Diffusion-weighted magnetic resonance imaging in oral and maxillofacial lesions: preliminary study on diagnostic ability of apparent diffusion coefficient maps

Optimizing diagnosis and surgical decisions for chronic osteomyelitis through radiomics in the precision medicine era

Introduction: Chronic osteomyelitis is a complex clinical condition that is associated with a high recurrence rate. Traditional surgical interventions often face challenges in achieving a balance between thorough debridement and managing resultant bone defects. Radiomics is an emerging technique that extracts quantitative features from medical images to reveal pathological information imperceptible to the naked eye. This study aims to investigate the potential of radiomics in optimizing osteomyelitis diagnosis and surgical treatment. Methods: Magnetic resonance imaging (MRI) scans of 93 suspected osteomyelitis patients were analyzed. Radiomics features were extracted from the original lesion region of interest (ROI) and an expanded ROI delineated by enlarging the original by 5 mm. Feature selection was performed and support vector machine (SVM) models were developed using the two ROI datasets. To assess the diagnostic efficacy of the established models, we conducted receiver operating characteristic (ROC) curve analysis, employing histopathological results as the reference standard. The model's performance was evaluated by calculating the area under the curve (AUC), sensitivity, specificity, and accuracy. Discrepancies in the ROC between the two models were evaluated using the DeLong method. All statistical analyses were carried out using Python, and a significance threshold of p < 0.05 was employed to determine statistical significance. Results and Discussion: A total of 1,037 radiomics features were extracted from each ROI. The expanded ROI model achieved significantly higher accuracy (0.894 vs. 0.821), sensitivity (0.947 vs. 0.857), specificity (0.842 vs. 0.785) and AUC (0.920 vs. 0.859) than the original ROI model. Key discriminative features included shape metrics and wavelet-filtered texture features. Radiomics analysis of MRI exhibits promising clinical translational potential in enhancing the diagnosis of chronic osteomyelitis by accurately delineating lesions and identifying surgical margins. The inclusion of an expanded ROI that encompasses perilesional tissue significantly improves diagnostic performance compared to solely focusing on the lesions. This study provides clinicians with a more precise and effective tool for diagnosis and surgical decision-making, ultimately leading to improved outcomes in this patient population.

Characteristic Mean Kurtosis Values in Simple Diffusion Kurtosis Imaging of Dentigerous Cysts

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10-6 mm2/s, OKC: 925 × 10-6 mm2/s, R: 2718 × 10-6 mm2/s, and M: 2686 × 10-6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts.

Evaluation of the efficacy of diffusion-weighted magnetic resonance imaging and apparent diffusion coefficients in the diagnosis of maxillary diseases

OBJECTIVE

We investigated the efficacy of using diffusion-weighted imaging (DWI) with quantitative apparent diffusion coefficient (ADC) mapping in the diagnosis of maxillary diseases.

STUDY DESIGN

We evaluated 146 cases of maxillary diseases (32 malignant tumors, 11 benign tumors, 28 maxillary cysts, 60 cases of maxillary sinusitis, and 15 maxillary sinus retention cysts) that had been examined using magnetic resonance imaging. The DWI sequence was obtained with b values of 0 and 800 s/mm2 and ADC values were calculated. We used one-way analysis of variance and the Tukey honestly significant difference test to identify differences within and between the types of diseases.

RESULTS

Mean ADC values for malignant tumors (1.07 × 10-3 mm2 s-1) were significantly lower than ADCs for benign tumors (1.85 × 10-3 mm2 s-1), maxillary cysts (1.77 × 10-3 mm2 s-1), maxillary sinusitis (2.34 × 10-3 mm2 s-1), and maxillary sinus retention cysts (2.52 × 10-3 mm2 s-1), with P < 0.001.   Mean ADC differed significantly between all disease types except between maxillary sinusitis and maxillary sinus retention cysts. ADC values also significantly differed between specific lesions within the malignant tumor and maxillary cyst groups.

CONCLUSIONS

The use of ADC values can be useful in the differential diagnosis of malignant maxillary diseases, benign lesions, cysts, and inflammatory and reactive conditions.

