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Irrigating the root canal: A case report

Post-operative radiograph (Image: Dr Vittorio Franco, UK and Italy)
Dr Vittorio Franco, UK and Italy

Dr Vittorio Franco, UK and Italy

Mon. 22. January 2018

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The patient reported on in this article is a student in dentistry and his parents are both dentists. They referred their son to a good endodontist, who then referred the case to me. As always, peers are more than welcome in either of my practices, in Rome and London, so when I treated this case, I had three dentists watching me, a future dentist on the chair, placing a great deal of pressure on me.

The 22-year-old male patient had a history of trauma to his maxillary incisors and arrived at my practice with symptoms related to tooth #21. The tooth, opened in an emergency by the patient’s mother, was tender when prodded, with a moderate level of sensitivity on the respective buccal gingiva. Sensitivity tests were negative for the other central incisor (tooth #12 was positive), and a periapical radiograph showed radiolucency in the periapical areas of both of the central incisors. The apices of these teeth were quite wide and the length of teeth appeared to exceed 25 mm.

My treatment plan was as follows: root canal therapy with two apical plugs with a calcium silicate-based bioactive cement. The patient provided his consent for the treatment of the affected tooth and asked to have the other treated in a subsequent visit.

After isolating with a rubber dam, I removed the temporary filling, and then the entire pulp chamber roof with a low-speed round drill. The working length was immediately evaluated using an electronic apex locator and a 31 mm K-type file. The working length was determined to be 28 mm.

As can be seen in the photographs, the canal was actually quite wide, so I decided to only use an irrigating solution and not a shaping instrument. Root canals are usually shaped so that there will be enough space for proper irrigation and a proper shape for obturation. This usually means giving these canals a tapered shape to ensure good control when obturating. With open apices, a conical shape is not needed, and often there is enough space for placing the irrigating solution deep and close to the apex.

I decided to use only some syringes containing 5 per cent sodium hypochlorite and EDDY, a sonic tip produced by VDW, for delivery of the cleaning solution and to promote turbulence in the endodontic space and shear stress on the canal walls in order to remove the necrotic tissue faster and more effectively. After a rinse with sodium hypochlorite, the sonic tip was moved to and from the working length of the canal for 30 seconds. This procedure was repeated until the sodium hypochlorite seemed to become ineffective, was clear and had no bubbles. I did not use EDTA, as no debris or smear layer was produced.

I suctioned the sodium hypochlorite, checked the working length with a paper point and then obturated the canal with a of 3 mm in thickness plug of bioactive cement. I then took a radiograph before obturating the rest of the canal with warm gutta-percha. I used a compomer as a temporary filling material.

The symptoms resolved, so I conducted the second treatment only after some months, when the tooth #11 became tender. Tooth #21 had healed. I performed the same procedure and obtained the same outcome (the four-month follow-up radiograph showed healing).

Editorial note: A complete list of references are available from the publisher. This article was published in roots - international magazine of endodontology No. 04/2017.

One thought on “Irrigating the root canal: A case report

  1. The ultimate reason why root canals fail is bacteria. If our mouths were sterile there would be no decay or infection, and damaged teeth could, in ways, repair themselves. So although we can attribute nearly all root canal failure to the presence of bacteria, I will discuss five common reasons why root canals fail, and why at least four of them are mostly preventable.

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Does AI affect treatment decision-making and outcomes?

A new study has shown that while artificial intelligence demonstrated unequivocal capabilities in the diagnostic sphere, its reliability and efficacy in terms of treatment planning and patient outcomes requires further interrogation. (Image: unai/Adobe Stock)

RIYADH, Saudi Arabia: While many artificial intelligence (AI) systems for dental diagnosis demonstrate high accuracy, their real clinical value depends on their influence on treatment decision-making and patient outcomes. A new systematic review and meta-analysis has investigated this and presents the evidence so far on both the potential and the limitations of AI across specialties in clinical practice.

Crucially, the review moves beyond technical performance to assess how AI affects clinicians’ diagnostic judgement in practice. The evidence shows that AI assistance improved clinicians diagnostic performance and increased diagnostic agreement between clinicians interpreting the same images, suggesting that these systems can reduce variability in radiographic interpretation and serve as reliable adjuncts to clinical judgement.

AI also appears to contribute to faster diagnostic judgement and improved workflow efficiency. The review found that diagnostic tasks that typically require significant time can be completed far more quickly with AI support, without compromising accuracy, and that AI can help clinicians identify the location of abnormalities more accurately on dental images.

However, the review highlights an important evidence gap. While AI appears to support treatment planning indirectly by improving image interpretation and clinicians’ confidence in diagnosis, the review could draw no conclusions regarding its impact on treatment decisions and success. Evidence on treatment planning was limited by the small number of studies, variation in their clinical contexts and the absence of patient-centred outcomes.

Across multiple studies, the review found that AI systems demonstrated high accuracy in analysing dental images, particularly in detecting disease, identifying teeth and delineating anatomical boundaries, supporting diagnostic interpretation across different dental imaging contexts. However, differences in AI models, imaging techniques and validation methods led to high variability in diagnostic performance across dental tasks and clinical settings. Also, many studies relied on retrospective data, and few included external validation. This raises concerns about how well the findings apply across routine clinical settings.

Overall, AI shows strong potential to enhance diagnostic decision-making and support treatment planning, particularly as a tool to augment clinician judgement, something of central importance also to the patient experience. However, its true impact on treatment planning and patient outcomes remains unclear, and the authors point out that robust prospective research is needed to confirm its clinical value in routine practice.

The article, titled “Artificial intelligence in dental treatment planning and diagnostic decision‐making: A systematic review and meta‐analysis”, was published online in the April 2026 issue of Clinical and Experimental Dental Research.

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