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An interactive 3D atlas of sentinel lymph nodes in breast cancer developed using SPECT/CT. 利用 SPECT/CT 技术开发的乳腺癌前哨淋巴结交互式三维图谱。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-30 DOI: 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.

背景:乳腺癌前哨淋巴结(SLN)的识别和评估对于优化患者管理非常重要。本研究旨在开发交互式三维乳腺前哨淋巴结图谱,并对淋巴引流模式和肿瘤患病率进行统计分析:方法:共纳入 861 名接受术前淋巴管造影和 SPECT/CT 检查的早期乳腺癌患者。采用贝叶斯推断、非参数自引导和回归技术计算淋巴引流和肿瘤患病率统计数据。对 350 名患者进行了 SPECT/CT 与参考患者 CT 的图像配准,并对 SLN 位置进行了相对于参考 CT 的转换。对参考 CT 进行分割以显示骨骼和肌肉,并将 SLN 分布与欧洲放射治疗与肿瘤学会 (ESTRO) 的临床目标体积 (CTV) 进行比较。SLN图谱和统计分析都集成到了图形用户界面(GUI)中:直接淋巴引流至腋窝 I 级(前方)结节区最为常见(77.2%),其次是乳腺内结节区(30.4%)。乳房外上象限的肿瘤发病率最高(22.9%),其次是乳晕后区域(12.8%)。三维图集中有来自 335 名患者的 765 个 SLN,ESTRO CTV 覆盖了 33.3%-66.7% 的腋窝 SLN 和 25.4% 的乳腺内 SLN:交互式三维图谱有效地显示了大量患者的乳腺SLN分布和统计数据。该图谱可免费下载,是一种宝贵的教育资源,今后可用于指导治疗。
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引用次数: 0
Development and validation of a machine learning-based 18F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival. 基于机器学习的18F-氟脱氧葡萄糖PET/CT放射组学特征的开发与验证,用于预测胃癌生存率。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-30 DOI: 10.1186/s40644-024-00741-4
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

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。
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引用次数: 0
Pelvic lymph node mapping in prostate cancer: examining the impact of PSMA PET/CT on radiotherapy decision-making in patients with node-positive disease. 前列腺癌盆腔淋巴结映射:研究 PSMA PET/CT 对结节阳性患者放疗决策的影响。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-29 DOI: 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.

前言:前列腺特异性膜抗原(PSMA)正电子发射计算机断层扫描(PET)成像在前列腺癌治疗中起着至关重要的作用。然而,关于 PSMA PET/CT(计算机断层扫描)如何影响放射治疗决策,尤其是结节阳性前列腺癌病例的放射治疗决策,目前还缺乏全面的数据。本研究旨在通过评估两个主要目标来填补这一空白:(1) 与 PSMA PET/CT 相比,使用 CT 的传统方法绘制主动脉分叉以内的区域和非区域淋巴结 (LN) 及其分布图;(2) 评估 PSMA PET/CT 发现对放射治疗决策的影响:对 95 例结节阳性前列腺癌患者进行了回顾性分析,这些患者在接受原发性放疗和雄激素剥夺疗法(ADT)之前均接受了 CT 和 PSMA PET/CT 成像检查。分析的重点是确定不同区域的 LN,包括髂总、髂外、髂内、钝肌、骶前、直肠间、腹股沟和其他部位。根据 PSMA PET/CT 检查结果对治疗方案进行复查以进行修改,并进行统计分析以确定 PSMA PET/CT 扫描中专属结节阳性的预测因素:结果:PSMA PET/CT 在 48% 的病例中发现了额外的阳性结节,导致 29% 的患者的分期从 N0 改为 N1。最常见的转移性结节位于髂外(76 个;34%)、髂内(43 个;19%)和髂总(35 个;15%)。在仅通过 PSMA PET 检测到结节的患者中,最常见的结节位于髂外站(27 个,占 40%)、髂内站(13 个,占 19%)和髂总站(11 个,占 15%)。在完全显示 PSMA PET 检测到结节的 28 例患者中,有 5 例患者(18%)改变了放疗治疗野,23 例患者(83%)增加了剂量。然而,分析结果显示,PSMA PET/CT 扫描显示结节阳性的预测因素并不明显:讨论:该研究强调了 PSMA PET/CT 与单纯 CT 相比在对结节阳性前列腺癌进行准确分期和指导个性化放疗策略方面的关键作用。我们提倡将 PSMA PET/CT 常规纳入诊断方案,以优化治疗精确度并改善患者预后。
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引用次数: 0
Deformation-based morphometry: a sensitive imaging approach to detect radiation-induced brain injury? 基于形变的形态测量:检测辐射所致脑损伤的灵敏成像方法?
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-18 DOI: 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.