Virtual reality-based training and pre-operative planning for head and neck sentinel lymph node biopsy

OBJECTIVE

Sentinel lymph node biopsy (SLNB) is crucial for managing head and neck skin cancer. However, variable lymphatic drainage can complicate SLN detection when using Single-Photon Emission Computed Tomography (SPECT) or lymphoscintigraphy. Virtual Reality (VR) can contribute to pre-operative planning by simulating a realistic 3D model, which improves orientation. VR can also facilitate real-patient training outside the operating room. This study explored using a VR platform for pre-operative planning in head and neck skin cancer patients undergoing SLNBs and assessed its value for residential training.

MATERIALS AND METHODS

In this prospective technology pilot study, attending surgeons and residents who performed 21 SLNB operations on patients with head and neck skin cancers (81% males, mean age 69.2 ± 11.3) used a VR simulation model based on each patient's pre-operative SPECT scan to examine patient-specific anatomy. After surgery, they completed a questionnaire on the efficiency of the VR simulation as a pre-operative planning tool and training device for residents.

RESULTS

The attending surgeons rated the VR model's accuracy at 8.3 ± 1.6 out of 10. Three-quarters (76%) of residents reported increased confidence after using VR. The physicians rated the platform's contribution to residents' training at 7.4 ± 2.1 to 8.9 ± 1.3 out of 10.

CONCLUSION

A VR SLNB simulation can accurately portray marked sentinel lymph nodes. It was rated high as a surgical planning and teaching tool among attending surgeons and residents alike and may play a role in pre-operative planning and resident training. Further studies are needed to explore its applications in practice.

Diagnostic Efficacy of Diffusion-weighted Imaging in Distinguishing Chronic Diffuse Sclerosing Osteomyelitis from Suppurative Osteomyelitis of the Mandible

PURPOSE

Chronic diffuse sclerosing osteomyelitis (CDSO) is a non-suppurative inflammatory bone disease diagnosed based on combined clinical, histopathological, and radiological findings. Accurate diagnosis is important since CDSO is more refractory to treatment than suppurative osteomyelitis. The purpose of this study was to determine the diagnostic efficacy of diffusion-weighted imaging (DWI) in the quantitative assessment of CDSO to distinguish it from acute suppurative osteomyelitis (ASO) and chronic suppurative osteomyelitis (CSO) of the mandible.

METHODS

Using a retrospective cohort study design, we analyzed MRI data of 6 patients with CDSO and 34 patients with ASO and CSO. The mean apparent diffusion coefficient (ADC) values of the three groups (CDSO, ASO, and CSO groups) were calculated, and differences were analyzed using Kruskal-Wallis and post-hoc Mann-Whitney tests with Bonferroni adjustments. We performed a receiver operating characteristic (ROC) curve analysis to evaluate the ability of the ADC to predict CDSO. P < 0.05 was considered statistically significant.

RESULTS

The mean ADCs in the CDSO, ASO, and CSO groups were 1.22 ± 0.04 × 10-3 mm2/s, 1.28 ± 0.08 × 10-3 mm2/s, and 1.06 ± 0.09 × 10-3 mm2/s, respectively. Significant differences were observed between the ASO and CSO groups (P < 0.001) and CSO and CDSO groups (P < 0.01). However, there was no significant difference between the ASO and CDSO groups (P = 0.21). The ROC analysis revealed a cut-off ADC value of 1.19 for distinguishing the CSO group from the CDSO group. Sensitivity, specificity, accuracy, and area under the ROC curve were 1.0, 0.92, 0, 95, and 0.94, respectively.

CONCLUSION

The results suggest that ADC may be useful in distinguishing CDSO from mandibular suppurative osteomyelitis.

Quantitative analysis of masticatory muscle changes by Eichner index using diffusion-weighted imaging

OBJECTIVES

Diffusion-weighted imaging (DWI) provides quantitative functional information about the microscopic movement of water at the cellular level. However, few reports have quantitatively evaluated histological changes in masticatory muscles due to changes in occlusal relationships using DWI. This study aimed to assess the changes in masticatory muscles by Eichner index using DWI.

