Pub Date : 2024-07-30DOI: 10.1186/s40644-024-00738-z
Josephine Situ, Poppy Buissink, Annie Mu, David K V Chung, Rob Finnegan, Thiranja P Babarenda Gamage, Tharanga D Jayathungage Don, Cameron Walker, Hayley M Reynolds
Background: The identification and assessment of sentinel lymph nodes (SLNs) in breast cancer is important for optimised patient management. The aim of this study was to develop an interactive 3D breast SLN atlas and to perform statistical analyses of lymphatic drainage patterns and tumour prevalence.
Methods: A total of 861 early-stage breast cancer patients who underwent preoperative lymphoscintigraphy and SPECT/CT were included. Lymphatic drainage and tumour prevalence statistics were computed using Bayesian inference, non-parametric bootstrapping, and regression techniques. Image registration of SPECT/CT to a reference patient CT was carried out on 350 patients, and SLN positions transformed relative to the reference CT. The reference CT was segmented to visualise bones and muscles, and SLN distributions compared with the European Society for Therapeutic Radiology and Oncology (ESTRO) clinical target volumes (CTVs). The SLN atlas and statistical analyses were integrated into a graphical user interface (GUI).
Results: Direct lymphatic drainage to the axilla level I (anterior) node field was most common (77.2%), followed by the internal mammary node field (30.4%). Tumour prevalence was highest in the upper outer breast quadrant (22.9%) followed by the retroareolar region (12.8%). The 3D atlas had 765 SLNs from 335 patients, with 33.3-66.7% of axillary SLNs and 25.4% of internal mammary SLNs covered by ESTRO CTVs.
Conclusion: The interactive 3D atlas effectively displays breast SLN distribution and statistics for a large patient cohort. The atlas is freely available to download and is a valuable educational resource that could be used in future to guide treatment.
{"title":"An interactive 3D atlas of sentinel lymph nodes in breast cancer developed using SPECT/CT.","authors":"Josephine Situ, Poppy Buissink, Annie Mu, David K V Chung, Rob Finnegan, Thiranja P Babarenda Gamage, Tharanga D Jayathungage Don, Cameron Walker, Hayley M Reynolds","doi":"10.1186/s40644-024-00738-z","DOIUrl":"10.1186/s40644-024-00738-z","url":null,"abstract":"<p><strong>Background: </strong>The identification and assessment of sentinel lymph nodes (SLNs) in breast cancer is important for optimised patient management. The aim of this study was to develop an interactive 3D breast SLN atlas and to perform statistical analyses of lymphatic drainage patterns and tumour prevalence.</p><p><strong>Methods: </strong>A total of 861 early-stage breast cancer patients who underwent preoperative lymphoscintigraphy and SPECT/CT were included. Lymphatic drainage and tumour prevalence statistics were computed using Bayesian inference, non-parametric bootstrapping, and regression techniques. Image registration of SPECT/CT to a reference patient CT was carried out on 350 patients, and SLN positions transformed relative to the reference CT. The reference CT was segmented to visualise bones and muscles, and SLN distributions compared with the European Society for Therapeutic Radiology and Oncology (ESTRO) clinical target volumes (CTVs). The SLN atlas and statistical analyses were integrated into a graphical user interface (GUI).</p><p><strong>Results: </strong>Direct lymphatic drainage to the axilla level I (anterior) node field was most common (77.2%), followed by the internal mammary node field (30.4%). Tumour prevalence was highest in the upper outer breast quadrant (22.9%) followed by the retroareolar region (12.8%). The 3D atlas had 765 SLNs from 335 patients, with 33.3-66.7% of axillary SLNs and 25.4% of internal mammary SLNs covered by ESTRO CTVs.</p><p><strong>Conclusion: </strong>The interactive 3D atlas effectively displays breast SLN distribution and statistics for a large patient cohort. The atlas is freely available to download and is a valuable educational resource that could be used in future to guide treatment.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"97"},"PeriodicalIF":3.5,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11289966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-node-metastasis (TNM) staging to predict overall survival (OS) in patients with GC.
Methods: We reviewed the clinical information of a total of 327 patients with pathological confirmation of GC undergoing 18 F-fluorodeoxyglucose (18 F-FDG) PET scans. The patients were randomly classified into training (n = 229) and validation (n = 98) cohorts. We extracted 171 PET radiomics features from the PET images and determined the PET radiomics scores (RS) using the least absolute shrinkage and selection operator (LASSO) and random survival forest (RSF). A radiomics model, including PET RS and clinical TNM staging, was constructed to predict the OS of patients with GC. This model was evaluated for discrimination, calibration, and clinical usefulness.
Results: On multivariate COX regression analysis, the difference between age, carcinoembryonic antigen (CEA), clinical TNM, and PET RS in GC patients was statistically significant (p < 0.05). A radiomics model was developed based on the results of COX regression. The model had the Harrell's concordance index (C-index) of 0.817 in the training cohort and 0.707 in the validation cohort and performed better than a single clinical model and a model with clinical features combined with clinical TNM staging. Further analyses showed higher PET RS in patients who were older (p < 0.001) and those who had elevated CEA (p < 0.001) and higher clinical TNM (p < 0.001). At different clinical TNM stages, a higher PET RS was associated with a worse survival prognosis.
Conclusions: Radiomics models based on PET RS, clinical TNM, and clinical features may provide new tools for predicting OS in patients with GC.
