Journal of Cancer Research and Clinical Oncology最新文献

{"title":"Cyclosporine plus methotrexate versus cyclosporine alone for graft-versus-host disease prophylaxis in pediatric patients undergoing hematopoietic stem cell transplantation from an HLA-identical sibling.","authors":"Vincenzo Apolito, Valeria Ceolin, Manuela Spadea, Raffaele Vitale, Marta Barone, Alessio Tomatis, Paola Quarello, Francesco Saglio, Franca Fagioli","doi":"10.1007/s00432-025-06138-5","DOIUrl":"10.1007/s00432-025-06138-5","url":null,"abstract":"","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"91"},"PeriodicalIF":2.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11850408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"¹⁵⁷Gd-DOTA-PSMA as theranostic bio-gadolinium agent for prostate cancer targeted gadolinium neutron capture therapy.","authors":"Liang Xie, Jialin Qin, Cuiping Song, Jianchun Yin, Ruixue Wu, Hong Chen, Yujie Dong, Nianfei Wang, Lei Chen, Bing Hong, Ni Chen, Peng Lu, Fei Li, Xiaoxi Pang","doi":"10.1007/s00432-025-06136-7","DOIUrl":"10.1007/s00432-025-06136-7","url":null,"abstract":"<p><strong>Purpose: </strong>Gadolinium-neutron capture therapy (Gd-NCT) employs isotopically enriched Gadolinium (Gd) and thermal neutrons to selectively target cancer cells. This study investigated the targeting efficacy of ¹⁵⁷Gd-DOTA-PSMA (Prostate-Specific Membrane Antigen) in prostate cancer and explored its potential applications in Gd-NCT.</p><p><strong>Methods and results: </strong>We developed ¹⁵⁷Gd-DOTA-PSMA, a novel theranostic bio-gadolinium agent specifically designed for magnetic resonance imaging (MRI)-guided Gd-NCT. ⁶⁸ Ga-DOTA-PSMA positron emission tomography-computed tomography (PET/CT) imaging showed peak radiotracer uptake at 2 h post-injection, with a tumor-to-non-tumor (T/NT) ratio of 6.95 ± 0.60. MRI analysis confirmed a stable T₁ signal enhancement 2 h post-injection. Time-of-flight inductively coupled plasma mass spectrometry (TOF-ICP-MS) revealed significantly elevated Gd concentrations in 22Rv1 tumor compared to PC-3 tumor and other healthy organs. ICP-MS analysis showed Gd concentrations of 165.69 μg [Gd]/g in 22Rv1 tumors and 35.25 μg [Gd]/g in blood, yielding a tumor-to-blood (T/B) ratio of 4.65 ± 0.54 and a T/NT ratio of 3.65 ± 0.49. Neutron irradiation with ¹⁵⁷Gd-DOTA-PSMA reduced cell viability, inhibited colony formation, and induced DNA damage and apoptosis in 22Rv1 cells. In 22Rv1 mice, γ-H2AX levels peaked at 6 h post-irradiation, accompanied by an increase in pro-apoptotic proteins and a decrease in anti-apoptotic proteins over 24 h. In the NCT group following the injection of ¹⁵⁷Gd-DOTA-PSMA, there was effective suppression of tumor growth without a loss of body weight, resulting in a 1.7-fold increase in median survival compared to control group.</p><p><strong>Conclusions: </strong>¹⁵⁷Gd-DOTA-PSMA, as a theranostic bio-gadolinium agent designed for targeted Gd-NCT in prostate cancer, represents a novel therapeutic approach and broadens the scope of potential applications of neutron capture therapy.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"93"},"PeriodicalIF":2.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861226/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143501239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic value of folate-associated gene expression in stage II colon cancer.","authors":"Donia Kaidi, Elisabeth Odin, Yvonne Wettergren, Elinor Bexe Lindskog","doi":"10.1007/s00432-025-06141-w","DOIUrl":"10.1007/s00432-025-06141-w","url":null,"abstract":"<p><strong>Purpose: </strong>Prognostic variability in stage II colon cancer underscores the need for better risk stratification. Analyzing folate-associated gene expression in stage II colon cancer could provide researchers and clinicians with deeper insights into tumor biology and potentially aid in identifying early prognostic and/or predictive biomarkers.</p><p><strong>Methods: </strong>Patients with stage II colon cancer and recurrence (n = 48) were matched to patients with a 5 year recurrence-free follow-up (n = 133). Gene expression of ABCC3, AMT, FPGS, GGH, MFT, PCFT, RFC-1, and TYMS was analyzed in tumor tissue and matching colon mucosa using qPCR and evaluated in relation to time to recurrence (TTR), as well as to demographic and clinicopathological variables.</p><p><strong>Results: </strong>Independent of other covariates, TYMS expression in tumors, pT4 stage, and emergency surgery were associated with TTR. There were significant differences in expression levels of all examined genes between tumor and mucosa. ABCC3, GGH, and RFC-1 expression levels differed in mucosa between microsatellite instability-high (MSI-H) compared to microsatellite stable/microsatellite instability-low (MSS/MSI-L) tumors, whereas tumoral expression of AMT, GGH, and TYMS differed between MSI-H and MSS/MSI-L tumors. Depending on tumor location, the expression of ABCC3, AMT, GGH, and RFC-1 in mucosa, as well as the tumoral expression of AMT, GGH, PCFT and RFC-1 differed.