Literature DB >> 33917590

Pretherapeutic Imaging for Axillary Staging in Breast Cancer: A Systematic Review and Meta-Analysis of Ultrasound, MRI and FDG PET.

Morwenn Le Boulc'h1, Julia Gilhodes2, Zara Steinmeyer3, Sébastien Molière4, Carole Mathelin5.   

Abstract

BACKGROUND: This systematic review aimed at comparing performances of ultrasonography (US), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (PET) for axillary staging, with a focus on micro- or micrometastases.
METHODS: A search for relevant studies published between January 2002 and March 2018 was conducted in MEDLINE database. Study quality was assessed using the QUality Assessment of Diagnostic Accuracy Studies checklist. Sensitivity and specificity were meta-analyzed using a bivariate random effects approach;
Results: Across 62 studies (n = 10,374 patients), sensitivity and specificity to detect metastatic ALN were, respectively, 51% (95% CI: 43-59%) and 100% (95% CI: 99-100%) for US, 83% (95% CI: 72-91%) and 85% (95% CI: 72-92%) for MRI, and 49% (95% CI: 39-59%) and 94% (95% CI: 91-96%) for PET. Interestingly, US detects a significant proportion of macrometastases (false negative rate was 0.28 (0.22, 0.34) for more than 2 metastatic ALN and 0.96 (0.86, 0.99) for micrometastases). In contrast, PET tends to detect a significant proportion of micrometastases (true positive rate = 0.41 (0.29, 0.54)). Data are not available for MRI.
CONCLUSIONS: In comparison with MRI and PET Fluorodeoxyglucose (FDG), US is an effective technique for axillary triage, especially to detect high metastatic burden without upstaging majority of micrometastases.

Entities:  

Keywords:  breast cancer; lymph node; magnetic resonance imaging; meta-analysis; micrometastasis; positron emission tomography; ultrasound

Year:  2021        PMID: 33917590     DOI: 10.3390/jcm10071543

Source DB:  PubMed          Journal:  J Clin Med        ISSN: 2077-0383            Impact factor:   4.241


  3 in total

1.  Superiority of 68Ga-FAPI PET/CT scan in detecting additional lesions compared to 18FDG PET/CT scan in breast cancer.

Authors:  Umut Elboga; Ertan Sahin; Tulay Kus; Yusuf Burak Cayirli; Gokmen Aktas; Evren Uzun; Havva Yesil Cinkir; Fatih Teker; Ozlem Nuray Sever; Alper Aytekin; Latif Yilmaz; Aydin Aytekin; Ufuk Cimen; Vuslat Mumcu; Benan Kilbas; Y Zeki Çelen
Journal:  Ann Nucl Med       Date:  2021-08-26       Impact factor: 2.668

Review 2.  AGO Recommendations for the Diagnosis and Treatment of Patients with Early Breast Cancer: Update 2022.

Authors:  Nina Ditsch; Achim Wöcke; Michael Untch; Christian Jackisch; Ute-Susann Albert; Maggie Banys-Paluchowski; Ingo Bauerfeind; Jens-Uwe Blohmer; Wilfried Budach; Peter Dall; Eva Maria Fallenberg; Peter A Fasching; Tanja N Fehm; Michael Friedrich; Bernd Gerber; Oleg Gluz; Nadia Harbeck; Jörg Heil; Jens Huober; Hans H Kreipe; David Krug; Thorsten Kühn; Sherko Kümmel; Cornelia Kolberg-Liedtke; Sibylle Loibl; Diana Lüftner; Michael Patrick Lux; Nicolai Maass; Christoph Mundhenke; Ulrike Nitz; Tjoung-Won Park-Simon; Toralf Reimer; Kerstin Rhiem; Achim Rody; Marcus Schmidt; Andreas Schneeweiss; Florian Schütz; Hans-Peter Sinn; Christine Solbach; Erich-Franz Solomayer; Elmar Stickeler; Christoph Thomssen; Isabell Witzel; Volkmar Müller; Wolfgang Janni; Marc Thill
Journal:  Breast Care (Basel)       Date:  2022-05-05       Impact factor: 2.268

3.  Multimodal Imaging of Target Detection Algorithm under Artificial Intelligence in the Diagnosis of Early Breast Cancer.

Authors:  Meiping Jiang; Sanlin Lei; Junhui Zhang; Liqiong Hou; Meixiang Zhang; Yingchun Luo
Journal:  J Healthc Eng       Date:  2022-01-10       Impact factor: 2.682

  3 in total

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