背景:胃癌(GC)患者的生存预后往往影响医生对其后续治疗的选择。本研究旨在开发一种基于正电子发射断层扫描(PET)的放射组学模型,结合临床肿瘤-结节-转移(TNM)分期预测胃癌患者的总生存期(OS):我们回顾了327例接受18 F-氟脱氧葡萄糖(18 F-FDG PET)扫描的病理确诊为GC患者的临床信息。患者被随机分为训练组(229 人)和验证组(98 人)。我们从 PET 图像中提取了 171 个 PET 放射组学特征,并使用最小绝对收缩和选择算子(LASSO)和随机生存森林(RSF)确定了 PET 放射组学评分(RS)。建立的放射组学模型包括 PET RS 和临床 TNM 分期,用于预测 GC 患者的 OS。对该模型的区分度、校准和临床实用性进行了评估:结果:在多变量 COX 回归分析中,GC 患者的年龄、癌胚抗原(CEA)、临床 TNM 分期和 PET RS 之间的差异具有统计学意义(p 结论:PET RS 和临床 TNM 分期在预测 GC 患者的 OS 方面具有重要作用:基于 PET RS、临床 TNM 和临床特征的放射组学模型可为预测 GC 患者的 OS 提供新的工具。
{"title":"Development and validation of a machine learning-based <sup>18</sup>F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival.","authors":"Huaiqing Zhi, Yilan Xiang, Chenbin Chen, Weiteng Zhang, Jie Lin, Zekan Gao, Qingzheng Shen, Jiancan Shao, Xinxin Yang, Yunjun Yang, Xiaodong Chen, Jingwei Zheng, Mingdong Lu, Bujian Pan, Qiantong Dong, Xian Shen, Chunxue Ma","doi":"10.1186/s40644-024-00741-4","DOIUrl":"10.1186/s40644-024-00741-4","url":null,"abstract":"<p><strong>Background: </strong>Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-node-metastasis (TNM) staging to predict overall survival (OS) in patients with GC.</p><p><strong>Methods: </strong>We reviewed the clinical information of a total of 327 patients with pathological confirmation of GC undergoing 18 F-fluorodeoxyglucose (18 F-FDG) PET scans. The patients were randomly classified into training (n = 229) and validation (n = 98) cohorts. We extracted 171 PET radiomics features from the PET images and determined the PET radiomics scores (RS) using the least absolute shrinkage and selection operator (LASSO) and random survival forest (RSF). A radiomics model, including PET RS and clinical TNM staging, was constructed to predict the OS of patients with GC. This model was evaluated for discrimination, calibration, and clinical usefulness.</p><p><strong>Results: </strong>On multivariate COX regression analysis, the difference between age, carcinoembryonic antigen (CEA), clinical TNM, and PET RS in GC patients was statistically significant (p < 0.05). A radiomics model was developed based on the results of COX regression. The model had the Harrell's concordance index (C-index) of 0.817 in the training cohort and 0.707 in the validation cohort and performed better than a single clinical model and a model with clinical features combined with clinical TNM staging. Further analyses showed higher PET RS in patients who were older (p < 0.001) and those who had elevated CEA (p < 0.001) and higher clinical TNM (p < 0.001). At different clinical TNM stages, a higher PET RS was associated with a worse survival prognosis.</p><p><strong>Conclusions: </strong>Radiomics models based on PET RS, clinical TNM, and clinical features may provide new tools for predicting OS in patients with GC.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"99"},"PeriodicalIF":3.5,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11290137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.1186/s40644-024-00742-3
Ben Furman, Tal Falick Michaeli, Robert Den, Simona Ben Haim, Aron Popovtzer, Marc Wygoda, Philip Blumenfeld
Introduction: Prostate Specific Membrane Antigen (PSMA) imaging with Positron Emission Tomography (PET) plays a crucial role in prostate cancer management. However, there is a lack of comprehensive data on how PSMA PET/CT (Computed Tomography) influences radiotherapeutic decisions, particularly in node-positive prostate cancer cases. This study aims to address this gap by evaluating two primary objectives: (1) Mapping the regional and non-regional lymph nodes (LNs) up to the aortic bifurcation and their distribution using conventional methods with CT compared to PSMA PET/CT, and (2) assessing the impact of PSMA PET/CT findings on radiotherapeutic decisions.
Methods: A retrospective analysis of 95 node-positive prostate cancer patients who underwent both CT and PSMA PET/CT imaging prior to primary radiotherapy and androgen deprivation therapy (ADT) was conducted. The analysis focused on identifying LNs in various regions including the common iliac, external iliac, internal iliac, obturator, presacral, mesorectal, inguinal, and other stations. Treatment plans were reviewed for modifications based on PSMA PET/CT findings, and statistical analysis was performed to identify predictors for exclusive nodal positivity on PSMA PET/CT scans.
Results: PSMA PET/CT identified additional positive nodes in 48% of cases, resulting in a staging shift from N0 to N1 in 29% of patients. The most frequent metastatic LNs were located in the external iliac (76 LNs; 34%), internal iliac (43 LNs; 19%), and common iliac (35 LNs; 15%) stations. In patients with nodes only detected on PSMA PET the most common nodes were in the external iliac (27, 40%), internal iliac (13, 19%), obturator (11, 15%) stations. Within the subgroup of 28 patients exclusively demonstrating PSMA PET-detected nodes, changes in radiotherapy treatment fields were implemented in 5 cases (18%), and a dose boost was applied for 23 patients (83%). However, no discernible predictors for exclusive nodal positivity on PSMA PET/CT scans emerged from the analysis.
