Placenta Accreta Spectrum: A Narrative Review of Clinical Management, Contemporary Innovations, And Global Challenges.

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Abstract

Placenta accreta spectrum (PAS) is a severe obstetric complication characterised by abnormal placental adherence or invasion into the uterine wall, posing significant global reproductive health challenges. While clinical guidelines for PAS exist, a critical knowledge gap remains regarding how to successfully translate high-resource diagnostic innovations and multidisciplinary frameworks into resource-limited settings. Furthermore, there is a lack of synthesized literature evaluating how emerging technologies, such as machine learning models and real-time intraoperative flow assessments, can be integrated with traditional imaging to optimise surgical outcomes. This narrative review comprehensively evaluates the evolving clinical landscape of PAS, examining its epidemiology, pathophysiology, risk factors, and diagnostic advancements, while critically appraising multidisciplinary management frameworks across diverse healthcare resource settings. A descriptive narrative approach was utilised to synthesise peer-reviewed publications, consensus guidelines, and clinical studies from PubMed, SCOPUS, Web of Science, and Google Scholar. The initial literature search was conducted in March 2026, with an updated search performed in June 2026 during the manuscript revision process. Data synthesis focused on key parameters including study characteristics, diagnostic modalities (ultrasound, magnetic resonance imaging, and emerging imaging mordalities), and clinical management outcomes, with additional context integrated from regional low- and middle-income country (LMIC) reports. The incidence of PAS has escalated globally, driven primarily by rising primary and recurrent caesarean section rates. Emerging evidence confirms that the condition arises from an endometrial-myometrial interface defect characterised by thinned or absent decidua basalis, accompanied by molecularly driven hypervascularity and altered tissue adhesion. Modern diagnostic signs, such as intracervical lakes (ICL) and the "rail sign," significantly enhance prenatal identification and predict severe peripartum morbidity. Multidisciplinary care, specialized surgical planning, and intraoperative adjuncts (such as transvaginal ultrasound [TVUS] and machine learning models) improve maternal outcomes, although severe postpartum haemorrhage and maternal mortality remain pronounced in resource-limited systems. Optimising PAS outcomes requires timely prenatal detection and structured, coordinated care. Advances in ultrasound techniques, combined imaging scores, and real-time intraoperative flow assessments facilitate better risk stratification and surgical optimisation. Addressing current limitations through standardised reporting frameworks and expanding access to subspecialty multidisciplinary care, especially in low-resource settings, remains mandatory to reduce severe maternal morbidity and optimise reproductive health preservation.

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