Cancer Imaging最新文献

筛选
英文 中文
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
Cancer Imaging 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
{"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}
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
Cancer Imaging Pub Date : 2024-07-11 DOI: 10.1186/s40644-024-00733-4
Shelly Yim, Wei Chan Lin, Jung Sen Liu, Ming Hong Yen
{"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}
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
Cancer Imaging 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
{"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}
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
Cancer Imaging Pub Date : 2024-07-09 DOI: 10.1186/s40644-024-00727-2
Charline Lasnon, Adeline Morel, Nicolas Aide, Angélique Da Silva, George Emile
{"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}
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
Cancer Imaging 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
{"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}
引用次数: 0
Diagnostic efficiency of intravoxel incoherent motion-based virtual magnetic resonance elastography in pulmonary neoplasms. 基于体细胞内非相干运动的虚拟磁共振弹性成像对肺部肿瘤的诊断效率。
IF 3.5 2区 医学
Cancer Imaging Pub Date : 2024-07-06 DOI: 10.1186/s40644-024-00728-1
Shuo Zhang, Yonghao Du, Ting Liang, Xuyin Zhang, Yinxia Guo, Jian Yang, Xianjun Li, Gang Niu
{"title":"Diagnostic efficiency of intravoxel incoherent motion-based virtual magnetic resonance elastography in pulmonary neoplasms.","authors":"Shuo Zhang, Yonghao Du, Ting Liang, Xuyin Zhang, Yinxia Guo, Jian Yang, Xianjun Li, Gang Niu","doi":"10.1186/s40644-024-00728-1","DOIUrl":"10.1186/s40644-024-00728-1","url":null,"abstract":"<p><strong>Background: </strong>The aim of the study were as below. (1) To investigate the feasibility of intravoxel incoherent motion (IVIM)-based virtual magnetic resonance elastography (vMRE) to provide quantitative estimates of tissue stiffness in pulmonary neoplasms. (2) To verify the diagnostic performance of shifted apparent diffusion coefficient (sADC) and reconstructed virtual stiffness values in distinguishing neoplasm nature.</p><p><strong>Methods: </strong>This study enrolled 59 patients (37 males, 22 females) with one pulmonary neoplasm who underwent computed tomography-guided percutaneous transthoracic needle biopsy (PTNB) with pathological diagnosis (26 adenocarcinoma, 10 squamous cell carcinoma, 3 small cell carcinoma, 4 tuberculosis and 16 non-specific benign; mean age, 60.81 ± 9.80 years). IVIM was performed on a 3 T magnetic resonance imaging scanner before biopsy. sADC and virtual shear stiffness maps reflecting lesion stiffness were reconstructed. sADC and virtual stiffness values of neoplasm were extracted, and the diagnostic performance of vMRE in distinguishing benign and malignant and detailed pathological type were explored.</p><p><strong>Results: </strong>Compared to benign neoplasms, malignant ones had a significantly lower sADC and a higher virtual stiffness value (P < 0.001). Subsequent subtype analyses showed that the sADC values of adenocarcinoma and squamous cell carcinoma groups were significantly lower than non-specific benign group (P = 0.013 and 0.001, respectively). Additionally, virtual stiffness values of the adenocarcinoma and squamous cell carcinoma subtypes were significantly higher than non-specific benign group (P = 0.008 and 0.001, respectively). However, no significant correlation was found among other subtype groups.</p><p><strong>Conclusions: </strong>Non-invasive vMRE demonstrated diagnostic efficiency in differentiating the nature of pulmonary neoplasm. vMRE is promising as a new method for clinical diagnosis.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"88"},"PeriodicalIF":3.5,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544583","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
Review on radiomic analysis in 18F-fluorodeoxyglucose positron emission tomography for prediction of melanoma outcomes. 18F- 氟脱氧葡萄糖正电子发射断层扫描中用于预测黑色素瘤预后的放射线组学分析综述。
IF 3.5 2区 医学
Cancer Imaging Pub Date : 2024-07-05 DOI: 10.1186/s40644-024-00732-5