Discussion: The study underscores the pivotal role of PSMA PET/CT compared to CT alone in accurately staging node-positive prostate cancer and guiding personalized radiotherapy strategies. The routine integration of PSMA PET/CT into diagnostic protocols is advocated to optimize treatment precision and improve patient outcomes.
{"title":"Pelvic lymph node mapping in prostate cancer: examining the impact of PSMA PET/CT on radiotherapy decision-making in patients with node-positive disease.","authors":"Ben Furman, Tal Falick Michaeli, Robert Den, Simona Ben Haim, Aron Popovtzer, Marc Wygoda, Philip Blumenfeld","doi":"10.1186/s40644-024-00742-3","DOIUrl":"10.1186/s40644-024-00742-3","url":null,"abstract":"<p><strong>Introduction: </strong>Prostate Specific Membrane Antigen (PSMA) imaging with Positron Emission Tomography (PET) plays a crucial role in prostate cancer management. However, there is a lack of comprehensive data on how PSMA PET/CT (Computed Tomography) influences radiotherapeutic decisions, particularly in node-positive prostate cancer cases. This study aims to address this gap by evaluating two primary objectives: (1) Mapping the regional and non-regional lymph nodes (LNs) up to the aortic bifurcation and their distribution using conventional methods with CT compared to PSMA PET/CT, and (2) assessing the impact of PSMA PET/CT findings on radiotherapeutic decisions.</p><p><strong>Methods: </strong>A retrospective analysis of 95 node-positive prostate cancer patients who underwent both CT and PSMA PET/CT imaging prior to primary radiotherapy and androgen deprivation therapy (ADT) was conducted. The analysis focused on identifying LNs in various regions including the common iliac, external iliac, internal iliac, obturator, presacral, mesorectal, inguinal, and other stations. Treatment plans were reviewed for modifications based on PSMA PET/CT findings, and statistical analysis was performed to identify predictors for exclusive nodal positivity on PSMA PET/CT scans.</p><p><strong>Results: </strong>PSMA PET/CT identified additional positive nodes in 48% of cases, resulting in a staging shift from N0 to N1 in 29% of patients. The most frequent metastatic LNs were located in the external iliac (76 LNs; 34%), internal iliac (43 LNs; 19%), and common iliac (35 LNs; 15%) stations. In patients with nodes only detected on PSMA PET the most common nodes were in the external iliac (27, 40%), internal iliac (13, 19%), obturator (11, 15%) stations. Within the subgroup of 28 patients exclusively demonstrating PSMA PET-detected nodes, changes in radiotherapy treatment fields were implemented in 5 cases (18%), and a dose boost was applied for 23 patients (83%). However, no discernible predictors for exclusive nodal positivity on PSMA PET/CT scans emerged from the analysis.</p><p><strong>Discussion: </strong>The study underscores the pivotal role of PSMA PET/CT compared to CT alone in accurately staging node-positive prostate cancer and guiding personalized radiotherapy strategies. The routine integration of PSMA PET/CT into diagnostic protocols is advocated to optimize treatment precision and improve patient outcomes.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"96"},"PeriodicalIF":3.5,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11285572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141792020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18DOI: 10.1186/s40644-024-00736-1
Carole Brunaud, Samuel Valable, Gwenn Ropars, Fatima-Azzahra Dwiri, Mikaël Naveau, Jérôme Toutain, Myriam Bernaudin, Thomas Freret, Marianne Léger, Omar Touzani, Elodie A Pérès
Background: Radiotherapy is a major therapeutic approach in patients with brain tumors. However, it leads to cognitive impairments. To improve the management of radiation-induced brain sequalae, deformation-based morphometry (DBM) could be relevant. Here, we analyzed the significance of DBM using Jacobian determinants (JD) obtained by non-linear registration of MRI images to detect local vulnerability of healthy cerebral tissue in an animal model of brain irradiation.
Methods: Rats were exposed to fractionated whole-brain irradiation (WBI, 30 Gy). A multiparametric MRI (anatomical, diffusion and vascular) study was conducted longitudinally from 1 month up to 6 months after WBI. From the registration of MRI images, macroscopic changes were analyzed by DBM and microscopic changes at the cellular and vascular levels were evaluated by quantification of cerebral blood volume (CBV) and diffusion metrics including mean diffusivity (MD). Voxel-wise comparisons were performed on the entire brain and in specific brain areas identified by DBM. Immunohistology analyses were undertaken to visualize the vessels and astrocytes.
Results: DBM analysis evidenced time-course of local macrostructural changes; some of which were transient and some were long lasting after WBI. DBM revealed two vulnerable brain areas, namely the corpus callosum and the cortex. DBM changes were spatially associated to microstructural alterations as revealed by both diffusion metrics and CBV changes, and confirmed by immunohistology analyses. Finally, matrix correlations demonstrated correlations between JD/MD in the early phase after WBI and JD/CBV in the late phase both in the corpus callosum and the cortex.
Conclusions: Brain irradiation induces local macrostructural changes detected by DBM which could be relevant to identify brain structures prone to radiation-induced tissue changes. The translation of these data in patients could represent an added value in imaging studies on brain radiotoxicity.
