Hostname: page-component-745bb68f8f-grxwn Total loading time: 0 Render date: 2025-02-11T08:18:52.415Z Has data issue: false hasContentIssue false
  • English
  • Français

Prediction of skull base osteomyelitis in necrotising otitis externa with diffusion-weighted imaging

Published online by Cambridge University Press:  05 June 2020

A A K Abdel Razek  and
W Mahmoud
A A K Abdel Razek*
Affiliation:
Department of Diagnostic Radiology, Mansoura University Faculty of Medicine, Mansoura, Egypt
W Mahmoud
Affiliation:
Department of Diagnostic Radiology, Mansoura University Faculty of Medicine, Mansoura, Egypt
*
Author for correspondence: Dr Ahmed Abdel Khalek Abdel Razek, Department of Diagnostic Radiology, Mansoura University Faculty of Medicine, Elgomheryia Street, Mansoura, Egypt3512 E-mail: arazek@mans.edu.eg Fax: +20 502 259 146
Rights & Permissions [Opens in a new window]

Abstract

Objective

To predict skull base osteomyelitis in patients with necrotising otitis externa using diffusion-weighted imaging.

Methods

A retrospective analysis was conducted of 25 necrotising otitis externa patients with skull base osteomyelitis (n = 10) or without skull base involvement (n = 14) who underwent a single-shot diffusion-weighted imaging of the skull base.

Results

The respective mean apparent diffusion coefficient values of the skull base, as determined by two reviewers, were 0.851 ± 0.15 and 0.841 ± 0.14 ×10-3mm2/s for the skull base osteomyelitis patients, and 1.065 ± 0.19 and 1.045 ± 0.20 ×10-3mm2/s for the necrotising otitis externa patients without skull base involvement. The difference in apparent diffusion coefficients between the groups was significant, for both reviewers (p = 0.008 and 0.012). The optimal threshold apparent diffusion coefficient for predicting skull base osteomyelitis in necrotising otitis externa patients was 0.945 ×10-3mm2/s and 0.915 ×10-3mm2/s, with an area under the curve of 0.825 and 0.800, accuracy of 87.5 and 83.3 per cent, sensitivity of 85.7 and 90.0 per cent, and specificity of 90.0 and 78.6 per cent, for each reviewer respectively.

Conclusion

Apparent diffusion coefficient is a non-invasive imaging parameter useful for predicting skull base osteomyelitis in necrotising otitis externa patients.

Keywords

Magnetic Resonance ImagingOsteomyelitisInfectionOtitis ExternaSkull Base
Type
Main Articles
Information
The Journal of Laryngology & Otology , Volume 134 , Issue 5 , May 2020 , pp. 404 - 408
Copyright
Copyright © JLO (1984) Limited, 2020

Introduction

Necrotising otitis externa is an invasive infectious process of the external auditory canal that may extend into the skull base.Reference Peled, El-Seid, Bahat-Dinur, Tzvi-Ran, Kraus and Kaplan1–Reference Peled, Kraus and Kaplan3 Skull base osteomyelitis is a rare but serious and life-threatening complication that is mostly secondary to necrotising otitis externa. The mortality rate of skull base osteomyelitis is 33 per cent, reaching up to 80 per cent in patients with cranial nerve involvement.Reference Hatch, Bauschard, Nguyen, Lambert, Meyer and McRackan4–Reference Kornilenko, Rocka, Balseris and Arechvo8 The management for patients with skull base osteomyelitis is different from that for patients with necrotising otitis externa without skull base involvement. Surgery may be used in the treatment of skull base osteomyelitis, especially when there is cranial nerve involvement.Reference Le Clerc, Verillaud, Duet, Guichard, Herman and Kania7–Reference Chen, Yeh, Shiao and Tu9