Karim Amrane, Coline Le Meur, Philippe Thuillier, Christian Berthou, Arnaud Uguen, Désirée Deandreis, David Bourhis, Vincent Bourbonne, Ronan Abgral
{"title":"Review on radiomic analysis in <sup>18</sup>F-fluorodeoxyglucose positron emission tomography for prediction of melanoma outcomes.","authors":"Karim Amrane, Coline Le Meur, Philippe Thuillier, Christian Berthou, Arnaud Uguen, Désirée Deandreis, David Bourhis, Vincent Bourbonne, Ronan Abgral","doi":"10.1186/s40644-024-00732-5","DOIUrl":"10.1186/s40644-024-00732-5","url":null,"abstract":"<p><p>Over the past decade, several strategies have revolutionized the clinical management of patients with cutaneous melanoma (CM), including immunotherapy and targeted tyrosine kinase inhibitor (TKI)-based therapies. Indeed, immune checkpoint inhibitors (ICIs), alone or in combination, represent the standard of care for patients with advanced disease without an actionable mutation. Notably BRAF combined with MEK inhibitors represent the therapeutic standard for disease disclosing BRAF mutation. At the same time, FDG PET/CT has become part of the routine staging and evaluation of patients with cutaneous melanoma. There is growing interest in using FDG PET/CT measurements to predict response to ICI therapy and/or target therapy. While semiquantitative values such as standardized uptake value (SUV) are limited for predicting outcome, new measures including tumor metabolic volume, total lesion glycolysis and radiomics seem promising as potential imaging biomarkers for nuclear medicine. The aim of this review, prepared by an interdisciplinary group of experts, is to take stock of the current literature on radiomics approaches that could improve outcomes in CM.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"87"},"PeriodicalIF":3.5,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141537661","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
[68Ga]Ga‑PSMA‑617 PET-based radiomics model to identify candidates for active surveillance amongst patients with GGG 1-2 prostate cancer at biopsy. 基于[68Ga]Ga-PSMA-617 PET的放射组学模型,在活检结果为GGG 1-2的前列腺癌患者中确定主动监测的候选者。
IF 3.5 2区 医学
Cancer Imaging Pub Date : 2024-07-04 DOI: 10.1186/s40644-024-00735-2
Jinhui Yang, Ling Xiao, Ming Zhou, Yujia Li, Yi Cai, Yu Gan, Yongxiang Tang, Shuo Hu
{"title":"[<sup>68</sup>Ga]Ga‑PSMA‑617 PET-based radiomics model to identify candidates for active surveillance amongst patients with GGG 1-2 prostate cancer at biopsy.","authors":"Jinhui Yang, Ling Xiao, Ming Zhou, Yujia Li, Yi Cai, Yu Gan, Yongxiang Tang, Shuo Hu","doi":"10.1186/s40644-024-00735-2","DOIUrl":"10.1186/s40644-024-00735-2","url":null,"abstract":"<p><strong>Purpose: </strong>To develop a radiomics-based model using [<sup>68</sup>Ga]Ga-PSMA PET/CT to predict postoperative adverse pathology (AP) in patients with biopsy Gleason Grade Group (GGG) 1-2 prostate cancer (PCa), assisting in the selection of patients for active surveillance (AS).</p><p><strong>Methods: </strong>A total of 75 men with biopsy GGG 1-2 PCa who underwent radical prostatectomy (RP) were enrolled. The patients were randomly divided into a training group (70%) and a testing group (30%). Radiomics features of entire prostate were extracted from the [<sup>68</sup>Ga]Ga-PSMA PET scans and selected using the minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression model. Logistic regression analyses were conducted to construct the prediction models. Receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curve were employed to evaluate the diagnostic value, clinical utility, and predictive accuracy of the models, respectively.</p><p><strong>Results: </strong>Among the 75 patients, 30 had AP confirmed by RP. The clinical model showed an area under the curve (AUC) of 0.821 (0.695-0.947) in the training set and 0.795 (0.603-0.987) in the testing set. The radiomics model achieved AUC values of 0.830 (0.720-0.941) in the training set and 0.829 (0.624-1.000) in the testing set. The combined model, which incorporated the Radiomics score (Radscore) and free prostate-specific antigen (FPSA)/total prostate-specific antigen (TPSA), demonstrated higher diagnostic efficacy than both the clinical and radiomics models, with AUC values of 0.875 (0.780-0.970) in the training set and 0.872 (0.678-1.000) in the testing set. DCA showed that the net benefits of the combined model and radiomics model exceeded those of the clinical model.