"Article 105038"},"PeriodicalIF":2.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tumor control probability in large sacral chordomas treated with carbon ions radiotherapy integrating advanced microstructural modelling\",\"authors\":\"Giovanni Parrella , Letizia Morelli , Silvia Molinelli , Giuseppe Magro , Lars Glimelius , Jakob Ödén , Mario Ciocca , Sara Imparato , Marco Rotondi , Maria Rosaria Fiore , Ester Orlandi , Guido Baroni , Chiara Paganelli\",\"doi\":\"10.1016/j.ejmp.2025.105038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>To integrate patient-specific cell count data from diffusion-weighted MRI (DWI) into the linear-quadratic (LQ) Poisson tumor control probability (TCP) model for sacral chordomas (SC) treated with carbon ion radiotherapy (CIRT), aiming to improve local control (LC) and local relapse (LR) prediction.</div></div><div><h3>Materials and Methods</h3><div>We considered data from 37 of the first 50 SC patients consecutively treated at the National Centre for Oncological Hadrontherapy (CNAO, Pavia, Italy). LQ Poisson formalism was revised to integrate either a linear (TCP<sub>LIN</sub>) or logarithmic (TCP<sub>LOG</sub>) dependence on clonogenic cell count, derived from baseline DWI through an optimal match with <em>in</em>-<em>silico</em> simulations. The models were compared with the case of a uniform cell density of 10<sup>7</sup> cells/cm<sup>3</sup>, as widely adopted in the literature. All models were fitted on 27 patients and tested on 10 held-out cases to assess the performance, both in terms of area under the receiver-operator curve (AUC) and considering the statistical differences in TCP between LR and LC.</div></div><div><h3>Results</h3><div>In contrast to the constant cell density model, DWI-based models significantly separated the TCP of LC and LR patients, with TCP<sub>LOG</sub> describing an average TCP of 71.3 % ± 9.56 % for LC patients, compared to 48.9 % ± 9.49 % for LR test cases. AUC values of 0.92 and 0.96 were respectively achieved by TCP<sub>LIN</sub> and TCP<sub>LOG</sub>, compared to 0.88 for constant cell density, on the test set.</div></div><div><h3>Conclusion</h3><div>DWI-based cell count data can significantly improve the performance of TCP models in predicting the probability of LC of SC treated with CIRT.</div></div>\",\"PeriodicalId\":56092,\"journal\":{\"name\":\"Physica Medica-European Journal of Medical Physics\",\"volume\":\"136 \",\"pages\":\"Article 105038\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physica Medica-European Journal of Medical Physics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1120179725001486\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica Medica-European Journal of Medical Physics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1120179725001486","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Tumor control probability in large sacral chordomas treated with carbon ions radiotherapy integrating advanced microstructural modelling
Purpose
To integrate patient-specific cell count data from diffusion-weighted MRI (DWI) into the linear-quadratic (LQ) Poisson tumor control probability (TCP) model for sacral chordomas (SC) treated with carbon ion radiotherapy (CIRT), aiming to improve local control (LC) and local relapse (LR) prediction.
Materials and Methods
We considered data from 37 of the first 50 SC patients consecutively treated at the National Centre for Oncological Hadrontherapy (CNAO, Pavia, Italy). LQ Poisson formalism was revised to integrate either a linear (TCPLIN) or logarithmic (TCPLOG) dependence on clonogenic cell count, derived from baseline DWI through an optimal match with in-silico simulations. The models were compared with the case of a uniform cell density of 107 cells/cm3, as widely adopted in the literature. All models were fitted on 27 patients and tested on 10 held-out cases to assess the performance, both in terms of area under the receiver-operator curve (AUC) and considering the statistical differences in TCP between LR and LC.
Results
In contrast to the constant cell density model, DWI-based models significantly separated the TCP of LC and LR patients, with TCPLOG describing an average TCP of 71.3 % ± 9.56 % for LC patients, compared to 48.9 % ± 9.49 % for LR test cases. AUC values of 0.92 and 0.96 were respectively achieved by TCPLIN and TCPLOG, compared to 0.88 for constant cell density, on the test set.
Conclusion
DWI-based cell count data can significantly improve the performance of TCP models in predicting the probability of LC of SC treated with CIRT.
期刊介绍:
Physica Medica, European Journal of Medical Physics, publishing with Elsevier from 2007, provides an international forum for research and reviews on the following main topics:
Medical Imaging
Radiation Therapy
Radiation Protection
Measuring Systems and Signal Processing
Education and training in Medical Physics
Professional issues in Medical Physics.