{"title":"Deformation-based morphometry: a sensitive imaging approach to detect radiation-induced brain injury?","authors":"Carole Brunaud, Samuel Valable, Gwenn Ropars, Fatima-Azzahra Dwiri, Mikaël Naveau, Jérôme Toutain, Myriam Bernaudin, Thomas Freret, Marianne Léger, Omar Touzani, Elodie A Pérès","doi":"10.1186/s40644-024-00736-1","DOIUrl":"10.1186/s40644-024-00736-1","url":null,"abstract":"<p><strong>Background: </strong>Radiotherapy is a major therapeutic approach in patients with brain tumors. However, it leads to cognitive impairments. To improve the management of radiation-induced brain sequalae, deformation-based morphometry (DBM) could be relevant. Here, we analyzed the significance of DBM using Jacobian determinants (JD) obtained by non-linear registration of MRI images to detect local vulnerability of healthy cerebral tissue in an animal model of brain irradiation.</p><p><strong>Methods: </strong>Rats were exposed to fractionated whole-brain irradiation (WBI, 30 Gy). A multiparametric MRI (anatomical, diffusion and vascular) study was conducted longitudinally from 1 month up to 6 months after WBI. From the registration of MRI images, macroscopic changes were analyzed by DBM and microscopic changes at the cellular and vascular levels were evaluated by quantification of cerebral blood volume (CBV) and diffusion metrics including mean diffusivity (MD). Voxel-wise comparisons were performed on the entire brain and in specific brain areas identified by DBM. Immunohistology analyses were undertaken to visualize the vessels and astrocytes.</p><p><strong>Results: </strong>DBM analysis evidenced time-course of local macrostructural changes; some of which were transient and some were long lasting after WBI. DBM revealed two vulnerable brain areas, namely the corpus callosum and the cortex. DBM changes were spatially associated to microstructural alterations as revealed by both diffusion metrics and CBV changes, and confirmed by immunohistology analyses. Finally, matrix correlations demonstrated correlations between JD/MD in the early phase after WBI and JD/CBV in the late phase both in the corpus callosum and the cortex.</p><p><strong>Conclusions: </strong>Brain irradiation induces local macrostructural changes detected by DBM which could be relevant to identify brain structures prone to radiation-induced tissue changes. The translation of these data in patients could represent an added value in imaging studies on brain radiotoxicity.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"95"},"PeriodicalIF":3.5,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11256482/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141723122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.1186/s40644-024-00739-y
Lei Ni, Qihui Wang, Yilong Wang, Yaqi Du, Zhenggang Sun, Guoguang Fan, Ce Li, Guan Wang
Background: To explore the pulmonary-vascular-stump filling-defect on CT and investigate its association with cancer progression.
Methods: Records in our institutional database from 2018 to 2022 were retrospectively analyzed to identify filling-defects in the pulmonary-vascular-stump after lung cancer resection and collect imaging and clinical data of patients.
Results: Among the 1714 patients analyzed, 95 cases of filling-defects in the vascular stump after lung cancer resection were identified. After excluding lost-to-follow-up cases, a total of 77 cases were included in the final study. Morphologically, the filling-defects were dichotomized as 46 convex-shape and 31 concave-shape cases. Concave defects exhibited a higher incidence of increase compared to convex defects (51.7% v. 9.4%, P = 0.001). Among 61 filling defects in the pulmonary arterial stump, four (6.5%) increasing concave defects showed the nuclide concentration on PET and extravascular extension. The progression-free survival (PFS) time differed significantly among the concave, convex, and non-filling-defect groups (log-rank P < 0.0001), with concave defects having the shortest survival time. Multivariate Cox proportional hazards analysis indicated that the shape of filling-defects independently predicted PFS in early onset on CT (HR: 0.46; 95% CI: 0.39-1.99; P = 0.04). In follow-ups, the growth of filling-effects was an independent predictor of PFS (HR: 0.26; 95% CI: 0.11-0.65; P = 0.004).
Conclusions: Certain filling-defects in the pulmonary-arterial-stump post lung tumor resection exhibit malignant growth. In the early onset of filling-defects on CT, the concave-shape independently predicted cancer-progression, while during the subsequent follow-up, the growth of filling-defects could be used independently to forecast cancer-progression.