METHODS

We analyzed magnetic resonance imaging (MRI) studies of 201 patients from November 2017 to April 2018. Each Eichner index group, age, and sex were used as criterion variables, and the average apparent diffusion coefficient (ADC) values of the masticatory muscles were the explanatory variable. The mean ADC value differences were analyzed in each Eichner index group. We analyzed the data using the Kruskal-Wallis test and post hoc Mann-Whitney test with Bonferroni adjustment multiple regression analysis with Shapiro-Wilk test and Spearman's correlation coefficients. P < 0.05 was considered statistically significant.

RESULTS

The mean ADC values of each Eichner classification group were significantly different, with the lowest value in group C (P < 0.001). There was a negative correlation between the ADC value of the masseter, lateral pterygoid muscle, and age (P < 0.001). There were significant differences between the sex groups (P < 0.001).

CONCLUSIONS

ADC values of masticatory muscles were significantly different in the Eichner index groups. The ADC values of masticatory muscles may be useful for the quantitative evaluation of the masticatory muscles affected by the occlusal state.

Advanced imaging of head and neck infections

When head and neck infection is suspected, appropriate imaging contributes to treatment decisions and prognosis. While contrast-enhanced CT is the standard imaging modality for evaluating head and neck infections, MRI can better characterize the skull base, intracranial involvement, and osteomyelitis, implying that these are complementary techniques for a comprehensive assessment. Both CT and MRI are useful in the evaluation of abscesses and thrombophlebitis, while MRI is especially useful in the evaluation of intracranial inflammatory spread/abscess formation, differentiation of abscess from other conditions, evaluation of the presence and activity of inflammation and osteomyelitis, evaluation of mastoid extension in middle ear cholesteatoma, and evaluation of facial neuritis and labyrinthitis. Apparent diffusion coefficient derived from diffusion-weighted imaging is useful for differential diagnosis and treatment response of head and neck infections in various anatomical sites. Dynamic contrast-enhanced MRI perfusion may be useful in assessing the activity of skull base osteomyelitis. MR bone imaging may be of additional value in evaluating bony structures of the skull base and jaw. Dual-energy CT is helpful in reducing metal artifacts, evaluating deep neck abscess, and detecting salivary stones. Subtraction CT techniques are used to detect progressive bone-destructive changes and to reduce dental amalgam artifacts. This article provides a region-based approach to the imaging evaluation of head and neck infections, using both conventional and advanced imaging techniques.

Characteristic multimodal imaging of palatal follicular lymphoma: a case report on effectiveness of CT, diffusion-weighted MR imaging and intraoral ultrasonography

Oral lymphomas are relatively uncommon. Follicular lymphoma is the second most common subtype of non-Hodgkin lymphoma. We report characteristic multimodal imaging of palatal follicular lymphoma, especially CT, diffusion-weighted MR imaging (DWI) and intraoral ultrasonography. A 67-year-old woman presented with swelling on the right side of the palate within 2 months. On clinical examination, an approximately 35 × 20 mm mass lesion with elastic soft was found to overlay the right side of the palate. Contrast-enhanced CT image showed a mass with homogeneous enhancement on the right side of the palate, and bone tissue algorithm CT showed focal erosion of the right posterior maxilla. Regarding MR imaging, on T1-weighted image, the mass showed low signal intensity and homogeneous enhancement, and T2-weighted and STIR images revealed intermediate and high signal intensity, respectively. Furthermore, DWI and apparent diffusion coefficient (ADC) map showed high and low signal intensity, respectively. ADC value of the mass was 0.60 × 10^-3 mm²s^-1. On intraoral ultrasonography, the mass showed clear boundary, hypoechoic echogenicity, homogeneous internal architecture, vascular signals using color Doppler imaging and heterogeneous hard using strain elastography. A partial biopsy of the palatal region was performed. Histopathological diagnosis was follicular lymphoma. This case suggests that multimodal imaging, especially CT, DWI with ADC map and intraoral ultrasonography with color Doppler imaging and strain elastography, could be effective for evaluating palatal lesions.