背景:放疗是脑肿瘤患者的主要治疗方法。然而,放疗会导致认知障碍。为了改善放疗引起的脑部后遗症的管理,基于形变的形态测量(DBM)可能具有重要意义。在此,我们利用核磁共振成像非线性配准获得的雅各布行列式(JD)来分析 DBM 的意义,以检测脑辐照动物模型中健康脑组织的局部脆弱性:方法:对大鼠进行分次全脑辐照(WBI,30 Gy)。方法:对大鼠进行分次全脑照射(30 Gy),在照射后 1 个月至 6 个月期间进行纵向多参数磁共振成像(解剖、弥散和血管)研究。通过对核磁共振成像图像进行登记,以 DBM 分析宏观变化,并通过量化脑血容量(CBV)和扩散指标(包括平均扩散率(MD))评估细胞和血管水平的微观变化。对整个大脑和 DBM 确定的特定脑区进行体素比较。免疫组织学分析用于观察血管和星形胶质细胞:结果:DBM 分析显示了局部宏观结构变化的时间过程;其中一些变化在 WBI 后是短暂的,另一些则是长期的。DBM 显示了两个易受影响的脑区,即胼胝体和大脑皮层。扩散指标和 CBV 变化显示,DBM 变化在空间上与微结构改变相关,免疫组织学分析也证实了这一点。最后,矩阵相关性表明,在胼胝体和皮层中,WBI 后早期阶段的 JD/MD 与晚期阶段的 JD/CBV 之间存在相关性:结论:脑辐照会诱发 DBM 检测到的局部宏观结构变化,这可能与识别易受辐射诱发组织变化影响的脑结构有关。将这些数据应用于患者身上可为脑放射毒性成像研究带来附加值。
{"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}
引用次数: 0
The pulmonary-vascular-stump filling defect on CT post lung tumor resection: a predictor of cancer progression. 肺部肿瘤切除术后 CT 上的肺血管残端充盈缺损:癌症进展的预测因素。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-16 DOI: 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.

背景:探讨 CT 上肺血管残端充盈缺损并研究其与癌症进展的关系:探讨CT上肺血管残端充盈缺损并研究其与癌症进展的关系:回顾性分析我院数据库中2018年至2022年的记录,以确定肺癌切除术后肺血管残端充盈缺损,并收集患者的影像学和临床数据:在分析的1714例患者中,发现95例肺癌切除术后血管残端充盈缺损。排除失访病例后,共有 77 例纳入最终研究。从形态上看,充盈缺损可分为 46 例凸面形和 31 例凹面形。与凸形缺损相比,凹形缺损的发生率更高(51.7% 对 9.4%,P = 0.001)。在肺动脉残端 61 个充盈缺损中,有 4 个(6.5%)增大的凹形缺损在 PET 上显示出核素浓度和血管外扩展。凹缺损组、凸缺损组和非充盈缺损组的无进展生存期(PFS)时间差异显著(log-rank P 结论):肺部肿瘤切除术后肺动脉残端某些充盈缺损表现为恶性生长。在 CT 显示充盈缺损的早期,凹陷形状可独立预测癌症进展,而在随后的随访中,充盈缺损的生长可独立预测癌症进展。
{"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}
引用次数: 0
Correction: A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study 更正: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
IF 4.9 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-11 DOI: 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":"&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;The original article has been corrected.&lt;/p&gt;&lt;ol data-track-component=\"outbound reference\" data-track-context=\"references section\"&gt;&lt;li data-counter=\"1.\"&gt;&lt;p&gt;Li et al. Cancer Imaging (2024) 24:62. https://doi.org/10.1186/s40644-024-00690-y.&lt;/p&gt;&lt;/li&gt;&lt;/ol&gt;&lt;p&gt;Download references&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/p&gt;&lt;h3&gt;Authors and Affiliations&lt;/h3&gt;&lt;ol&gt;&lt;li&gt;&lt;p&gt;Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China&lt;/p&gt;&lt;p&gt;Zongbao Li, Yan Lv, Yanyan Yang, Yunxi Li, Meng Sun, Siqian Liu &amp; Mengchao Zhang&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Department of Radiology, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 611130, China&lt;/p&gt;&lt;p&gt;Zongbao Li&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Department of Radiology, The People’s Hospital of Bao’an, Shenzhen University, Shenzhen, 518101, China&lt;/p&gt;&lt;p&gt;Jianzhong Zheng &amp; Yu Hu&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Life Sciences, GE Healthcare, Shenyang, 110000, China&lt;/p&gt;&lt;p&gt;Yan Guo&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130000, China&lt;/p&gt;&lt;p&gt;Yifan Zhong &amp; Le Zhou&lt;/p&gt;&lt;/li&gt;&lt;/ol&gt;&lt;span&gt;Authors&lt;/span&gt;&lt;ol&gt;&lt;li&gt;&lt;span&gt;Zongbao Li&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yifan Zhong&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yan Lv&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Jianzhong Zheng&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yu Hu&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yanyan Yang&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yunxi Li&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Meng Sun&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Siqian Liu&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Yan Guo&lt;/span&gt;View author publications&lt;p&gt;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}
引用次数: 0
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. 在全身-2-[18F]FDG-PET/MRI混合同步成像方法中,DCE-MRI可区分单克隆浆细胞疾病的所有分期,并与基于弥散加权MRI/PET的生物标记物相关。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-11 DOI: 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.