{"title":"The pulmonary-vascular-stump filling defect on CT post lung tumor resection: a predictor of cancer progression.","authors":"Lei Ni, Qihui Wang, Yilong Wang, Yaqi Du, Zhenggang Sun, Guoguang Fan, Ce Li, Guan Wang","doi":"10.1186/s40644-024-00739-y","DOIUrl":"10.1186/s40644-024-00739-y","url":null,"abstract":"<p><strong>Background: </strong>To explore the pulmonary-vascular-stump filling-defect on CT and investigate its association with cancer progression.</p><p><strong>Methods: </strong>Records in our institutional database from 2018 to 2022 were retrospectively analyzed to identify filling-defects in the pulmonary-vascular-stump after lung cancer resection and collect imaging and clinical data of patients.</p><p><strong>Results: </strong>Among the 1714 patients analyzed, 95 cases of filling-defects in the vascular stump after lung cancer resection were identified. After excluding lost-to-follow-up cases, a total of 77 cases were included in the final study. Morphologically, the filling-defects were dichotomized as 46 convex-shape and 31 concave-shape cases. Concave defects exhibited a higher incidence of increase compared to convex defects (51.7% v. 9.4%, P = 0.001). Among 61 filling defects in the pulmonary arterial stump, four (6.5%) increasing concave defects showed the nuclide concentration on PET and extravascular extension. The progression-free survival (PFS) time differed significantly among the concave, convex, and non-filling-defect groups (log-rank P < 0.0001), with concave defects having the shortest survival time. Multivariate Cox proportional hazards analysis indicated that the shape of filling-defects independently predicted PFS in early onset on CT (HR: 0.46; 95% CI: 0.39-1.99; P = 0.04). In follow-ups, the growth of filling-effects was an independent predictor of PFS (HR: 0.26; 95% CI: 0.11-0.65; P = 0.004).</p><p><strong>Conclusions: </strong>Certain filling-defects in the pulmonary-arterial-stump post lung tumor resection exhibit malignant growth. In the early onset of filling-defects on CT, the concave-shape independently predicted cancer-progression, while during the subsequent follow-up, the growth of filling-defects could be used independently to forecast cancer-progression.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"94"},"PeriodicalIF":3.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11250966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141626092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1186/s40644-024-00725-4
Zongbao Li, Yifan Zhong, Yan Lv, Jianzhong Zheng, Yu Hu, Yanyan Yang, Yunxi Li, Meng Sun, Siqian Liu, Yan Guo, Mengchao Zhang, Le Zhou
<p>Following publication of the original article [1], we were notified that the correct affiliation of co-corresponding author Le Zhou is the Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130,000, China, rather than the Department of Radiology.</p><p>The original article has been corrected.</p><ol data-track-component="outbound reference" data-track-context="references section"><li data-counter="1."><p>Li et al. Cancer Imaging (2024) 24:62. https://doi.org/10.1186/s40644-024-00690-y.</p></li></ol><p>Download references<svg aria-hidden="true" focusable="false" height="16" role="img" width="16"><use xlink:href="#icon-eds-i-download-medium" xmlns:xlink="http://www.w3.org/1999/xlink"></use></svg></p><h3>Authors and Affiliations</h3><ol><li><p>Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China</p><p>Zongbao Li, Yan Lv, Yanyan Yang, Yunxi Li, Meng Sun, Siqian Liu & Mengchao Zhang</p></li><li><p>Department of Radiology, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 611130, China</p><p>Zongbao Li</p></li><li><p>Department of Radiology, The People’s Hospital of Bao’an, Shenzhen University, Shenzhen, 518101, China</p><p>Jianzhong Zheng & Yu Hu</p></li><li><p>Life Sciences, GE Healthcare, Shenyang, 110000, China</p><p>Yan Guo</p></li><li><p>Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130000, China</p><p>Yifan Zhong & Le Zhou</p></li></ol><span>Authors</span><ol><li><span>Zongbao Li</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yifan Zhong</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yan Lv</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Jianzhong Zheng</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yu Hu</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yanyan Yang</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yunxi Li</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Meng Sun</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Siqian Liu</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yan Guo</span>View author publications<p>You can also search for this author in
原文[1]发表后,我们接到通知,共同通讯作者周乐的正确单位是吉林大学中日联谊医院甲状腺外科,长春,130000,中国,而不是放射科。原文已更正。Li et al. Cancer Imaging (2024) 24:62. https://doi.org/10.1186/s40644-024-00690-y.下载参考文献作者及单位吉林大学中日联谊医院放射科,中国长春,130000李宗宝,吕岩,杨艳艳,李云喜,孙萌,刘思倩 &;张孟超 成都中医药大学附属第五人民医院放射科,成都,611130 李宗宝 深圳大学附属宝安人民医院放射科,深圳,518101 郑建中 &;Yu HuLife Sciences, GE Healthcare, Shenyang, 110000, ChinaYan GuoDepartment of Thyroid Surgery, China China Yifan Zhong &;Le ZhouAuthors李宗宝View Author publications您也可以在PubMed Google Scholar中搜索该作者钟一帆View Author publications您也可以在PubMed Google Scholar中搜索该作者吕燕View Author publications您也可以在PubMed Google Scholar中搜索该作者郑建中Jianzhong郑查看作者发表的作品您也可以在 PubMed Google Scholar中搜索该作者胡钰查看作者发表的作品您也可以在 PubMed Google Scholar中搜索该作者杨艳艳查看作者发表的作品您也可以在 PubMed Google Scholar中搜索该作者李云喜查看作者发表的作品您也可以在 PubMed Google Scholar中搜索该作者李云喜查看作者发表的作品发表文章您也可以在 PubMed Google Scholar中搜索该作者Meng Sun查看作者发表文章您也可以在 PubMed Google Scholar中搜索该作者Siqian Liu查看作者发表文章您也可以在 PubMed Google Scholar中搜索该作者Yan Guo查看作者发表文章您也可以在 PubMed Google Scholar中搜索该作者您也可以在 PubMed Google Scholar中搜索该作者张孟超查看作者发表的论文您也可以在 PubMed Google Scholar中搜索该作者周乐查看作者发表的论文您也可以在 PubMed Google Scholar中搜索该作者通讯作者张孟超或周乐。