Imaging is used for the assessment of skull base osteomyelitis, but the results overlapping with imaging findings for necrotising otitis externa.Reference van Kroonenburgh, van der Meer, Bothof, van Tilburg, van Tongeren and Postma10–Reference Razek and Huang12 Routine magnetic resonance imaging (MRI) and isotope studies are used for the prediction of skull base osteomyelitis, but their results are non-specific.Reference Goh, Karandikar, Loke and Tan13–Reference Rozenblum-Beddok, Verillaud, Paycha, Vironneau, Abulizi and Benada15 Diffusion-weighted imaging offers better characterisation of the soft tissues and their physiological processes because it reflects the random motion of the water protons, which is disturbed by the intracellular organelles and macromolecules located within the tissues.Reference Abdel Razek and Kamal16,Reference Abdel Razek, Mossad and Ghonim17 Diffusion-weighted imaging is commonly used for the assessment of head and neck cancer,Reference Abdel Razek, Mossad and Ghonim17,Reference Connolly and Srinivasan18 soft tissue infection,Reference Abd-El Khalek Abd-ALRazek and Fahmy19,Reference Schmid-Tannwald, Schmid-Tannwald, Morelli, Albert, Braunagel and Trumm20 and bone infection with osteomyelitis.Reference Ozgen, Oguz and Cila21–Reference Abdel Razek and Samir23 It is commonly used in the assessment of middle-ear cholesteatoma and recently in the characterisation of external-ear masses.Reference Lingam and Bassett24,Reference Razek25

Only one study has discussed the role of diffusion-weighted imaging in the follow up of patients with necrotising otitis externa.Reference Cherko, Nash, Singh and Lingam26 To our knowledge, no previous study in the English literature has investigated the role of diffusion-weighted imaging for predicting skull base osteomyelitis in necrotising otitis externa patients. This work aimed to predict skull base osteomyelitis in patients with necrotising otitis externa using diffusion-weighted imaging.

Materials and methods

Patients

This study was approved by the ethics board; the need for patients’ informed consent was waived given that this is a retrospective study. A retrospective analysis was conducted of the magnetic resonance images of patients with necrotising otitis externa. The inclusion criteria were patients with necrotising otitis externa who underwent diffusion-weighted imaging. We excluded only one patient from the study, because of motion artefacts.

A total of 24 patients were included in this study (18 males and 6 females), with a mean age of 53 years (age range, 44–62 years). These patients presented with: external-ear swelling (n = 24), headache (n = 24), otalgia (n = 24), otorrhoea (n = 19), trismus (n = 18) and cranial nerve palsy (n = 8). All patients were diabetic and the final diagnosis was confirmed via biopsy. Patients were classified according to skull base involvement and spilt into two groups accordingly: necrotising otitis externa without skull base involvement (n = 14), or necrotising otitis externa with skull base osteomyelitis (n = 10).

Routine magnetic resonance imaging

Magnetic resonance imaging of the petrous bone was performed on a 1.5 Tesla Symphony scanner (Siemens, Munich, Germany) using a head coil with a circular polarised surface. All patients underwent axial T1-weighted imaging (repetition time = 800 ms, echo time = 15 ms) and axial T2-weighted imaging (repetition time = 800 ms, echo time = 20 ms), with section thickness of 3 mm, an interslice gap of 1–2 mm, and field of view of 25 × 20 cm. Axial, contrast-enhanced, T1-weighted images (repetition time = 800 ms, echo time = 15 ms) were obtained after an intravenous bolus injection of gadopentetate gadolinium (0.1 ml/kg of body weight).

Diffusion-weighted imaging

A single-shot echo-planar imaging diffusion-weighted imaging (‘EPI-DWI’) sequence was used prior to contrast medium injection with b-values of 0, 500 and 1000 s/mm2. The imaging parameters were: repetition time = 1000 ms, echo time = 108 ms, field of view = 25 × 20 cm and section thickness = 5 mm, with an interslice gap of 1–2 mm. The apparent diffusion coefficient map was automatically constructed.

Image analysis

Image analysis was performed by two radiologists (AA and WM) with 30 and 11 years’ respective experience in head and neck imaging. They independently calculated the apparent diffusion coefficient of the skull base lesion; the radiologists were blinded to the patient data and the final diagnosis. A region of interest was drawn on the apparent diffusion coefficient map using an electronic cursor at the skull base lesion, and the apparent diffusion coefficient value of the lesion was calculated.