</p><p><strong>Conclusion: </strong>Low tumoral expression of TYMS was associated with worse TTR, independent of MSI status, pT stage, and emergency surgery. The indication of a better outcome for patients with MSI-H status and high tumoral TYMS expression might be of particular interest in the stratification of patients for immunotherapy.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"92"},"PeriodicalIF":2.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861115/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction Note: Genetic inference and single cell expression analysis of potential targets in heart failure and breast cancer.","authors":"Yue Li, Ying Huang, Ning An, Xiaomiao Guan, Bing Liu, Huiying Li, Tingting Jiang","doi":"10.1007/s00432-025-06137-6","DOIUrl":"10.1007/s00432-025-06137-6","url":null,"abstract":"","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"90"},"PeriodicalIF":2.7,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846720/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of the COVID-19 pandemic and lockdown on cancer stage distribution and time to treatment initiation using cancer registry data of the Swiss cantons of Zurich and Zug from 2018 to 2021.","authors":"Flurina Suter, Miriam Wanner, Andreas Wicki, Dimitri Korol, Sabine Rohrmann","doi":"10.1007/s00432-025-06140-x","DOIUrl":"10.1007/s00432-025-06140-x","url":null,"abstract":"<p><strong>Purpose: </strong>Swiss healthcare institutions conducted only urgent procedures during the COVID-19 lockdown, potentially leading to a lack of care for other severe diseases, such as cancer. We examined the effects of the pandemic on cancer stage distribution and time between cancer diagnosis and treatment initiation using population-based cancer registry data.</p><p><strong>Methods: </strong>The study was based on data of the cancer registry of the cantons of Zurich and Zug from 2018 to 2021. Cancer stage distribution was analysed descriptively and with a Pearson's Chi-squared test. Time between cancer diagnosis and treatment initiation was determined in days and analysed descriptively and by fitting Quasipoisson regression models.</p><p><strong>Results: </strong>For all-cancer and colorectal, lung, and prostate cancer statistically significant evidence for a difference in cancer stages distribution among the incidence years was observed. Based on the all-cancer regression models, longer time to treatment initiation (TTI) was observed for patients diagnosed in 2021 and receiving surgery (Rate Ratio = 1.08 [95% confidence interval 1.03, 1.14]) or hormone therapy (1.20 [1.03, 1.40]) compared to those diagnosed in 2018/19 receiving those therapies. We observed no difference in TTI between cancer patients diagnosed in 2020 compared to 2018/19 for any of the therapies investigated, except for chemotherapy with shorter TTI (0.92 [0.86, 0.98]).</p><p><strong>Conclusion: </strong>The observed effects on cancer outcomes in 2020 and 2021 compared to 2018/19 coincided with the beginning of the COVID-19 pandemic in Switzerland in 2020 onwards. Short- and long-term effects of the pandemic on cancer outcomes and the public healthcare system were observed. However, we cannot exclude that the implementation of the new Swiss law on cancer registration in 2020 explains part of our observations.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"88"},"PeriodicalIF":2.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Docetaxel rechallenge in HER2-negative metastatic breast cancer: a real-world study of previously discontinued patients for non-progression reasons.","authors":"Hui-Ai Zeng, Hui-Min Lv, Meng-Wei Zhang, Li-Min Niu, Jing Wang, Hui-Hui Sun, Zhen-Zhen Liu, Min Yan","doi":"10.1007/s00432-025-06133-w","DOIUrl":"10.1007/s00432-025-06133-w","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to evaluate the efficacy and safety of docetaxel rechallenge in HER2-negative metastatic breast cancer (MBC) patients who discontinued docetaxel for reasons other than disease progression.</p><p><strong>Patients and methods: </strong>We retrospectively analyzed HER2-negative MBC patients treated with docetaxel-based therapy (DBT) at our institution from 2010 to 2020. Objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were assessed. Multivariate Cox regression and propensity score matching analysis (PSMA) were used to minimize bias.</p><p><strong>Results: </strong>Among 600 patients, 369 only received docetaxel once (control group), while 231 (38.5%) received docetaxel rechallenge as second or later-line therapy (rechallenge group). In the second-line rechallenge subset (143 patients), ORR was 51.0%, and PFS was 6.7 months. Multivariate analysis showed that a response to initial DBT (stable disease [SD] vs. complete response/partial response [CR/PR]: odds ratio [OR] 2.615, 95% confidence interval [CI] 1.373-4.981; p = 0.03) independently predicted the ORR. Beyond second-line rechallenge, the ORR and PFS were 37.5% and 5.6 months, respectively. After PSMA, the rechallenge group demonstrated significantly improved OS compared to the control group: 50.5 months vs. 46.0 months (Hazard Ratio [HR] 0.632; 95% CI 0.455-0.878; p = 0.006). The toxicities reported were manageable, primarily hematologic, with grade 3-4 events occurring in 19.5% of cases.