出版者注Springer Nature对已出版地图中的管辖权主张和机构隶属关系保持中立。原文的在线版本可在以下网址找到 https://doi.org/10.1186/s40644-024-00690-y.Open Access 本文采用知识共享署名 4.0 国际许可协议进行许可,该协议允许以任何媒介或格式使用、共享、改编、分发和复制,只要您适当注明原作者和来源,提供知识共享许可协议的链接,并说明是否进行了修改。本文中的图片或其他第三方材料均包含在文章的知识共享许可协议中,除非在材料的署名栏中另有说明。如果材料未包含在文章的知识共享许可协议中,且您打算使用的材料不符合法律规定或超出许可使用范围,则您需要直接从版权所有者处获得许可。要查看该许可的副本,请访问 http://creativecommons.org/licenses/by/4.0/。除非在数据的信用行中另有说明,否则知识共享公共领域专用免责声明(http://creativecommons.org/publicdomain/zero/1.0/)适用于本文提供的数据。转载与许可引用本文Li, Z., Zhong, Y., Lv, Y. et al. Correction:基于CT的放射组学分析预测甲状腺乳头状癌的CN0状态:一项双中心研究。Cancer Imaging 24, 92 (2024). https://doi.org/10.1186/s40644-024-00725-4Download citationPublished: 11 July 2024DOI: https://doi.org/10.1186/s40644-024-00725-4Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative
{"title":"Correction: A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study","authors":"Zongbao Li, Yifan Zhong, Yan Lv, Jianzhong Zheng, Yu Hu, Yanyan Yang, Yunxi Li, Meng Sun, Siqian Liu, Yan Guo, Mengchao Zhang, Le Zhou","doi":"10.1186/s40644-024-00725-4","DOIUrl":"https://doi.org/10.1186/s40644-024-00725-4","url":null,"abstract":"<p>Following publication of the original article [1], we were notified that the correct affiliation of co-corresponding author Le Zhou is the Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130,000, China, rather than the Department of Radiology.</p><p>The original article has been corrected.</p><ol data-track-component=\"outbound reference\" data-track-context=\"references section\"><li data-counter=\"1.\"><p>Li et al. Cancer Imaging (2024) 24:62. https://doi.org/10.1186/s40644-024-00690-y.</p></li></ol><p>Download references<svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></p><h3>Authors and Affiliations</h3><ol><li><p>Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China</p><p>Zongbao Li, Yan Lv, Yanyan Yang, Yunxi Li, Meng Sun, Siqian Liu & Mengchao Zhang</p></li><li><p>Department of Radiology, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 611130, China</p><p>Zongbao Li</p></li><li><p>Department of Radiology, The People’s Hospital of Bao’an, Shenzhen University, Shenzhen, 518101, China</p><p>Jianzhong Zheng & Yu Hu</p></li><li><p>Life Sciences, GE Healthcare, Shenyang, 110000, China</p><p>Yan Guo</p></li><li><p>Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130000, China</p><p>Yifan Zhong & Le Zhou</p></li></ol><span>Authors</span><ol><li><span>Zongbao Li</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yifan Zhong</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yan Lv</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Jianzhong Zheng</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yu Hu</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yanyan Yang</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yunxi Li</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Meng Sun</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Siqian Liu</span>View author publications<p>You can also search for this author in <span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Yan Guo</span>View author publications<p>You can also search for this author in ","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"12 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1186/s40644-024-00740-5
Bastien Jamet, Hatem Necib, Thomas Carlier, Eric Frampas, Juliette Bazin, Paul-Henri Desfontis, Aurélien Monnet, Caroline Bodet-Milin, Philippe Moreau, Cyrille Touzeau, Francoise Kraeber-Bodere
Background: Dynamic contrast-enhanced-MRI (DCE-MRI) is able to study bone marrow angiogenesis in patients with multiple myeloma (MM) and asymptomatic precursor diseases but its role in the management of MM has not yet been established. The aims of this prospective study was to compare DCE-MRI-based parameters between all monoclonal plasma cell disease stages in order to find out discriminatory parameters and to seek correlations with other diffusion-weighted MRI and positron emission tomography (PET)-based biomarkers in a hybrid simultaneous whole-body-2-[18F]fluorodeoxyglucose (FDG)-PET/MRI (WB-2-[18F]FDG-PET/MRI) imaging approach.
Methods: Patients with newly diagnosed Monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM) or symptomatic MM according to international myeloma working group and underwent WB-2-[18F]FDG-PET/MRI imaging including bone marrow DCE sequences at the Nantes University Hospital were prospectively enrolled in this study before receiving treatment.
Results: One hundred and sixty-seven patients (N = 167, mean age: 64 years ± 11 [Standard deviation], 66 males) were considered for the analysis. DCE-MRI-based Peak Enhancement Intensity (PEI), Time to PEI (TPEI) and their maximum intensity time ratio (MITR: PEI/TPEI) values were significantly different between the different monoclonal plasma cell disease stages, PEI values increasing and TPEI values decreasing progressively along the spectrum of plasma cell disorders, from MGUS stage to symptomatic multiple myeloma. PEI values were significantly higher in patients with diffuse bone marrow involvement (either in PET or in MRI images) than in those without diffuse bone marrow involvement, unlike TPEI values. PEI and TPEI values were not significantly different between patients with or without focal bone lesions.
Conclusion: Different DCE-MRI-based parameters (PEI, TPEI, MITR) could significantly differentiate all monoclonal plasma cell disease stages and complemented conventional MRI and PET-based biomarkers.