Diagnostic utility of magnetic resonance imaging texture analysis in suppurative osteomyelitis of the mandible

PURPOSE

This study aimed to determine the diagnostic utility of magnetic resonance imaging (MRI) texture analysis for evaluating mandibular suppurative osteomyelitis (OM).

MATERIALS AND METHODS

In this retrospective cohort study, we analyzed the records of 50 patients with and without OM who underwent MRI between April 2019 and March 2021. The presence or absence of OM served as a predictor variable. The outcome variables were the texture features of the region of interest, which were analyzed. Quantitative parameters based on histogram features (90th percentile) and gray-level co-occurrence matrix (GLCM) features (Sum Averg) were calculated using short-tau inversion-recovery data with a region of interest. These six features out of 279 parameters were selected using Fisher, probability of error, and average correlation coefficient methods in MaZda. For the analysis of trivariate statistics, the post-Mann-Whitney test of the Kruskal-Wallis test with Bonferroni adjustment was used, and the p value was set to 0.05. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic effect of texture function to distinguish between acute and chronic diseases.

RESULTS

One histogram feature and five GLCM features showed differences among the non-OM patients, acute OM patients, and chronic OM patients (p < 0.05). The ROC analysis revealed a high area under the curve ranging from 0.91 to 0.96 for six texture features.

CONCLUSION

The six texture features of the mandibular bone marrow demonstrated differences among patients without and with acute and chronic OM. MRI texture analysis may facilitate accurate assessment of the mandibular OM stage.

Techniques, Tricks, and Stratagems of Oral Cavity Computed Tomography and Magnetic Resonance Imaging

The oral cavity constitutes a complex anatomical area that can be affected by many developmental, inflammatory, and tumoural diseases. MultiSlice Computed Tomography (MSCT) and Magnetic Resonance Imaging (MRI) currently represent the essential and complementary imaging techniques for detecting oral cavity abnormalities. Advanced MRI with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) has recently increased the ability to characterise oral lesions and distinguish disease recurrences from post therapy changes. The analysis of the oral cavity area via imaging techniques is also complicated both by mutual close appositions of different mucosal surfaces and metal artifacts from dental materials. Nevertheless, an exact identification of oral lesions is made possible thanks to dynamic manoeuvres and specific stratagems applicable on MSCT and MRI acquisitions. This study summarises the currently available imaging techniques for oral diseases, with particular attention to the role of DWI, DCE-PWI, and dynamic manoeuvres. We also propose MSCT and MRI acquisition protocols for an accurate study of the oral cavity area.

Magnetic resonance imaging texture analysis in the quantitative evaluation of acute osteomyelitis of the mandibular bone

OBJECTIVES

Accurate assessment of radiological images can help in early diagnosis and therapy of suppurative osteomyelitis (OM). The purpose of this study was to apply texture analysis to MRI as a means of quantitatively evaluating acute OM of the mandible.

METHODS

We analyzed the data from 38 patients who complained of pain and underwent MRI between April 2017 and March 2019. From the MRIs of these patients, with (n = 19) and without OM (n = 19), 279 radiomics features were extracted using short tau inversion recovery, data of the regions of interest and analyzed with MaZda v. 3.3. 10 features, including one histogram feature (90th percentile), eight gray-level co-occurrence matrix features (Sum Averg), and one gray-level run-length matrix feature (Horzl_RLNonUni), were selected using Fisher coefficient and compared between the acute OM and non-OM groups. The two groups were compared using Mann-Whitney U test with p value set at 0.05.

RESULTS

All 10 radiomics features showed significant differences between the acute OM and non-OM groups (p < 0.05).

CONCLUSIONS

MRI texture analysis has potential application in radiomics diagnosis of acute OM of the mandible.

Efficacy of diffusion-weighted magnetic resonance imaging in the diagnosis of osteomyelitis of the mandible

OBJECTIVE

This retrospective cohort study aimed to determine the diagnostic utility of apparent diffusion coefficient (ADC) values in the quantitative evaluation of mandibular osteomyelitis.