背景:动态对比增强磁共振成像(DCE-MRI)能够研究多发性骨髓瘤(MM)患者和无症状前驱疾病患者的骨髓血管生成,但其在MM治疗中的作用尚未确定。这项前瞻性研究的目的是在全身-2-[18F]氟脱氧葡萄糖(FDG)-PET/MRI(WB-2-[18F]FDG-PET/MRI)混合同步成像方法中,比较所有单克隆浆细胞疾病分期之间基于 DCE-MRI 的参数,以找出鉴别参数,并寻求与其他弥散加权 MRI 和基于正电子发射断层扫描(PET)的生物标记物的相关性:方法:根据国际骨髓瘤工作组的标准,对新诊断为意义未定的单克隆丙种球蛋白病(MGUS)、烟雾型多发性骨髓瘤(SMM)或无症状MM,并在接受治疗前在南特大学医院接受了包括骨髓DCE序列在内的WB-2-[18F]FDG-PET/MRI成像的患者进行前瞻性登记:167 名患者(N = 167,平均年龄:64 岁 ± 11 [标准差],66 名男性)被纳入分析范围。基于 DCE-MRI 的峰值增强强度(PEI)、PEI 时间(TPEI)及其最大强度时间比(MITR:PEI/TPEI)值在不同单克隆浆细胞疾病分期之间存在显著差异,从 MGUS 期到有症状的多发性骨髓瘤,PEI 值在浆细胞疾病谱中逐渐增加,TPEI 值逐渐减少。与 TPEI 值不同的是,有弥漫性骨髓受累(PET 或 MRI 图像)的患者 PEI 值明显高于无弥漫性骨髓受累的患者。PEI和TPEI值在有或无局灶性骨病变的患者之间无明显差异:结论:基于DCE-MRI的不同参数(PEI、TPEI、MITR)可显著区分单克隆浆细胞疾病的所有分期,是对传统MRI和PET生物标志物的补充。
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引用次数: 0
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 小于 1 厘米和 1 至 2 厘米的 I 期非小细胞肺癌热消融与楔形切除术后的存活率:来自美国 SEER 数据库的证据
IF 4.9 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-11 DOI: 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.
这项研究比较了≤2厘米的I期非小细胞肺癌(NSCLC)患者热消融与楔形切除术后的生存结果。研究人员对美国国家癌症研究所监测流行病学和最终结果(SEER)数据库2004年至2019年的数据进行了回顾性分析。纳入了接受热消融或楔形切除术的病灶≤2厘米的I期NSCLC患者。不包括接受化疗或放疗的患者。采用倾向分数匹配法(PSM)来平衡接受两种手术的患者的基线特征。为了确定研究变量、总生存率(OS)和癌症特异性生存率(CSS)之间的关系,进行了单变量和 Cox 回归分析。在 PSM 之后,仍有 328 名患者可供分析。多变量 Cox 回归分析显示,与楔形切除术相比,热消融与较差的 OS 风险显著相关(调整 HR [aHR]:1.34,95% CI:1.09-1.63,p = 0.004),但与 CSS 无关(aHR:1.28,95% CI:0.96-1.71,p = 0.094)。在分层分析中,无论组织学和分级如何,两种手术的OS和CSS均无明显差异。在肿瘤大小为1至2厘米的患者中,与楔形切除术相比,热消融术与较高的不良OS风险显著相关(aHR:1.35,95% CI:1.10-1.66,p = 0.004)。相比之下,在肿瘤大小小于1厘米的患者中,热消融与楔形切除术在OS和CSS方面无明显差异。对于肿瘤大小小于1厘米的I期NSCLC患者,热消融与楔形切除术的OS和CSS相似。
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引用次数: 0
Baseline and early 18F-FDG PET/CT evaluations as predictors of progression-free survival in metastatic breast cancer patients treated with targeted anti-CDK therapy. 作为抗 CDK 靶向治疗转移性乳腺癌患者无进展生存期预测指标的基线和早期 18F-FDG PET/CT 评估。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-09 DOI: 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.