Statistical analysis

The data were described in terms of mean and standard deviation values. The data were analysed to determine statistically significant differences. The student's t-test was used to compare the two groups (necrotising otitis externa patients with or without skull base involvement). The p-value was considered significant if 0.05 or lower. Receiver operating characteristic curves were used to determine the optimal threshold apparent diffusion coefficient for predicting skull base osteomyelitis in patients with necrotising otitis externa. The data were statistically analysed using SPSS software version 22 (SPSS, Chicago, Illinois, USA).

Results

All patients with suspected skull base osteomyelitis presented with otalgia and otorrhoea; 34 per cent had cranial nerve palsies and 17 per cent had hearing loss. Culture was positive for Pseudomonas aeruginosa in 12 patients (50 per cent). Staphylococcus aureus was the causative organism in 8 patients (34 per cent). Fungal infection was found in two patients. The causative organism was difficult to detect in two patients in light of antibiotics given prior to MRI.

The mean apparent diffusion coefficient of the skull base in patients with skull base osteomyelitis (n = 10) (Figure 1) was 0.851 ± 0.15 ×10-3mm2/s (range, 0.72–1.23 ×10-3mm2/s) for the first reviewer and 0.841 ± 0.14 ×10-3mm2/s (range, 0.74–1.20) for the second reviewer (Table 1). The mean apparent diffusion coefficient of the skull base in patients with necrotising otitis externa without skull base involvement (n = 14) (Figure 2) was 1.065 ± 0.19 ×10-3mm2/s (range, 0.73–1.32 ×10-3mm2/s) for the first reviewer and 1.045 ± 0.20 ×10-3mm2/s (range, 0.73–1.30 ×10-3mm2/s) for the second reviewer. There was a significant difference in the apparent diffusion coefficient of the skull base between necrotising otitis externa patients with and without skull base osteomyelitis for the first reviewer (p = 0.008) and for the second reviewer (p = 0.012). Only one patient with skull base osteomyelitis was determined to have a high apparent diffusion coefficient of the skull base by both reviewers who was misdiagnosed as having an uninvolved skull base.

Fig. 1. Necrotising otitis externa with skull base osteomyelitis. (a) Axial, contrast-enhanced magnetic resonance imaging scan shows diffuse enhancing lesion infiltrating the right masticator space in a patient with necrotising otitis externa. The lesion extends into the skull base bone marrow on the right side. Note abnormal marrow signal intensity of the ramus of the right mandible, denoting osteomyelitis of the mandible. (b) Apparent diffusion coefficient map shows low apparent diffusion coefficient values for the bony lesion of the skull base (arrows), with calculated apparent diffusion coefficient values of 0.83 and 0.79 ×10-3mm2/s for each reviewer respectively.

Fig. 2. Necrotising otitis externa without skull base involvement. (a) Axial, contrast-enhanced magnetic resonance imaging scan shows diffuse enhancing lesion infiltrating the left masticator space in a patient with necrotising otitis externa. The lesion extends into the skull base bone marrow on the left side. (b) Apparent diffusion coefficient map shows high apparent diffusion coefficient values for the bony lesion of the skull base (arrows), with calculated apparent diffusion coefficient values of 1.21 and 1.17 ×10-3mm2/s for each reviewer respectively.

Table 1. Mean apparent diffusion coefficients of skull base in necrotising otitis externa patients with and without skull base osteomyelitis

Data represent mean (± standard deviation) apparent diffusion coefficients (10-3mm2/s), with ranges in parentheses, unless indicated otherwise. *n = 10; †n = 14

The apparent diffusion coefficients of 0.945 and 0.915 ×10-3mm2/s were optimal threshold values for predicting skull base osteomyelitis in necrotising otitis externa patients, with area under the curve values of 0.825 and 0.800, accuracy of 87.5 per cent and 83.3 per cent, sensitivity of 85.7 per cent and 90.0 per cent, specificity of 90.0 per cent and 78.6 per cent, positive predictive values of 92.3 per cent and 75.0 per cent, and negative predictive values of 81.8 per cent and 91.7 per cent, for each reviewer respectively (Table 2 and Figure 3).