</p><p><strong>Conclusion: </strong>This study suggests that docetaxel rechallenge may be an effective and tolerable later-line treatment option for patients with HER2-negative MBC, particularly those who responded to initial DBT. However, further prospective, randomized controlled research is needed to fully evaluate its impact on disease response in this patient population.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"89"},"PeriodicalIF":2.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.","authors":"Shilin Xu, Chengguang Zhu, Meixuan Wu, Sijia Gu, Yongsong Wu, Shanshan Cheng, Chao Wang, Yue Zhang, Weixia Zhang, Wei Shen, Jiani Yang, Xiaokang Yang, Yu Wang","doi":"10.1007/s00432-025-06134-9","DOIUrl":"10.1007/s00432-025-06134-9","url":null,"abstract":"<p><strong>Purpose: </strong>The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients' pretreatment clinical, positron emission tomography scan (PET/CT) metabolic, and radiomics features.</p><p><strong>Methods: </strong>We enrolled OC patients who underwent PET/CT scans and divided them into two cohorts according to their FIGO stage. Then we manually delineated the volume of interest (VOI) and calculated PET metabolic features. Other PET/CT radiomics features were extracted by Python. We developed 11 prediction models to predict stages based on four groups of features and conducted three experiments to verify the meaning of PET/CT features. We also redesigned experiments to demonstrate the stage prediction performance in ovarian clear cell carcinoma (OCCC) and mucinous ovarian cancer (MCOC).</p><p><strong>Results: </strong>183 OC patients were enrolled in this study, and we obtained 137 features from four groups of data. The best model was an adaptive ensemble with an area under the curve (AUC) value of 0.819. Our proposed models presented the best result of 0.808 in terms of AUC in OCCC and MCOC patients' groups.</p><p><strong>Conclusion: </strong>Through artificial intelligence (AI) algorithms, the PET/CT metabolic and radiomics features combined with clinical features could improve the accuracy of staging prediction.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"87"},"PeriodicalIF":2.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842498/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143458094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns and outcomes of current antitumor therapy for high-grade neuroendocrine neoplasms: perspective of a tertiary referral center.","authors":"Philipp Melhorn, Julia Spitzer, Thomas Adel, Ladislaia Wolff, Peter Mazal, Markus Raderer, Barbara Kiesewetter","doi":"10.1007/s00432-025-06126-9","DOIUrl":"10.1007/s00432-025-06126-9","url":null,"abstract":"<p><strong>Purpose: </strong>Patients with metastatic high-grade neuroendocrine neoplasms (NEN) have an unfavorable prognosis. Treatment patterns and therapy outcome are scarcely evidenced, especially considering the WHO classification updates since 2017, and were thus investigated in this study.</p><p><strong>Methods: </strong>This retrospective single-center analysis evaluated patients with neuroendocrine tumors grade 3 (NET G3) or neuroendocrine carcinomas (NEC) treated at the Medical University of Vienna since 2010. The primary endpoints were progression-free survival (PFS) and overall survival (OS) following first-line treatment.</p><p><strong>Results: </strong>A total of 80 patients were included, 53 (66%) had NEC and 27 (34%) NET G3. Thirty patients had pancreatic NEN (38%), 29 gastrointestinal NEN (36%), 20 an unknown primary (25%), and one gall bladder NEC. All patients had metastatic disease, and all but four received systemic therapy. Platinum/etoposide was the most frequent palliative first-line treatment in NEC (41/47, 87%) and capecitabine/temozolomide (CAPTEM) in NET G3 (14/27, 52%). Overall, the median PFS and OS from first line start were 16.1 and 43.9 months for NET G3 and 6.1 and 12.7 months for NEC, respectively. Median PFS for platin/etoposide in NEC was 6.1 months (overall response rate [ORR] 56%) and for CAPTEM in NET G3 16.9 months (ORR 46%). Irrespective of the limited sample size (n = 4-11), second-line median PFS was short in NEC (FOLFIRI 2.8, FOLFOX 2.6, CAPTEM 5.4, other 2.6 months) and longer in NET G3 (8.2-11.1 months).</p><p><strong>Conclusions: </strong>The present data from a large European NET center show that multiple treatment strategies are used in NEN and highlight the varying outcomes between NET G3 and NEC.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"86"},"PeriodicalIF":2.