背景:探索基线和早期18F-FDG PET/CT评估在ER+/HER2-转移性乳腺癌患者接受细胞周期蛋白依赖性激酶抑制剂联合内分泌治疗后预测PFS的价值:回顾性纳入了66例连续接受治疗前18F-FDG PET/CT和治疗后6个月内第二次PET/CT检查的乳腺癌患者。研究人员计算了代谢性肿瘤体积(MTV)、总病灶糖酵解量(TLG)和Dmax,Dmax代表肿瘤扩散情况,定义为两个最远病灶之间的距离。这些参数在基线和早期 PET 评估以及 PERCIST 治疗评估之间的变化被评估为 18 个月时的 PFS 预后指标:中位随访时间为22.5个月。发生了 30 例进展(45.4%)。平均进展时间为(17.8 ± 10.4)个月。在基线时,Dmax是唯一可预测的代谢参数。基线Dmax≤18.10厘米的患者的18个月PFS生存率明显高于其他患者:69.2%(7.7%)对36.7%(8.8%),P = 0.017。PERCIST评估与18 m-PFS状况之间没有关联(p = 0.149),被归类为完全、部分代谢反应者或代谢疾病稳定的患者之间的18 m-PFS状况也没有差异:结论:根据 Dmax 评估,基线 PET 的疾病扩散可预测 18 个月内发生的事件。在没有出现早期代谢进展的情况下(15% 的患者会出现这种情况),无论最初治疗反应的质量如何,都应继续治疗。
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引用次数: 0
Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer. 比较合成和获取的高 b 值弥散加权磁共振成像在检测前列腺癌方面的应用。
IF 3.5 2区 医学 Q2 ONCOLOGY Pub Date : 2024-07-08 DOI: 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.

背景:高b值弥散加权成像(DWI)用于检测有临床意义的前列腺癌(csPCa)。本研究对合成 DWI(sDWI)和获取的 DWI(aDWI)进行了定性和定量比较,以检测 csPCa:研究纳入了 151 名连续接受前列腺 MRI 和活检的患者。我们使用一台使用 32 通道相控阵体线圈的 3T 临床扫描仪采集了 b = 0、500、1000 和 2000 s/mm2 的轴向 DWI。我们通过基于单指数衰减的外推法,使用 b = 0 和 b = 500 s/mm2(sDWI500)以及 b = 0、b = 500 s/mm2 和 b = 1000 s/mm2(sDWI1000)回顾性地合成了 b = 2000 s/mm2 的 DWI。在不同的感兴趣区(单独前列腺、前列腺加 5 毫米、30 毫米和 70 毫米边缘以及全视野)内评估 sDWI 和 aDWI 信号强度的差异。对每个区域内的最大 DWI 值进行评估,以预测 csPCa。分类准确性与限制性频谱成像限制性评分(RSIrs)进行了比较,后者是之前基于多指数 DWI 验证过的生物标记物。通过接收者操作特征曲线下面积(AUC)对 csPCa 的判别进行评估:结果:在前列腺内,sDWI1000 和 sDWI500 的 sDWI 和 aDWI 信号平均差异百分比的平均值(标准差)分别为 -46 ± 35% 和 -67 ± 24%。前列腺内 aDWI、sDWI500、sDWI1000 和 RSIrs 的 AUC 分别为 0.62[95%置信区间:0.53,0.71]、0.63[0.54,0.72]、0.65[0.56,0.73] 和 0.78[0.71,0.86]。结论:在前列腺内,sDWI 的质量与 aDWI 相当,但在盆腔周围组织中,sDWI 会产生高强度伪影,干扰癌症的定量检测,并可能掩盖转移灶。在前列腺中,RSIrs 对 csPCa 的定量检测优于 sDWI 或 aDWI。
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Cancer Imaging
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