Fig. 3. Receiver operating characteristic curve. The optimal threshold apparent diffusion coefficient (ADC) used to predict skull base osteomyelitis in patients with necrotising otitis externa was 0.945 ×10-3mm2/s and 0.915 ×10-3mm2/s, with an area under the curve of 0.825 and 0.800, accuracy of 87.5 per cent and 83.3 per cent, sensitivity of 85.7 per cent and 90.0 per cent, and specificity of 90.0 per cent and 78.6 per cent for each reviewer respectively.

Table 2. Receiver operating characteristic curve results of apparent diffusion coefficients for both reviewers

AUC = area under the curve; PPV = positive predictive value; NPV = negative predictive value

Discussion

The main finding in this study is that the apparent diffusion coefficient of the skull base can predict skull base osteomyelitis in patients with necrotising otitis externa. There is restricted diffusion with a low apparent diffusion coefficient of the skull base lesion in patients with skull base osteomyelitis, and unrestricted diffusion with a high apparent diffusion coefficient of the skull base in patients with necrotising otitis externa without skull base involvement, with excellent inter-observer agreement of the apparent diffusion coefficients by both reviewers.

Previous studies using computed tomography and routine MRI reported that there is a thin line of demarcation between osteitis and osteomyelitis. Differentiation between both entities is crucial because they involve different treatment methods and planning.Reference Razek and Huang12–Reference Rozenblum-Beddok, Verillaud, Paycha, Vironneau, Abulizi and Benada15 The treatment of osteitis involves antibiotics alone, whereas osteomyelitis must be treated surgically with debridement and sequestrectomy.Reference Prasad, Prasad, Kumar, Thada, Rao and Chalasani27

Previous studies applied diffusion-weighted imaging in the assessment of infection of the spine, masticator space and diabetic foot.Reference Daghighi, Poureisa, Safarpour, Behzadmehr, Fouladi and Meshkini22,Reference Abdel Razek and Samir23,Reference Abdel Razek and Nada28 Diffusion-weighted imaging has the ability to distinguish between acute and chronic inflammatory changes. Only one study investigated the role of diffusion-weighted imaging for monitoring patients with necrotising otitis externa after therapy.Reference Cherko, Nash, Singh and Lingam26 That study reported a decrease in the apparent diffusion coefficient value for necrotising otitis externa after a response to the therapy. The apparent diffusion coefficient value facilitated quantitative assessment of the disease activity; hence, this parameter can be helpful for assessing the therapeutic response in subsequent follow-up examinations.Reference Cherko, Nash, Singh and Lingam26

In this study, the mean apparent diffusion coefficient value for the skull base bone marrow in nine patients with skull base osteomyelitis was lower than that in necrotising otitis externa patients without skull base involvement, as determined by two reviewers. The difference in the apparent diffusion coefficient between both entities may be attributed to the different pathological nature of the two conditions. Skull base osteomyelitis is characterised by high cellularity (inflammation and pus cells, dead organisms), decreased diffusion space for the water protons, and, hence, subsequent restricted diffusion and lower apparent diffusion coefficient values. The lower skull base bone marrow diffusion-weighted imaging signal intensity in necrotising otitis externa may be attributed to lower cellularity and consequently higher apparent diffusion coefficient values. These pathological criteria are responsible for the significant difference in the apparent diffusion coefficient values between both entities.Reference Abd-El Khalek Abd-ALRazek and Fahmy19,Reference Abdel Razek and Samir23,Reference Abdel Razek and Nada28,Reference Razek, Sieza and Maha29

