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Photoacoustic (PA) spectroscopy, a hybrid technique combining optical absorption with acoustic resolution, detects biochemical changes in biomolecules within the tumor microenvironment to support early identification of malignancies. By integrating PA with modalities such as ultrasound, photoacoustic microscopy, and nanoparticle-enhanced imaging—then combining endoscopy and machine learning—PA enables real-time, minimally invasive, and highly accurate detection for tumor classification and therapy monitoring. Machine learning–assisted PA studies report diagnostic performance up to AUC 0.96 and classification accuracy exceeding 89%, and ongoing advances aim to further improve nanoparticle design, molecular targeting, and analytics for personalized management.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/photoacoustic-integrated-multimodal-approach-for-colorectal-cancer-diagnosis/369678/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/photoacoustic-integrated-multimodal-approach-for-colorectal-cancer-diagnosis/369678.png","ImageObject",300,407,{"name":92,"@type":93},"Terk","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-24","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",13,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What diagnostic capability does photoacoustic (PA) spectroscopy provide for colorectal cancer?","Question",{"text":113,"@type":114},"PA spectroscopy combines optical absorption with acoustic resolution to detect biochemical changes in biomolecules within the tumor microenvironment. This supports early identification of malignancies.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How do multimodal integrations improve colorectal tumor mapping with PA technology?",{"text":118,"@type":114},"PA can be integrated with ultrasound, photoacoustic microscopy, and nanoparticle-enhanced imaging to map tissue structure, vascularity, and molecular markers. Combined with endoscopy and machine learning, it supports accurate, real-time detection.",{"name":120,"@type":111,"acceptedAnswer":121},"What levels of diagnostic performance have been reported for machine learning–enhanced PA imaging?",{"text":122,"@type":114},"Recent studies integrating machine learning with PA imaging report high diagnostic accuracy, including AUC values up to 0.96 and classification accuracies above 89%.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},369678,1790552147,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146},1099525198933,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","This article is licensed under CC-BY 4.0   \n[pubs.acs.org/journal/abseba](pubs.acs.org/journal/abseba)  Review   \nPhotoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis  \nShimul Biswas, Diya Pratish Chohan, Mrunmayee Wankhede, Jackson Rodrigues, Ganesh Bhat, Stanley Mathew, and Krishna Kishore Mahato *  \n Cite This: ACS Biomater. Sci. Eng. 2025, 11, 4033−4049  \nRead Online  \n\n|  |  |  |  |\n| --- | --- | --- | --- |\n| ACCESS   | Metrics & More |  |  Article Recommendations |\n\nABSTRACT: Colorectal cancer remains a major global health challenge, emphasizing the need for advanced diagnostic tools that enable early and accurate detection. Photoacoustic (PA) spectroscopy, a hybrid technique combining optical absorption with acoustic resolution, is emerging as a powerful tool in cancer diagnostics. It detects biochemical changes in biomolecules within the tumor microenvironment, aiding early identification of malignancies. Integration with modalities, such as ultrasound (US), photoacoustic microscopy (PAM), and nanoparticle-enhanced imaging, enables detailed mapping of tissue structure, vascularity, and molecular markers. When combined with endoscopy and machine learning (ML) for data analysis, PA technology offers real-time, minimally invasive, and highly accurate detection of colorectal tumors. This approach supports tumor classification, therapy monitoring, and detecting features like hypoxia and tumorassociated bacteria. Recent studies integrating machine learning with PA imaging have demonstrated high diagnostic accuracy, achieving area under the curve (AUC) values up to 0.96 and classification accuracies exceeding 89%, highlighting its potential for precise, noninvasive colorectal cancer detection. Continued advancements in nanoparticle design, molecular targeting, and ML analytics position PA as a key tool for personalized colorectal cancer management. KEYWORDS: photoacoustic, colorectal, cancer, multimodal, imaging  \n1. INTRODUCTION  \nColorectal cancer (CRC) is a major global health issue, ranking as the third most common cancer all over the globe with an estimated 19,26,425 new cases. It is also responsible for the second-highest number of deaths related to the disease, causing 9,04,019 fatalities according to GLOBACON 2022. Over 50% of colorectal cancer cases occur in Asia, highlighting the region’s substantial burden of this disease (Figure 1).1 These statistics underscore the critical need for enhanced screening, early detection, and effective treatment strategies.2 The World Health Organization anticipates that by 2030, 75 million individuals will experience CRC, with 17 million fatalities and 27 million new diagnoses projected.3 Recent analyses reported 154,270 new cases and 52,900 deaths from colorectal cancer in the United States in 2025.4 Globally, recent peer-reviewed research confirms that colorectal cancer remains the third most common cancer, with more than 1.9 million new cases and almost 900,000 deaths annually, and underscores the concerning rise in incidence among individuals under 50 years old.5 These trends highlight ongoing challenges in colorectal cancer prevention, early detection, and management.  \nUnderstanding the progression of colorectal cancer is vital as it progresses through distinct stages, starting from stage 0,  \nwhere abnormal cells are confined to the mucosa. Stage I shows growth into the muscular layer, while stage II involves deeper tissue penetration without lymph node involvement. Stage III indicates the spread to nearby lymph nodes, and stage IV, or metastatic cancer, marks the spread to distant organs like the liver and lungs, representing an advanced and more complex phase of the disease.6,7 Colorectal cancer develops through two main precursor pathways: the adenomacarcinoma pathway (70−90% of cases) and the serrated neoplasia pathway (10−20%).8,9 In the adenoma-carcinoma pathway, APC mutations trigger chromosomal instability, leading to tumor formation, often fo","cbCaircvxDPkNpWP","https://ap.wps.com/l/cbCaircvxDPkNpWP","pdf",9738712,17,"English","# Introduction\n## Colorectal cancer burden and need for screening\n## Disease stages and precursor pathways\n## Molecular mechanisms and emerging evaluation methods\n## Importance of early detection and diagnostic challenges\n## Advances in targets and personalized treatment","[{\"question\":\"What diagnostic capability does photoacoustic (PA) spectroscopy provide for colorectal cancer?\",\"answer\":\"PA spectroscopy combines optical absorption with acoustic resolution to detect biochemical changes in biomolecules within the tumor microenvironment. This supports early identification of malignancies.\"},{\"question\":\"How do multimodal integrations improve colorectal tumor mapping with PA technology?\",\"answer\":\"PA can be integrated with ultrasound, photoacoustic microscopy, and nanoparticle-enhanced imaging to map tissue structure, vascularity, and molecular markers. Combined with endoscopy and machine learning, it supports accurate, real-time detection.\"},{\"question\":\"What levels of diagnostic performance have been reported for machine learning–enhanced PA imaging?\",\"answer\":\"Recent studies integrating machine learning with PA imaging report high diagnostic accuracy, including AUC values up to 0.96 and classification accuracies above 89%.\"}]","Photoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis | PDF",1790184077,43]