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143458077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy.","authors":"Yi Chen, David Pasquier, Damon Verstappen, Henry C Woodruff, Philippe Lambin","doi":"10.1007/s00432-025-06119-8","DOIUrl":"10.1007/s00432-025-06119-8","url":null,"abstract":"<p><strong>Purpose: </strong>Hepatocellular carcinoma (HCC) remains a global health concern, marked by increasing incidence rates and poor outcomes. This study seeks to develop a robust predictive model by integrating radiomics and deep learning features with clinical data to predict 2-year survival in HCC patients treated with stereotactic body radiation therapy (SBRT).</p><p><strong>Methods: </strong>This study analyzed a cohort of 186 HCC patients who underwent SBRT. Radiomics features were extracted from CT scans, complemented by collection of clinical data. Training and validation of machine learning models were conducted using nested cross-validation techniques. Deep learning models, leveraging various convolutional neural networks (CNNs), were employed to effectively integrate both image and clinical data. Post-hoc explainability techniques were applied to elucidate the contribution of imaging data to predictive outcomes.</p><p><strong>Results: </strong>Handcrafted radiomics features demonstrated moderate predictive performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.59 to 0.72. Deep learning models, harnessing the fusion of image and clinical data, exhibited improved predictive accuracy, with AUC values ranging from 0.71 to 0.81. Notably, the ensemble model, amalgamating handcrafted radiomics and deep learning features with clinical data, demonstrated the most robust predictive capability, achieving an AUC of 0.86 (95% CI: 0.80-0.93).</p><p><strong>Conclusion: </strong>The ensemble model represents a significant advancement, providing a comprehensive tool for predicting survival outcomes in HCC patients undergoing SBRT. The inclusion of interpretability methods such as Grad-CAM enhances transparency and understanding of these complex predictive models.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"84"},"PeriodicalIF":2.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11825551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143414288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical evaluation of breast cancer tissue with optical coherence tomography: key findings from a large-scale study.","authors":"Xiaojing Liu, Miao Cui, Cuixia Feng, Shujuan Jin, Xiaowei Han, Yongfang Wu, Di Meng, Si Zuo, Qing Xu, YanHong Tai, Feng Liang","doi":"10.1007/s00432-025-06125-w","DOIUrl":"10.1007/s00432-025-06125-w","url":null,"abstract":"<p><strong>Purpose: </strong>Breast cancer patients undergoing breast-conserving surgery may require a second operation if positive margins persist but current intraoperative methodologies often lack real-time and comprehensive assessments of tissue margins. This study addresses this critical gap by introducing a novel approach to enhance margin assessment in breast surgery.</p><p><strong>Methods: </strong>A total of 252 fresh tissue blocks from 199 patients with different types of breast lesions were scanned with a customized swept-source optical coherence tomography (SS-OCT) system, and the OCT features of normal, benign, and malignant breast tissues, were systematically analyzed.</p><p><strong>Results: </strong>The qualitative analysis results revealed that adipose tissue has high penetration depth and a typical honeycomb pattern, whereas fibrous tissue has the brightest grayscale values and a bundle-like structure. The lobular area appears as a dark region, and dilated ducts present a distinct tubular structure on B-scan images. Adenosis results in bright areas, fibroadenoma results in typical contour structures, phyllodes tumors present lobular structures, invasive carcinomas present a stellate pattern and low penetration depth, and mucinous carcinoma cancer cells are clearly visible within the low-scattering mucin.</p><p><strong>Conclusions: </strong>Importantly, we provide comparative OCT and hematoxylin and eosin (H&E) histology images for less common conditions, such as phyllodes tumors, intraductal papillomas, and mucinous carcinoma. For the first time, we established an 3D OCT-histopathology library with a large field of view and systematically analyzed the multidimensional features. This work strongly supports the feasibility of using OCT technology intraoperatively in surgery. Additionally, the OCT-histopathology library can help pathologists better understand and identify tissue features, thereby enhancing diagnostic efficiency.</p>","PeriodicalId":15118,"journal":{"name":"Journal of Cancer Research and Clinical Oncology","volume":"151 2","pages":"83"},"PeriodicalIF":2.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11825538/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143414293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}