{"title":"DCE-MRI to distinguish all monoclonal plasma cell disease stages and correlation with diffusion-weighted MRI/PET-based biomarkers in a hybrid simultaneous whole body-2-[18F]FDG-PET/MRI imaging approach.","authors":"Bastien Jamet, Hatem Necib, Thomas Carlier, Eric Frampas, Juliette Bazin, Paul-Henri Desfontis, Aurélien Monnet, Caroline Bodet-Milin, Philippe Moreau, Cyrille Touzeau, Francoise Kraeber-Bodere","doi":"10.1186/s40644-024-00740-5","DOIUrl":"10.1186/s40644-024-00740-5","url":null,"abstract":"<p><strong>Background: </strong>Dynamic contrast-enhanced-MRI (DCE-MRI) is able to study bone marrow angiogenesis in patients with multiple myeloma (MM) and asymptomatic precursor diseases but its role in the management of MM has not yet been established. The aims of this prospective study was to compare DCE-MRI-based parameters between all monoclonal plasma cell disease stages in order to find out discriminatory parameters and to seek correlations with other diffusion-weighted MRI and positron emission tomography (PET)-based biomarkers in a hybrid simultaneous whole-body-2-[18F]fluorodeoxyglucose (FDG)-PET/MRI (WB-2-[18F]FDG-PET/MRI) imaging approach.</p><p><strong>Methods: </strong>Patients with newly diagnosed Monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM) or symptomatic MM according to international myeloma working group and underwent WB-2-[18F]FDG-PET/MRI imaging including bone marrow DCE sequences at the Nantes University Hospital were prospectively enrolled in this study before receiving treatment.</p><p><strong>Results: </strong>One hundred and sixty-seven patients (N = 167, mean age: 64 years ± 11 [Standard deviation], 66 males) were considered for the analysis. DCE-MRI-based Peak Enhancement Intensity (PEI), Time to PEI (TPEI) and their maximum intensity time ratio (MITR: PEI/TPEI) values were significantly different between the different monoclonal plasma cell disease stages, PEI values increasing and TPEI values decreasing progressively along the spectrum of plasma cell disorders, from MGUS stage to symptomatic multiple myeloma. PEI values were significantly higher in patients with diffuse bone marrow involvement (either in PET or in MRI images) than in those without diffuse bone marrow involvement, unlike TPEI values. PEI and TPEI values were not significantly different between patients with or without focal bone lesions.</p><p><strong>Conclusion: </strong>Different DCE-MRI-based parameters (PEI, TPEI, MITR) could significantly differentiate all monoclonal plasma cell disease stages and complemented conventional MRI and PET-based biomarkers.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"93"},"PeriodicalIF":3.5,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11241781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141589736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1186/s40644-024-00733-4
Shelly Yim, Wei Chan Lin, Jung Sen Liu, Ming Hong Yen
This study compared the survival outcomes after thermal ablation versus wedge resection in patients with stage I non-small cell lung cancer (NSCLC) ≤ 2 cm. Data from the United States (US) National Cancer Institute Surveillance Epidemiology and End Results (SEER) database from 2004 to 2019 were retrospectively analyzed. Patients with stage I NSCLC and lesions ≤ 2 cm who received thermal ablation or wedge resection were included. Patients who received chemotherapy or radiotherapy were excluded. Propensity-score matching (PSM) was applied to balance the baseline characteristics between patients who underwent the two procedures. Univariate and Cox regression analyses were performed to determine the associations between study variables, overall survival (OS), and cancer-specific survival (CSS). After PSM, 328 patients remained for analysis. Multivariable Cox regression analysis revealed, compared to wedge resection, thermal ablation was significantly associated with a greater risk of poor OS (adjusted HR [aHR]: 1.34, 95% CI: 1.09–1.63, p = 0.004) but not CSS (aHR: 1.28, 95% CI: 0.96–1.71, p = 0.094). In stratified analyses, no significant differences were observed with respect to OS and CSS between the two procedures regardless of histology and grade. In patients with tumor size 1 to 2 cm, compared to wedge resection, thermal ablation was significantly associated with a higher risk of poor OS (aHR: 1.35, 95% CI: 1.10–1.66, p = 0.004). In contrast, no significant difference was found on OS and CSS between thermal ablation and wedge resection among those with tumor size < 1 cm. In patients with stage I NSCLC and tumor size < 1 cm, thermal ablation has similar OS and CSS with wedge resection.
{"title":"Survival after thermal ablation versus wedge resection for stage I non-small cell lung cancer < 1 cm and 1 to 2 cm: evidence from the US SEER database","authors":"Shelly Yim, Wei Chan Lin, Jung Sen Liu, Ming Hong Yen","doi":"10.1186/s40644-024-00733-4","DOIUrl":"https://doi.org/10.1186/s40644-024-00733-4","url":null,"abstract":"This study compared the survival outcomes after thermal ablation versus wedge resection in patients with stage I non-small cell lung cancer (NSCLC) ≤ 2 cm. Data from the United States (US) National Cancer Institute Surveillance Epidemiology and End Results (SEER) database from 2004 to 2019 were retrospectively analyzed. Patients with stage I NSCLC and lesions ≤ 2 cm who received thermal ablation or wedge resection were included. Patients who received chemotherapy or radiotherapy were excluded. Propensity-score matching (PSM) was applied to balance the baseline characteristics between patients who underwent the two procedures. Univariate and Cox regression analyses were performed to determine the associations between study variables, overall survival (OS), and cancer-specific survival (CSS). After PSM, 328 patients remained for analysis. Multivariable Cox regression analysis revealed, compared to wedge resection, thermal ablation was significantly associated with a greater risk of poor OS (adjusted HR [aHR]: 1.34, 95% CI: 1.09–1.63, p = 0.004) but not CSS (aHR: 1.28, 95% CI: 0.96–1.71, p = 0.094). In stratified analyses, no significant differences were observed with respect to OS and CSS between the two procedures regardless of histology and grade. In patients with tumor size 1 to 2 cm, compared to wedge resection, thermal ablation was significantly associated with a higher risk of poor OS (aHR: 1.35, 95% CI: 1.10–1.66, p = 0.004). In contrast, no significant difference was found on OS and CSS between thermal ablation and wedge resection among those with tumor size < 1 cm. In patients with stage I NSCLC and tumor size < 1 cm, thermal ablation has similar OS and CSS with wedge resection.","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"46 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141585693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1186/s40644-024-00727-2
Charline Lasnon, Adeline Morel, Nicolas Aide, Angélique Da Silva, George Emile
Background: Exploring the value of baseline and early 18F-FDG PET/CT evaluations in prediction PFS in ER+/HER2- metastatic breast cancer patients treated with a cyclin-dependent kinase inhibitor in combination with an endocrine therapy.
