Picture That Cavity: Comparing Modalities for Cavity Detection

Dental cavities are one of the most prevalent chronic diseases globally. As such, it is crucial to be able to identify and diagnose them before they begin to cause pain, sensitivity and infection. In 1896, the first known dental x-ray was exposed, paving the way for modern dentistry as we know it. However, newer technologies are emerging that are proving to be potentially safer and more effective alternatives. One such advancement is near-infrared imaging (NIRI) which uses near-infrared light to detect demineralization in teeth without the use of radiation. With increased awareness about the effects of radiation exposure and a growing push for less invasive technologies, NIRI may become a more common tool in modern dentistry. As dental technology evolves it is crucial to determine whether newer methods can match or exceed the effectiveness of conventional techniques.

The findings of this project will be able to assist dental professionals diagnose and treat cavities, sometimes at their earliest stages, more conservatively with remineralization strategies like high concentration fluoride before they become larger and potentially more problematic.

QUESTION

How does the accuracy of NIRI compare to traditional bitewing x-rays when trying to detect dental cavities?

HYPOTHESIS

NIRI will detect cavities with a higher accuracy than bitewing x-rays because NIRI is able to detect smaller lesions in enamel before they penetrate the dentin which bitewings cannot do well.

VARIABLES

Independent: Imaging method used to detect cavities (Bitewing x-rays/NIRI)

Dependent: Compared accuracy in detecting cavities between NIRI and bitewing x-rays

Controlled: Ensuring NIRI and bitewing are from the same patient; having the same dentist analyze the images; the number of cases used for each comparison; the same standard of cavity diagnosis

MATERIALS

Dental x-ray unit to capture bitewing x-rays

iTero Element digital scanner with NIRI scanning wand

70 anonymous patient records containing both NIRI scans and bitewings

Dental professional to interpret/analyze images

Table to record data

EXPERIMENTAL DESIGN

Identify a dentist that can provide patient records and verify presence or absence of cavities on bitewing x-rays and NIRI scans.

Collect matched pairs of NIRI scans and bitewings from 70 anonymous patients.

Randomize the order so that only the experimenter knows which pair of images are from the same patient.

Evaluate the images - the dental professional will examine the NIRI and x-ray images. The order in which they will view the images is randomized so that the matched pair is not seen together. This will prevent bias when assessing images.

Record the number of cavities detected on each image.

Analyze the data.

RESULTS AND ANALYSIS

Based on my observations and analysis of 70 patient samples, it was found that 115 cavities were detected by NIRI. Of those, 85 cavities were detected by NIRI alone and not seen on the corresponding bitewing x-rays. A total of 61 cavities were detected by bitewings. Of those, 31 were found only on the x-ray and did not appear on the corresponding NIRI scan. 30 of the cavities that were identified were seen on matching sets of both NIRI scans and bitewing x-rays.

The bar graph in the figure above displays the accuracy of NIRI scans versus bitewing x-rays in detecting cavities. This is represented by the number of cavities found by each method. The length of each bar displays the total number of cavities detected by each individual method i.e. NIRI or bitewing. The darker blue part of each bar that is located on the bottom represents the cavities that were specific to that method or those that the other method did not detect. The lighter blue part on top represents the cavities that were seen on both methods together.

Based on my observations, it was found that NIRI was more accurate than bitewing x-rays in detecting cavities as it found a total of 115 cavities versus bitewings that found 61. More cavities were found on NIRI scans alone and this is likely due to the fact that NIRI can detect very small or early cavities that are often not seen on x-rays due to their size. It is only when cavities reach a certain point and begin to break through the enamel layer and invade the dentin that bitewings will start to pick them up. 30 of the cavities detected had reached this large enough size to be seen on both the NIRI scan and the bitewing x-ray. When analyzing the results of those cavities detected by bitewing x-rays only, there were 31 cavities that were seen on the x-ray but not detected by NIRI. Upon further investigation, it was found that all 31 of these cavities were located underneath old dental restorations such as fillings and crowns. The presence of these restorations blocks the penetration of near infrared light through the tooth causing the image on the scan to appear darker or blurry, and as such, it is not possible to see what is happening below the restoration. When considering the electromagnetic spectrum of light, x-rays have a shorter wavelength and more energy allowing them to pass through restorations, and thus, being able to diagnose decay in these areas.

