Roshan S Rupra, Francesca Ruccia, Kian Daneshi, Fatema Aftab, Yousif F Yousif, Gul R Khan, Sina Dehnadi, Yaqoob H AlSaidi, Nicola Maggialetti, Giovanni Lorusso, Maria Yan, Ankur Khajuria
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The aim of this study is to identify how CTA affects surgical outcomes in autologous breast reconstruction.</p><p><strong>Methods: </strong>A systematic review and meta-analysis (PROSPERO: CRD42024596646) were conducted per PRISMA guidelines. A comprehensive search of six databases identified studies comparing CTA with non-CTA imaging for DIEP flap reconstruction. Primary outcomes included operative time and flap loss rates. Risk of bias was assessed using ROBINS-I and RoB2, with quality appraised via AMSTAR-2 and GRADE.</p><p><strong>Results: </strong>Eighteen studies (3870 patients, 4283 flaps) were included. CTA guidance reduced unilateral flap operative time (mean 304.98 min vs. 390.18 min, CI -12.9 to 5.7; P = 0.2367), as well as partial and total flap loss rates (OR: 0.26, 95% CI: 0.14-0.47; OR: 0.30, 95% CI: 0.13-0.68). High heterogeneity (I² = 98.7%) limited generalizability. 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Future research should compare CTA with MRA, assess cost-effectiveness, integrate AI-assisted imaging, and explore MRI-based protocols for optimized preoperative planning in microsurgical breast cancer reconstruction and enhanced oncologic care delivery.</p><p><strong>Systematic review registration: </strong>https://www.crd.york.ac.uk/PROSPERO/view/CRD42024596646, idenitifier CRD42024596646.</p>","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":"15 ","pages":"1600476"},"PeriodicalIF":3.5000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483871/pdf/","citationCount":"0","resultStr":"{\"title\":\"A systematic review and meta-analysis on computed tomography angiography mapping for deep inferior epigastric perforator flap breast reconstruction.\",\"authors\":\"Roshan S Rupra, Francesca Ruccia, Kian Daneshi, Fatema Aftab, Yousif F Yousif, Gul R Khan, Sina Dehnadi, Yaqoob H AlSaidi, Nicola Maggialetti, Giovanni Lorusso, Maria Yan, Ankur Khajuria\",\"doi\":\"10.3389/fonc.2025.1600476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Breast cancer remains the most prevalent cancer among women globally, necessitating effective reconstructive options post-mastectomy. 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CTA guidance reduced unilateral flap operative time (mean 304.98 min vs. 390.18 min, CI -12.9 to 5.7; P = 0.2367), as well as partial and total flap loss rates (OR: 0.26, 95% CI: 0.14-0.47; OR: 0.30, 95% CI: 0.13-0.68). High heterogeneity (I² = 98.7%) limited generalizability. Prior reviews showed limitations in study design integrity, whereas this study achieved a high-confidence rating.</p><p><strong>Conclusions: </strong>Preoperative CTA improves surgical outcomes in DIEP flap reconstruction, though evidence quality is variable. 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引用次数: 0
摘要
背景：乳腺癌仍然是全球女性中最常见的癌症，需要在乳房切除术后进行有效的重建选择。腹下深穿支皮瓣（DIEP）是自体乳房重建的金标准，尽管穿支的解剖变异性给手术带来了挑战。计算机断层血管造影（CTA）已被提出，以加强术前计划和减少手术时间。本研究的目的是确定CTA如何影响自体乳房重建术的手术结果。方法：根据PRISMA指南进行系统评价和荟萃分析（PROSPERO: CRD42024596646）。对六个数据库进行综合检索，确定了比较CTA与非CTA成像对DIEP皮瓣重建的研究。主要结果包括手术时间和皮瓣丢失率。采用robins - 1和RoB2评估偏倚风险，采用AMSTAR-2和GRADE评估质量。结果：纳入18项研究（3870例患者，4283个皮瓣）。CTA引导可减少单侧皮瓣手术时间（平均304.98 min vs. 390.18 min, CI -12.9 ~ 5.7; P = 0.2367），以及皮瓣部分和全部损失（OR: 0.26, 95% CI: 0.14 ~ 0.47; OR: 0.30, 95% CI: 0.13 ~ 0.68）。高异质性（I²= 98.7%）限制了通用性。先前的综述显示研究设计完整性存在局限性，而本研究获得了高可信度评级。结论：术前CTA改善了DIEP皮瓣重建的手术效果，尽管证据质量存在差异。未来的研究应该比较CTA和MRA，评估成本效益，整合人工智能辅助成像，并探索基于mri的方案，以优化显微外科乳腺癌重建的术前计划和增强肿瘤护理交付。系统评审注册：https://www.crd.york.ac.uk/PROSPERO/view/CRD42024596646，标识符CRD42024596646。
A systematic review and meta-analysis on computed tomography angiography mapping for deep inferior epigastric perforator flap breast reconstruction.
Background: Breast cancer remains the most prevalent cancer among women globally, necessitating effective reconstructive options post-mastectomy. The deep inferior epigastric perforator (DIEP) flap is the gold standard for autologous breast reconstruction, though anatomical variability of perforators presents surgical challenges. Computed tomography angiography (CTA) has been proposed to enhance preoperative planning and reduce operative time. The aim of this study is to identify how CTA affects surgical outcomes in autologous breast reconstruction.
Methods: A systematic review and meta-analysis (PROSPERO: CRD42024596646) were conducted per PRISMA guidelines. A comprehensive search of six databases identified studies comparing CTA with non-CTA imaging for DIEP flap reconstruction. Primary outcomes included operative time and flap loss rates. Risk of bias was assessed using ROBINS-I and RoB2, with quality appraised via AMSTAR-2 and GRADE.
Results: Eighteen studies (3870 patients, 4283 flaps) were included. CTA guidance reduced unilateral flap operative time (mean 304.98 min vs. 390.18 min, CI -12.9 to 5.7; P = 0.2367), as well as partial and total flap loss rates (OR: 0.26, 95% CI: 0.14-0.47; OR: 0.30, 95% CI: 0.13-0.68). High heterogeneity (I² = 98.7%) limited generalizability. Prior reviews showed limitations in study design integrity, whereas this study achieved a high-confidence rating.
Conclusions: Preoperative CTA improves surgical outcomes in DIEP flap reconstruction, though evidence quality is variable. Future research should compare CTA with MRA, assess cost-effectiveness, integrate AI-assisted imaging, and explore MRI-based protocols for optimized preoperative planning in microsurgical breast cancer reconstruction and enhanced oncologic care delivery.
期刊介绍：
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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