In this study, only one patient with skull base osteomyelitis was determined to have a high apparent diffusion coefficient value for the skull base that was misdiagnosed as non-involvement of the skull base. This may be attributed to the early skull base infection with bone marrow oedema of the skull base, which is associated with more fluid and unrestricted diffusion, with a high apparent diffusion coefficient value for the skull base.Reference Daghighi, Poureisa, Safarpour, Behzadmehr, Fouladi and Meshkini22,Reference Abdel Razek and Samir23

Diffusion-weighted imaging can be conducted using either echo-planar imaging or non-echo-planar imaging diffusion-weighted imaging sequences. Echo-planar imaging diffusion-weighted imaging involves scanning a large volume within a short period (1 minute) and has an adequate signal-to-noise ratio; however, it is associated with susceptibility and chemical shift artefacts, especially at air–tissue interfaces, although parallel imaging can decrease susceptibility artefacts and image blurring. Non-echo-planar imaging diffusion-weighted imaging has a long echo time, high signal-to-noise ratio and is without susceptibility artefacts or image distortion at air–tissue interfaces such as the skull base; however, it is associated with ghosting artefacts and is more sensitive to motion artefacts.Reference Razek30–Reference Soni, Gupta, Kumar, Mangla and Mangla38 Diffusion-weighted imaging of the skull base has been conducted using echo-planar imaging diffusion-weighted imagingReference Abdel Razek, Mossad and Ghonim17,Reference Guler, Ozgen, Mut, Soylemezoglu and Oguz35 and non-echo-planar imaging diffusion-weighted imaging.Reference Soni, Gupta, Kumar, Mangla and Mangla38 In our study, we employed echo-planar imaging diffusion-weighted imaging using a shorter echo time and a large receiver bandwidth, to reduce the time of dephasing and minimise subsequent signal loss.

This study has a few limitations. First, it was a retrospective study with a small number of patients. Further studies with larger numbers of patients are recommended. Second, this study applied diffusion-weighted imaging; further studies using diffusion tensor imaging combined with dynamic contrast-enhanced MRI and proton magnetic resonance spectroscopy, on a 3 Tesla scanner,Reference Razek and Nada39–Reference Allam, Abdel Razek, Ashraf and Khaled46 will improve the results. Third, this study employed echo-planar imaging diffusion-weighted imaging of the skull base, which is associated with susceptibility changes at air–tissue interfaces that lead to image distortion and artefacts. Further studies that use non-echo-planar imaging diffusion-weighted imaging are recommended, with the application of parallel imaging to decrease the artefacts of diffusion-weighted imaging at the skull base.

  • • The apparent diffusion coefficient of the skull base is lower in necrotising otitis externa patients with skull base osteomyelitis than in those without skull base involvement

  • • Apparent diffusion coefficient can be used for predicting skull base osteomyelitis in necrotising otitis externa patients

  • • The optimal threshold apparent diffusion coefficient values of two reviewers used to predict skull base osteomyelitis in necrotising otitis externa patients were 0.945 and 0.915 ×10-3mm2/s

Conclusion

Apparent diffusion coefficient is a non-invasive imaging parameter that can be used to predict skull base osteomyelitis in patients with necrotising otitis externa.

Competing interests

None declared

Footnotes

Dr A A K Abdel Razek takes responsibility for the integrity of the content of the paper