Methods: Sixty-six consecutive breast cancer patients who underwent a pre-therapeutic 18F-FDG PET/CT and a second PET/CT within the first 6 months of treatment were retrospectively included. Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) and Dmax, which represents tumour dissemination and is defined as the distance between the two most distant lesions, were computed. The variation in these parameters between baseline and early evaluation PET as well as therapeutic evaluation using PERCIST were assessed as prognosticators of PFS at 18 months.
Results: The median follow-up was equal to 22.5 months. Thirty progressions occurred (45.4%). The average time to event was 17.8 ± 10.4 months. At baseline, Dmax was the only predictive metabolic parameter. Patients with a baseline Dmax ≤ 18.10 cm had a significantly better 18 m-PFS survival than the others: 69.2% (7.7%) versus 36.7% (8.8%), p = 0.017. There was no association between PERCIST evaluation and 18 m-PFS status (p = 0.149) and there was no difference in 18 m-PFS status between patients classified as complete, partial metabolic responders or having stable metabolic disease.
Conclusion: Disease spread at baseline PET, as assessed by Dmax, is predictive of an event occurring within 18 months. In the absence of early metabolic progression, which occurs in 15% of patients, treatment should be continued regardless of the quality of the initial response to treatment.
{"title":"Baseline and early <sup>18</sup>F-FDG PET/CT evaluations as predictors of progression-free survival in metastatic breast cancer patients treated with targeted anti-CDK therapy.","authors":"Charline Lasnon, Adeline Morel, Nicolas Aide, Angélique Da Silva, George Emile","doi":"10.1186/s40644-024-00727-2","DOIUrl":"10.1186/s40644-024-00727-2","url":null,"abstract":"<p><strong>Background: </strong>Exploring the value of baseline and early <sup>18</sup>F-FDG PET/CT evaluations in prediction PFS in ER+/HER2- metastatic breast cancer patients treated with a cyclin-dependent kinase inhibitor in combination with an endocrine therapy.</p><p><strong>Methods: </strong>Sixty-six consecutive breast cancer patients who underwent a pre-therapeutic <sup>18</sup>F-FDG PET/CT and a second PET/CT within the first 6 months of treatment were retrospectively included. Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) and D<sub>max</sub>, which represents tumour dissemination and is defined as the distance between the two most distant lesions, were computed. The variation in these parameters between baseline and early evaluation PET as well as therapeutic evaluation using PERCIST were assessed as prognosticators of PFS at 18 months.</p><p><strong>Results: </strong>The median follow-up was equal to 22.5 months. Thirty progressions occurred (45.4%). The average time to event was 17.8 ± 10.4 months. At baseline, D<sub>max</sub> was the only predictive metabolic parameter. Patients with a baseline D<sub>max</sub> ≤ 18.10 cm had a significantly better 18 m-PFS survival than the others: 69.2% (7.7%) versus 36.7% (8.8%), p = 0.017. There was no association between PERCIST evaluation and 18 m-PFS status (p = 0.149) and there was no difference in 18 m-PFS status between patients classified as complete, partial metabolic responders or having stable metabolic disease.</p><p><strong>Conclusion: </strong>Disease spread at baseline PET, as assessed by D<sub>max</sub>, is predictive of an event occurring within 18 months. In the absence of early metabolic progression, which occurs in 15% of patients, treatment should be continued regardless of the quality of the initial response to treatment.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"90"},"PeriodicalIF":3.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11232230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141562646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.1186/s40644-024-00723-6
Karoline Kallis, Christopher C Conlin, Allison Y Zhong, Troy S Hussain, Aritrick Chatterjee, Gregory S Karczmar, Rebecca Rakow-Penner, Anders M Dale, Tyler M Seibert
Background: High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.
Methods: One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).
Results: Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.
Conclusion: sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.
{"title":"Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.","authors":"Karoline Kallis, Christopher C Conlin, Allison Y Zhong, Troy S Hussain, Aritrick Chatterjee, Gregory S Karczmar, Rebecca Rakow-Penner, Anders M Dale, Tyler M Seibert","doi":"10.1186/s40644-024-00723-6","DOIUrl":"10.1186/s40644-024-00723-6","url":null,"abstract":"<p><strong>Background: </strong>High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.</p><p><strong>Methods: </strong>One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm<sup>2</sup> using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm<sup>2</sup> via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm<sup>2</sup> (sDWI<sub>500</sub>) and b = 0, b = 500 s/mm<sup>2</sup>, and b = 1000 s/mm<sup>2</sup> (sDWI<sub>1000</sub>). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).</p><p><strong>Results: </strong>Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI<sub>1000</sub> and -67 ± 24% for sDWI<sub>500</sub>. AUC for aDWI, sDWI<sub>500,</sub> sDWI<sub>1000</sub>, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.</p><p><strong>Conclusion: </strong>sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"89"},"PeriodicalIF":3.5,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11229343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141554141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}