</p><p><strong>Conclusion: </strong>The combined model shows potential in stratifying men with biopsy GGG 1-2 PCa based on the presence of AP at final pathology and outperforms models based solely on clinical or radiomics features. It may be expected to aid urologists in better selecting suitable patients for AS.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"86"},"PeriodicalIF":3.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11229016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141533712","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
Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023. 2015年至2023年深度学习在癌症中应用的文献计量分析。
IF 3.5 2区 医学
Cancer Imaging Pub Date : 2024-07-04 DOI: 10.1186/s40644-024-00737-0
Ruiyu Wang, Shu Huang, Ping Wang, Xiaomin Shi, Shiqi Li, Yusong Ye, Wei Zhang, Lei Shi, Xian Zhou, Xiaowei Tang
{"title":"Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023.","authors":"Ruiyu Wang, Shu Huang, Ping Wang, Xiaomin Shi, Shiqi Li, Yusong Ye, Wei Zhang, Lei Shi, Xian Zhou, Xiaowei Tang","doi":"10.1186/s40644-024-00737-0","DOIUrl":"10.1186/s40644-024-00737-0","url":null,"abstract":"<p><strong>Background: </strong>Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aimed to explore the research status and hotspots of the application of DL in cancer.</p><p><strong>Methods: </strong>We retrieved all articles on the application of DL in cancer from the Web of Science database Core Collection database. Biblioshiny, VOSviewer and CiteSpace were used to perform the bibliometric analysis through analyzing the numbers, citations, countries, institutions, authors, journals, references, and keywords.</p><p><strong>Results: </strong>We found 6,016 original articles on the application of DL in cancer. The number of annual publications and total citations were uptrend in general. China published the greatest number of articles, USA had the highest total citations, and Saudi Arabia had the highest centrality. Chinese Academy of Sciences was the most productive institution. Tian, Jie published the greatest number of articles, while He Kaiming was the most co-cited author. IEEE Access was the most popular journal. The analysis of references and keywords showed that DL was mainly used for the prediction, detection, classification and diagnosis of breast cancer, lung cancer, and skin cancer.</p><p><strong>Conclusions: </strong>Overall, the number of articles on the application of DL in cancer is gradually increasing. In the future, further expanding and improving the application scope and accuracy of DL applications, and integrating DL with protein prediction, genomics and cancer research may be the research trends.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"85"},"PeriodicalIF":3.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141533714","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
3D airway geometry analysis of factors in airway navigation failure for lung nodules. 肺结节气道导航失败因素的三维气道几何分析。
IF 3.5 2区 医学
Cancer Imaging Pub Date : 2024-07-04 DOI: 10.1186/s40644-024-00730-7
Hwan-Ho Cho, Junsu Choe, Jonghoon Kim, Yoo Jin Oh, Hyunjin Park, Kyungjong Lee, Ho Yun Lee
{"title":"3D airway geometry analysis of factors in airway navigation failure for lung nodules.","authors":"Hwan-Ho Cho, Junsu Choe, Jonghoon Kim, Yoo Jin Oh, Hyunjin Park, Kyungjong Lee, Ho Yun Lee","doi":"10.1186/s40644-024-00730-7","DOIUrl":"10.1186/s40644-024-00730-7","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure.</p><p><strong>Methods: </strong>We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors.</p><p><strong>Results: </strong>Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803.</p><p><strong>Conclusions: </strong>Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"24 1","pages":"84"},"PeriodicalIF":3.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223435/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141533713","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信