Assessment of Hounsfield unit in the differential diagnosis of odontogenic cysts

Can Hounsfield unit density value accurately predict prelaryngeal invasion in laryngeal carcinoma cases

OBJECTIVE

The Hounsfield unit density value (HUDV) is a relative quantitative measurement of radio density used by radiologists in the interpretation of computed tomography (CT) images. Our aim is to investigate the role of HUDV in evaluating pre-epiglottic space (PES) involvement of laryngeal carcinoma.

METHODS

Seventy-four patients treated for laryngeal carcinoma in our clinic between 2014 and 2019 were included in the study. The invasion status of PES was determined radiologically and pathologically. HUDV was measured with a circular selected region of interest, with a constant size of 10 mm2 for PES. The relationship between patological PES invasion, radiological PES invasion, and HUDV was evaluated.

RESULTS

Measuring HUDV to determine PES invasion (74.3 %) was significantly higher than​​ conventional CT evaluation (59.5 %) (p = 0.001). The agreement coefficient (kappa value) of the conventional CT evaluation and the HUDV regarding PES involvement was 0.673, which was interpreted as 'good'.

CONCLUSION

HUDV could be used as an additional tool in diagnosing pre-epiglottic space invasion in laryngeal cancer.

Detection of bone marrow edema in differential diagnoses of odontogenic cysts using dual-energy computed tomography

PURPOSE

In this study, we prospectively investigated the relationship between bone marrow edema (BME) and odontogenic cysts and explored the possibility of using dual-energy computed tomography (DECT) as an auxiliary tool for the diagnosis of odontogenic cysts.

METHODS

This cross-sectional study included 73 patients who underwent the DECT scan and surgery for odontogenic cysts or odontogenic tumors. The virtual noncalcium (VNCa) computed tomography (CT) values and CT values were measured at several sites. The predictor variable was diagnosis, and the other variables included age, sex, and sites. The primary outcome was VNCa CT value. Variables were tested using the chi-square test or the Kruskal-Wallis test. The VNCa CT and CT values were tested using the Scheffe test for multiple comparisons. All variables were analyzed as independent variables affecting the VNCa CT values around the lesion in the multiple regression analysis.

RESULT

There were 35 men and 38 women. The mean patient age was 50.0 ± 19.5 years (range: 8-86). The VNCa CT values (- 6.2 ± 34.3) around the lesion in patients with RCs were significantly higher than those in patients with dentigerous cysts (- 44.4 ± 28.6) and odontogenic keratocysts (- 67.3 ± 19.5). In multiple regression analysis, the VNCa CT values around the lesion showed a significant positive correlation with histological results (regression coefficient: - 0.605, P < 0.001).

CONCLUSION

The presence of BME is associated with radicular cysts, and DECT can be used as an auxiliary tool for radicular cyst diagnosis.

High Endplate Hounsfield Units Value Indicate Intervertebral Disc Degeneration Following Transforaminal Lumbar Interbody Fusion Surgery

OBJECTIVE

Lumbar disc degeneration (LDD) is a common cause of low back pain and disability, and its prevalence increases with age. The aim of this study is to investigate whether endplate Hounsfield unit (HU) values have an effect on lumbar disc degeneration (LDD) after transforaminal lumbar interbody fusion (TLIF) surgery in patients with degenerative lumbar stenosis.

METHODS

This study was a retrospective analysis of patients who underwent TLIF surgery in January 2016 to October 2019. One hundred and fifty-seven patients who underwent TLIF surgery for degenerative lumbar stenosis were enrolled in this study. Demographic data was recorded. VAS and ODI values were compared to assess the surgical outcomes in patients with or without process of LDD after TLIF surgery. Correlation analysis was performed to investigate associations between LDD and endplate HU value. Binary logistic regression analysis was carried out to study relationships between the DDD and the multiple risk factors.

RESULTS

There was a statistically significant correlation between LDD, body mass index (BMI), age, paraspinal muscle atrophy, and total endplate scores (TEPS). Also, a strong and independent association between endplate HU value and LDD was found at every lumbar disc level (p < 0.01). After conditioning on matching factors, multivariate logistic regression analysis showed that higher endplate HU (odds ratio [OR]: 1.003, p = 0.003), higher TEPS (OR: 1.264, p = 0.002), higher BMI (odds ratio [OR]: 1.202, p = 0.002), a smaller cross-sectional area (CSA) of the paraspinal muscle preoperatively (OR: 0.096, p < 0.001) were significant predictors of LDD development after TLIF surgery.