METHODS

We analyzed the records of 70 patients aged 30 to 90 years, with and without osteomyelitis, who underwent magnetic resonance imaging at the Nihon University School of Dentistry between April 2017 and March 2019. The mean ADC of bone marrow of patients without osteomyelitis and those with acute and chronic osteomyelitis of the mandible were calculated. Differences in ADC overall and in pair-wise comparisons were analyzed. Correlations with patient age were also calculated.

RESULTS

The mean ADC values in the nonosteomyelitis, acute osteomyelitis, and chronic osteomyelitis groups were 0.87 ± 0.15 × 10^-3, 1.24 ± 0.11 × 10^-3, and 1.07 ± 0.13 × 10^-3 mm²/s, respectively (P < .001 for all pair-wise comparisons). Receiver operating characteristic curve analysis revealed an ADC cut-off of 0.98 for osteomyelitis. Diagnostic values for predicting osteomyelitis were ≥ .81. No correlations of osteomyelitis with age were found.

CONCLUSIONS

The ADC was significantly higher in the osteomyelitis groups than in the nonosteomyelitis group. This suggests that ADC may be a useful parameter for quantitative evaluation of mandibular osteomyelitis.

The value of diffusion-weighted imaging in the diagnosis of medication-related osteonecrosis of the jaws

OBJECTIVE

The purpose of this study was to assess apparent diffusion coefficient (ADC) values associated with medication-related osteonecrosis of the jaws (MRONJ) at each stage of the disease compared to controls.

STUDY DESIGN

The magnetic resonance imaging data of 38 patients in the 4 stages of MRONJ and 10 controls were analyzed. Mean ADC values of bone marrow in the controls and patients in each stage of MRONJ were calculated. The significance of differences was analyzed by using the Kruskal-Wallis test and post-hoc Mann-Whitney tests with Bonferroni adjustment. A receiver operating characteristic (ROC) curve was plotted to distinguish controls from MRONJ stage 0. P < .05 was considered statistically significant.

RESULTS

The mean ADC values of controls and stages 0 to 3 were significantly different, with the lowest value in the controls (P < .001). ROC analysis revealed a cutoff ADC value of 1.06 × 10^-3 mm²/s to distinguish between the control group and MRONJ stage 0 patients, producing values of sensitivity, specificity, accuracy, and area under the ROC curve ranging from 0.89 to 0.94.

CONCLUSIONS

The ADC values of bone marrow affected by MRONJ are significantly different among controls and stages 0 to 3. ADC values may be useful for distinguishing normal from MRONJ stage 0.

Quantitative assessment of age-related changes in the mandibular bone marrow using apparent coefficient value

PURPOSE

The purpose of this study was to investigate the age-related changes in apparent diffusion coefficient (ADC) values of the mandibular bone marrow using diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

This retrospective cohort study comprised all patients who underwent pantomography and magnetic resonance imaging (MRI) between April 2018 and November 2020 at our institution. A total of 351 participants (140 men, 211 women), aged 15-89 years (mean age 46.01 years), were included in the study. Spearman's correlation coefficients were calculated using age groups as the criterion variable and the ADC values as the explanatory variables. P < 0.05 was considered statistically significant.

RESULTS

The mean ADC value for all age groups was 0.91 ± 0.18 in men and 0.86 ± 0.16 in women (p = 0.016). There was a significant negative correlation between age and the ADC values in each sex group (p < 0.001).

CONCLUSION

This study demonstrates that the normal ADC values of the mandibular bone marrow show significant negative correlation with increasing age. These findings will be useful in the diagnosis of bone marrow diseases.

Application of diffusion-weighted magnetic resonance imaging in the diagnosis of odontogenic lesions: a systematic review

OBJECTIVES

This systematic literature review addresses the use of diffusion-weighted magnetic resonance imaging (DWI) and apparent diffusion coefficient (ADC) for the evaluation of benign maxillomandibular odontogenic lesions.