References

Peled, C, El-Seid, S, Bahat-Dinur, A, Tzvi-Ran, LR, Kraus, M, Kaplan, D. Necrotizing otitis externa--analysis of 83 cases: clinical findings and course of disease. Otol Neurotol 2019;40:56–62Google ScholarPubMed
Cooper, T, Hildrew, D, McAfee, JS, McCall, AA, Branstetter, BF 4th, Hirsch, BE. Imaging in the diagnosis and management of necrotizing otitis externa: a survey of practice patterns. Otol Neurotol 2018;39:597–601CrossRefGoogle ScholarPubMed
Peled, C, Kraus, M, Kaplan, D. Diagnosis and treatment of necrotising otitis externa and diabetic foot osteomyelitis - similarities and differences. J Laryngol Otol 2018;132:775–9CrossRefGoogle ScholarPubMed
Hatch, JL, Bauschard, MJ, Nguyen, SA, Lambert, PR, Meyer, TA, McRackan, TR. Malignant otitis externa outcomes: a study of the University HealthSystem Consortium database. Ann Otol Rhinol Laryngol 2018;127:514–20Google ScholarPubMed
Khan, MA, Quadri, SAQ, Kazmi, AS, Kwatra, V, Ramachandran, A, Gustin, A et al. A comprehensive review of skull base osteomyelitis: diagnostic and therapeutic challenges among various presentations. Asian J Neurosurg 2018;13:959–70Google ScholarPubMed
Ridder, GJ, Breunig, C, Kaminsky, J, Pfeiffer, J. Central skull base osteomyelitis: new insights and implications for diagnosis and treatment. Eur Arch Otorhinolaryngol 2015;272:1269–76CrossRefGoogle ScholarPubMed
Le Clerc, N, Verillaud, B, Duet, M, Guichard, JP, Herman, P, Kania, R. Skull base osteomyelitis: incidence of resistance, morbidity, and treatment strategy. Laryngoscope 2014;124:2013–16CrossRefGoogle ScholarPubMed
Kornilenko, L, Rocka, S, Balseris, S, Arechvo, I. Clinical challenges in the diagnosis and treatment of temporal bone osteomyelitis. Case Rep Otolaryngol 2017;2017:4097973Google ScholarPubMed
Chen, JC, Yeh, CF, Shiao, S, Tu, TY. Temporal bone osteomyelitis: the relationship with malignant otitis externa, the diagnostic dilemma, and changing trends. ScientificWorldJournal 2014;2014:591714Google ScholarPubMed
van Kroonenburgh, AMJL, van der Meer, WL, Bothof, RJP, van Tilburg, M, van Tongeren, J, Postma, AA. Advanced imaging techniques in skull base osteomyelitis due to malignant otitis externa. Curr Radiol Rep 2018;6:3CrossRefGoogle ScholarPubMed
Adams, A, Offiah, C. Central skull base osteomyelitis as a complication of necrotizing otitis externa: imaging findings, complications, and challenges of diagnosis. Clin Radiol 2012;67:e7–16Google ScholarPubMed
Razek, AA, Huang, BY. Lesions of the petrous apex: classification and findings at CT and MR imaging. Radiographics 2012;32:151–73CrossRefGoogle ScholarPubMed
Goh, JPN, Karandikar, A, Loke, SC, Tan, TY. Skull base osteomyelitis secondary to malignant otitis externa mimicking advanced nasopharyngeal cancer: MR imaging features at initial presentation. Am J Otolaryngol 2017;38:466–71CrossRefGoogle ScholarPubMed
Lee, JE, Song, JJ, Oh, SH, Chang, SO, Kim, CH, Lee, JH. Prognostic value of extension patterns on follow-up magnetic resonance imaging in patients with necrotizing otitis externa. Arch Otolaryngol Head Neck Surg 2011;137:688–93CrossRefGoogle ScholarPubMed
Rozenblum-Beddok, L, Verillaud, B, Paycha, F, Vironneau, P, Abulizi, M, Benada, A et al. 99mTc-HMPAO-leukocyte scintigraphy for diagnosis and therapy monitoring of skull base osteomyelitis. Laryngoscope Investig Otolaryngol 2018;3:218–24CrossRefGoogle ScholarPubMed
Abdel Razek, AA, Kamal, E. Nasopharyngeal carcinoma: correlation of apparent diffusion coefficient value with prognostic parameters. Radiol Med 2013;118:534–9CrossRefGoogle ScholarPubMed