CONCLUSIONS

There is a significant association between LDD and endplate HU value after TLIF surgery in patients with degenerative lumbar stenosis. Beyond that, results from this study provide a mechanism by which high endplate HU value predisposes to LDD after TLIF surgery.

Novel Three-Dimensional and Non-Invasive Diagnostic Approach for Distinction between Odontogenic Keratocysts and Ameloblastomas

Aim of this study was to demonstrate the diagnostic ability to differentiate odontogenic keratocysts (OKCs) from ameloblastomas (AMs) based on computed tomography (CT) or cone beam computed tomography (CBCT) scans. Preoperative CT and CBCT scans from 2004 to 2019 of OKCs and AMs were analyzed in 51 participants. Lesions were three-dimensionally (3D) assessed and Hounsfield units (HU) as well as gray scale values (GSV) were quantified. Calculated HU spectra were compared within the same imaging modalities using unpaired t-tests and correlated with participants characteristics by calculating Pearsons correlation coefficients. Within the CT scans, AMs had highly significantly higher HU values compared to OKCs (43.52 HU and 19.79 HU, respectively; p < 0.0001). Analogous, within the CBCT scans, AMs had significantly higher GSV compared to OKCs (-413.76 HU and -564.76 HU, respectively; p = 0.0376). These findings were independent from participants' gender and age, anatomical site, and lesion size, indicating that the HU- and GSV-based difference reflects an individual configuration of the lesion. HU and GSV spectra calculated from CT and CBCT scans can be used to discriminate between OKCs and AMs. This diagnostic approach represents a faster and non-invasive option for preoperative diagnosis of such entities and has potential to facilitate therapeutic decision making.

Improved Diagnostic Accuracy of Ameloblastoma and Odontogenic Keratocyst on Cone-Beam CT by Artificial Intelligence

OBJECTIVE

The purpose of this study was to utilize a convolutional neural network (CNN) to make preoperative differential diagnoses between ameloblastoma (AME) and odontogenic keratocyst (OKC) on cone-beam CT (CBCT).

METHODS

The CBCT images of 178 AMEs and 172 OKCs were retrospectively retrieved from the Hospital of Stomatology, Wuhan University. The datasets were randomly split into a training dataset of 272 cases and a testing dataset of 78 cases. Slices comprising lesions were retained and then cropped to suitable patches for training. The Inception v3 deep learning algorithm was utilized, and its diagnostic performance was compared with that of oral and maxillofacial surgeons.

RESULTS

The sensitivity, specificity, accuracy, and F1 score were 87.2%, 82.1%, 84.6%, and 85.0%, respectively. Furthermore, the average scores of the same indexes for 7 senior oral and maxillofacial surgeons were 60.0%, 71.4%, 65.7%, and 63.6%, respectively, and those of 30 junior oral and maxillofacial surgeons were 63.9%, 53.2%, 58.5%, and 60.7%, respectively.

CONCLUSION

The deep learning model was able to differentiate these two lesions with better diagnostic accuracy than clinical surgeons. The results indicate that the CNN may provide assistance for clinical diagnosis, especially for inexperienced surgeons.

Novel recurrence risk stratification of odontogenic keratocysts: A systematic review

The aim of this study was to identify all clinical, radiological, histopathological, and immunohistochemical features associated with recurrence of odontogenic keratocysts (OKCs) in the literature and formulate a recurrence risk stratification based on these findings. A search was performed in PubMed/Medline, Scopus, Web of Science, Google Scholar and Cochrane databases for clinical and laboratory studies reporting on clinico-pathological features that led to OKC recurrences for the period 2000 to 2020. Twenty-three studies were identified and analyzed qualitatively. A total of 2064 OKCs were included of which 439 OKCs were recurrent with a mean follow-up period of 46.7 months. Significantly associated parameters with OKC recurrence included age (variable age categories), large (>4 cm), multilocular lesions with cortical perforation, association with dentition, presence of daughter cysts, and epithelial budding. Immunohistochemical markers including high Ki67 index and AgNOR count were also implicated. A recurrence risk stratification was formulated based on these findings. Although the level of evidence from the included studies was low, there was considerable evidence that the clinico-pathological parameters identified were linked with higher OKC recurrence. The surgeon, radiologist, and pathologist should aim to identify these features when making a diagnosis so as to determine the appropriate management regime and prevent recurrences.