The results of this experiment demonstrate that near-infrared imaging is an accurate tool to diagnose dental cavities and that it is more effective than bitewing x-rays when detecting smaller, early cavity lesions. This proves my hypothesis correct. However, although NIRI detected more cavities than bitewings overall and was able to see smaller cavities that bitewings did not pick up, it is important to note that bitewings also showed cavities that were not detected on the NIRI scan as these cavities were under existing dental restorations. This demonstrates the usefulness and need for both tools in the dental setting when diagnosing dental cavities.

The findings of this project could be very useful in a dental setting. Knowing that cavities are such a prevalent chronic disease, dental professionals should try and take a more preventative approach to their treatment, rather than a reactive one when cavities are too large to be remineralized. By taking a NIRI scan on a patient, in addition to traditional x-rays, a dental professional will be much better equipped to educate their patients and help them to take better care of their overall oral health. Recommendations to patients like high fluoride toothpastes which help to remineralize early enamel lesions before they penetrate into dentin, or products that contain xylitol that helps reduce the presence of cavity causing bacteria in the mouth can be very useful if they are prescribed at the earliest stage of cavity development.

Future considerations for this study may include correlating the NIRI scan data with clinical findings during cavity treatment in a dental office to see if the scan data was accurate in predicting the depth/size of the actual cavity. Another consideration could be to place a patient on a preventative regimen of high fluoride after a cavity is detected on a NIRI scan to determine its ability to reverse demineralization. Finally, the usefulness of other radiation-free diagnostic technologies like saliva testing for cavity causing bacteria can be tested to see how they compare to the accuracy of NIRI scans.

ACKNOWLEDGMENTS

I am grateful for the help of my dentist Dr. Nureen Somani and her team at Donsdale Dental for providing me with their time, resources, and support throughout this endeavor. Dr. Somani’s analysis has been instrumental in completing this experiment.

I also wish to extend my thanks to Ms. Corrigan, my science teacher, and the ERSF core team for their support and constructive feedback. Their willingness to provide feedback and answer my questions allowed me to complete this experiment successfully.

Lastly, I would like to thank Align Technology for the development of the iTero Digital Scanner and the NIRI analysis software. The knowledge that I gained from using this technology is immeasurable.

REFERENCES

Hagi, F. S. (2023, March 3). The History of Dental Radiology: A Review. Bulletin of National Institute of Health Sciences. Retrieved October 17, 2025, from https://www.healthsciencesbulletin.com/volume/BNIHS/141/03/the-history-of-dental-radiology-a-review-642a8981437ec.pdf

Dawes, C. (n.d.). Journal of the Canadian Dental Association 722 December 2003, vol. 69, no. 11. Canadian Dental Association. https://www.cda-adc.ca/jcda/vol-69/issue-11/722.pdf

Sulyanto, R. (2024). Biology of the Teeth - Mouth and Dental Disorders - Merck Manual Consumer Version. Merck Manuals. Retrieved October 17, 2025, from https://www.merckmanuals.com/home/mouth-and-dental-disorders/biology-of-the-mouth-and-teeth/biology-of-the-teeth

Vorster, M. (n.d.). (PDF) New Clinical Innovations to ensure predictable class II posterior composite resin restorations. https://www.researchgate.net/publication/327473836_New_clinical_innovations_to_ensure_predictable_Class_II_posterior_composite_resin_restorations

Can you remineralize teeth? | expert tips | colgate. Colgate. (n.d.). https://www.colgate.com/en-us/oral-health/cavities/can-you-remineralize-teeth

Cavities (tooth decay): Symptoms, causes & treatment. Cleveland Clinic. (2025, August 18). https://my.clevelandclinic.org/health/diseases/10946-cavities

IAEA. (2017, August 7). Radiation protection in dental radiology. IAEA. https://www.iaea.org/resources/rpop/health-professionals/dentistry

Intraoral scanners for restorative and Orthodontic Dentistry. (n.d.). https://itero.com/en-APAC/grow-your-practice/diagnostic