Abdel Razek, A, Mossad, A, Ghonim, M. Role of diffusion-weighted MR imaging in assessing malignant versus benign skull-base lesions. Radiol Med 2011;116:125–32CrossRefGoogle ScholarPubMed
Connolly, M, Srinivasan, A. Diffusion-weighted imaging in head and neck cancer technique, limitations, and applications. Magn Reson Imaging Clin N Am 2018;26:121–33CrossRefGoogle ScholarPubMed
Abd-El Khalek Abd-ALRazek, A, Fahmy, DM. Diagnostic value of diffusion-weighted imaging and apparent diffusion coefficient in assessment of the activity of Crohn disease: 1.5 or 3 T. J Comput Assist Tomogr 2018;42:688–96CrossRefGoogle ScholarPubMed
Schmid-Tannwald, C, Schmid-Tannwald, CM, Morelli, JN, Albert, NL, Braunagel, M, Trumm, C et al. The role of diffusion-weighted MRI in assessment of inflammatory bowel disease. Abdom Radiol 2016;41:1484–94CrossRefGoogle ScholarPubMed
Ozgen, B, Oguz, KK, Cila, A. Diffusion MR imaging features of skull base osteomyelitis compared with skull base malignancy. AJNR Am J Neuroradiol 2011;32:179–8410.3174/ajnr.A2237CrossRefGoogle ScholarPubMed
Daghighi, MH, Poureisa, M, Safarpour, M, Behzadmehr, R, Fouladi, DF, Meshkini, A et al. Diffusion-weighted magnetic resonance imaging in differentiating acute infectious spondylitis from degenerative Modic type 1 change; the role of b-value, apparent diffusion coefficient, claw sign and amorphous increased signal. Br J Radiol 2016;89:20150152CrossRefGoogle ScholarPubMed
Abdel Razek, A, Samir, S. Diagnostic performance of diffusion-weighted MR imaging in differentiation of diabetic osteoarthropathy and osteomyelitis in diabetic foot. Eur J Radiol 2017;89:221–5CrossRefGoogle ScholarPubMed
Lingam, RK, Bassett, P. A meta-analysis on the diagnostic performance of non-echoplanar diffusion-weighted imaging in detecting middle ear cholesteatoma: 10 years on. Otol Neurotol 2017;38:521–8CrossRefGoogle Scholar
Razek, AAKA. Assessment of masses of the external ear with diffusion-weighted MR imaging. Otol Neurotol 2018;39:227–31CrossRefGoogle ScholarPubMed
Cherko, M, Nash, R, Singh, A, Lingam, RK. Diffusion-weighted magnetic resonance imaging as a novel imaging modality in assessing treatment response in necrotizing otitis externa. Otol Neurotol 2016;37:704–7CrossRefGoogle ScholarPubMed
Prasad, SC, Prasad, KC, Kumar, A, Thada, ND, Rao, P, Chalasani, S. Osteomyelitis of the temporal bone: terminology, diagnosis, and management. J Neurol Surg B 2014;75:324–31CrossRefGoogle ScholarPubMed
Abdel Razek, AA, Nada, N. Role of diffusion-weighted MRI in differentiation of masticator space malignancy from infection. Dentomaxillofac Radiol 2013;42:20120183CrossRefGoogle ScholarPubMed
Razek, AA, Sieza, S, Maha, B. Assessment of nasal and paranasal sinus masses by diffusion-weighted MR imaging. J Neuroradiol 2009;36:206–11CrossRefGoogle ScholarPubMed
Razek, AA. Diffusion-weighted magnetic resonance imaging of head and neck. J Comput Assist Tomogr 2010;34:808–15CrossRefGoogle ScholarPubMed
Abdel Razek, AA, Soliman, N, Elashery, R. Apparent diffusion coefficient values of mediastinal masses in children. Eur J Radiol 2012;81:1311–14CrossRefGoogle ScholarPubMed
Razek, AAA. Ashmalla G. Assessment of paraspinal neurogenic tumors with diffusion-weighted MR imaging. Eur Spine J 2018;27:841–6CrossRefGoogle ScholarPubMed
Surov, A, Nagata, S, Razek, AA, Tirumani, SH, Wienke, A, Kahn, T. Comparison of ADC values in different malignancies of the skeletal musculature: a multicentric analysis. Skeletal Radiol 2015;44:995–1000CrossRefGoogle ScholarPubMed
Razek, AA, Lattif, MA, Denewer, A, Farouk, O, Nada, N. Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging. Breast Cancer 2016;23:525–32CrossRefGoogle ScholarPubMed