STUDY DESIGN

Databases were searched, and original research studies or case report manuscripts up to April 2019 were included, using the keyword "diffusion," combined with the keywords "maxillofacial pathology," "oral pathology," "odontogenic tumors," "dental tissue neoplasms," "odontogenic cysts," and the histologic denomination of benign odontogenic lesions, according to the World Health Organization classification. Only English language articles and studies pertaining to DWI were selected.

RESULTS

Fifteen investigations (11 original articles and 4 case reports) of distinct benign odontogenic lesions were included. Most studies did not include exclusively odontogenic lesions in their samples.

CONCLUSIONS

It is too early to reach a conclusion that DWI and ADC can provide useful information in the differentiation of the histologic type of some benign odontogenic lesions on the basis of available data in the literature.

Differentiation of sublingual thyroglossal duct cyst from midline dermoid cyst with diffusion weighted imaging

PURPOSE

to differentiate sublingual thyroglossal duct cyst (TGDC) from midline dermoid cyst (DC) with diffusion weighted imaging (DWI).

MATERIALS AND METHODS

Retrospective analysis of 22 consecutive patients (11 male and 11 female aged 5-15 years) with midline cystic lesion at floor of mouth. They underwent DWI of floor of mouth. Apparent diffusion coefficient (ADC) of the cystic lesions was calculated and correlated with surgical findings.

RESULTS

The mean ADC value of TGDC of 1st observer was (2.20 ± 0.28 × 10^-3 mm²/s) and of 2nd observer was (2.28 ± 0.27 × 10^-3 mm²/s) was significantly higher than that of DC (P = 0.001) whose ADC of 1st observer was (1.55 ± 0.15 × 10^-3 mm²/s) and of 2nd observer was (1.53 ± 0.11 × 10^-3 mm²/s). There was excellent inter-observer agreement of both readings (r = 92%, P = 0.001). When ADC of 1.76 and 1.62 × 10^-3 mm²/s was used as a threshold value for differentiating TGDC from DC, the best results were obtained with area under the curve of 0.94 and 0.96, accuracy of 90% and 86%, sensitivity of 91% and 91%%, specificity of 90% and 80%, negative predictive value of 90% and 88% and positive predictive value of 92% and 84% of both reviewers respectively.

CONCLUSION

DWI is reliable and reproducible imaging modality for differentiation sublingual TGDC from DC.

AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics

INTRODUCTION

The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes.

OBJECTIVE

The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.

Tc-99m hydroxymethylene diphosphonate scintigraphy, computed tomography, and magnetic resonance imaging of osteonecrosis in the mandible: Osteoradionecrosis versus medication-related osteonecrosis of the jaw

Purpose

To present characteristic findings of Tc-99m hydroxymethylene diphosphonate (HMDP) scintigraphy, computed tomography (CT), and magnetic resonance (MR) imaging for osteonecrosis in the mandible, especially osteoradionecrosis (ORN) and medication-related osteonecrosis of the jaw (MRONJ).

Materials and Methods

Thirteen patients with MRONJ and 7 patients with ORN in the mandible underwent Tc-99m HMDP scintigraphy, CT, and MR imaging (T1-weighted images [T1WI], T2-weighted images [T2WI], short inversion time inversion recovery images [STIR]), diffusion-weighted images [DWI], and apparent diffusion coefficient [ADC] mapping). The associations of scintigraphy, CT, and MR imaging findings with MRONJ and ORN were analyzed using the chi-square test with the Pearson exact test.

Results

Thirteen patients with MRONJ and 7 patients with ORN in the mandible showed low signal intensity on T1WI and ADC mapping, high signal intensity on STIR and DWI, and increased uptake on scintigraphy. Periosteal bone proliferation on CT was observed in 69.2% of patients with MRONJ (9 of 13) versus 14.3% of patients with ORN (1 of 7) (P=0.019).

Conclusion

This study presented characteristic imaging findings of MRONJ and ORN on scintigraphy, CT, and MR imaging. Our results suggest that CT can be effective for detecting MRONJ and ORN.