Mode
Text Size
Log in / Sign up

Endoscopic techniques like ESD and EMR offer distinct advantages for early colon cancer managementDifferent Endoscopic Techniques Offer Different Benefits for Early Colon Cancer

AI-generated summary of the cited source, checked by automated accuracy review. How we work

Key Takeaway
Select endoscopic technique based on lesion morphology; AI shows promise for adenoma detection but lacks cancer data.

This narrative review synthesizes the clinical utility of various endoscopic techniques, including Endoscopic Mucosal Resection (EMR), Endoscopic Submucosal Dissection (ESD), and Endoscopic Full-Thickness Resection (EFTR), for managing early colon cancer. The authors argue that EMR is the primary approach for large, low-risk, nonpedunculated lesions due to efficiency, though it may limit histologic staging. ESD is preferred for lesions with suspected superficial submucosal invasion to allow for en bloc resection and more reliable pathologic assessment, despite higher technical demands and perforation risk.

EFTR is identified as a complementary role for specific small or fibrotic lesions, though the authors note that long-term oncologic evidence for this technique is less mature. Regarding technology, the review notes that while Artificial Intelligence improves adenoma detection in randomized trials, evidence for its use in predicting invasion depth or preventing interval cancer is currently insufficient for uncritical implementation.

Several limitations are noted, including heterogeneous lesion selection, varying operator expertise, and inconsistent outcome definitions across the literature. Clinical practice should involve selecting endoscopic techniques based on specific lesion morphology and risk profiles. While AI shows promise, its role in primary cancer management metrics is not yet sufficiently established.

How this fits prior evidence

This narrative review addresses a gap in the management of early colon cancer by evaluating specific endoscopic techniques. While prior coverage has addressed systemic treatments for metastatic colorectal cancer, the impact of visceral obesity on surgical outcomes, and pre-surgical prehabilitation, this review focuses on the technical nuances of endoscopic intervention. It provides specific guidance on choosing between EMR, ESD, and EFTR based on lesion characteristics.

Doctors use different endoscopic methods to treat early-stage colon cancer. This review looked at three main techniques: EMR, ESD, and EFTR. Each method has different strengths depending on the type of growth found during a procedure.

EMR is the most common method for large, low-risk lesions because it is efficient and generally safe. However, it can make it harder for doctors to see the full depth of the cancer. ESD is used for lesions where the cancer might have started to grow deeper. It allows for a single piece removal, which helps with staging, but it is more technically difficult and carries a higher risk of perforation. EFTR is used for specific, difficult-to-reach lesions, though more long-term data is needed.

Artificial intelligence is also being tested to help find polyps. While it shows promise for finding adenomas, there is currently not enough evidence to use AI for predicting cancer depth or improving survival rates. Because every case is different, doctors must choose the best tool based on the specific shape and risk of the lesion.

What this means for you:
Different endoscopic techniques are used based on the specific risk and size of the colon cancer lesion.

Common questions

What is the difference between EMR and ESD for colon cancer?

EMR is the primary method for large, low-risk lesions because it is efficient and safe. However, it may limit the ability to see the full depth of the cancer. ESD is used for lesions with suspected deeper invasion. It allows for a single piece removal for better staging but is more complex and carries a higher risk of perforation.

What is EFTR used for in colon cancer treatment?

EFTR is used as a complementary tool for specific types of lesions. These are typically small, fibrotic, or located in difficult areas. Because it is used for these specific cases, the long-term evidence regarding its success in preventing cancer recurrence is not yet fully established.

Can artificial intelligence help detect colon cancer?

Artificial intelligence has shown success in finding adenomas in randomized trials. However, there is currently not enough evidence to use AI for predicting how deep a cancer has invaded, preventing other cancers from forming, or improving overall survival rates. You should discuss these technologies with your doctor.

Study Details

Study typeSystematic review
EvidenceLevel 1
PublishedSep 2026
View Original Abstract ↓
Colorectal cancer remains a major cause of cancer morbidity and mortality, while screening and advances in endoscopic imaging have increased detection of lesions that may be amenable to organ-preserving treatment. Accurate assessment of morphology, optical pattern, and invasion depth is central to selecting among endoscopic mucosal resection (EMR), endoscopic submucosal dissection (ESD), endoscopic full-thickness resection (EFTR), and surgery. This structured narrative review synthesizes contemporary evidence and major society guidance on endoscopic diagnosis and treatment of early colon cancer, with particular attention to comparative effectiveness, evidence limitations, regional practice differences, surveillance, recurrence management, patient-centered decision-making, and implementation of artificial intelligence. EMR remains the principal approach for most large low-risk nonpedunculated lesions because of procedural efficiency and favorable safety, although piecemeal resection limits histologic staging and historically carries a higher risk of local recurrence. ESD provides en bloc resection and more reliable pathologic assessment for lesions with suspected superficial submucosal invasion or other features requiring precise staging, at the cost of longer procedures, greater technical demands, and higher perforation risk. EFTR has a complementary role for selected small non-lifting, fibrotic, or difficult-location lesions, but long-term oncologic evidence is less mature. Cross-study comparisons are limited by heterogeneous lesion selection, operator expertise, outcome definitions, and follow-up. Major European, Japanese, and US recommendations share a risk-based approach but differ in the practical positioning of ESD, reflecting regional expertise and referral infrastructure. Artificial intelligence improves adenoma detection in randomized trials, yet evidence for early cancer detection, invasion-depth prediction, interval cancer prevention, and survival remains insufficient for uncritical implementation. A structured, multidisciplinary approach that integrates lesion biology, local expertise, pathology, patient preferences, and the possibility of additional surgery after non-curative resection is essential.
Free Newsletter

Clinical research that matters. Delivered to your inbox.

Join thousands of clinicians and researchers. No spam, unsubscribe anytime.