Guler, E, Ozgen, B, Mut, M, Soylemezoglu, F, Oguz, KK. The added value of diffusion magnetic resonance imaging in diagnosis and posttreatment evaluation of skull base chordoma. J Neurol Surg B Skull Base 2017;78:256–65CrossRefGoogle Scholar
Abdel Razek, AAK, Elkhamary, SM, Nada, N. Correlation of apparent diffusion coefficient with histopathological parameters of salivary gland cancer. Int J Oral Maxillofac Surg 2019;48:995–1000CrossRefGoogle ScholarPubMed
Razek, AAKA. Prediction of malignancy of submandibular gland tumors with apparent diffusion coefficient. Oral Radiol 2019;35:11–15CrossRefGoogle ScholarPubMed
Soni, N, Gupta, N, Kumar, Y, Mangla, M, Mangla, R. Role of diffusion-weighted imaging in skull base lesions: a pictorial review. Neuroradiology J 2017;30:370–84CrossRefGoogle ScholarPubMed
Razek, AA, Nada, N. Correlation of choline/creatine and apparent diffusion coefficient values with the prognostic parameters of head and neck squamous cell carcinoma. NMR Biomed 2016;29:483–9CrossRefGoogle ScholarPubMed
Abdel Razek, AAK. Routine and advanced diffusion imaging modules of the salivary glands. Neuroimaging Clin N Am 2018;28:245–54CrossRefGoogle ScholarPubMed
Razek, AAKA. Diffusion tensor imaging in differentiation of residual head and neck squamous cell carcinoma from post-radiation changes. Magn Reson Imaging 2018;54:84–9Google ScholarPubMed
El-Serougy, L, Abdel Razek, AA, Ezzat, A, Eldawoody, H, El-Morsy, A. Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas. Neuroradiol J 2016;29:400–7CrossRefGoogle ScholarPubMed
Abdel Razek, AAK. Arterial spin labelling and diffusion-weighted magnetic resonance imaging in differentiation of recurrent head and neck cancer from post-radiation changes. J Laryngol Otol 2018;132:923–8CrossRefGoogle ScholarPubMed
Razek, AA, Gaballa, G, Megahed, AS, Elmogy, E. Time resolved imaging of contrast kinetics (TRICKS) MR angiography of arteriovenous malformations of head and neck. Eur J Radiol 2013;82:1885–91CrossRefGoogle ScholarPubMed
Abdel Razek, AA, Samir, S, Ashmalla, GA. Characterization of parotid tumors with dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging and diffusion-weighted MR imaging. J Comput Assist Tomogr 2017;41:131–6CrossRefGoogle ScholarPubMed
Allam, H, Abdel Razek, A, Ashraf, B, Khaled, M. Reliability of diffusion-weighted MR imaging in differentiation of recurrent cholesteatoma and granulation tissue after intact canal wall mastoidectomy. J Laryngol Otol 2019;133:1083–6CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Necrotising otitis externa with skull base osteomyelitis. (a) Axial, contrast-enhanced magnetic resonance imaging scan shows diffuse enhancing lesion infiltrating the right masticator space in a patient with necrotising otitis externa. The lesion extends into the skull base bone marrow on the right side. Note abnormal marrow signal intensity of the ramus of the right mandible, denoting osteomyelitis of the mandible. (b) Apparent diffusion coefficient map shows low apparent diffusion coefficient values for the bony lesion of the skull base (arrows), with calculated apparent diffusion coefficient values of 0.83 and 0.79 ×10-3mm2/s for each reviewer respectively.

Figure 1

Fig. 2. Necrotising otitis externa without skull base involvement. (a) Axial, contrast-enhanced magnetic resonance imaging scan shows diffuse enhancing lesion infiltrating the left masticator space in a patient with necrotising otitis externa. The lesion extends into the skull base bone marrow on the left side. (b) Apparent diffusion coefficient map shows high apparent diffusion coefficient values for the bony lesion of the skull base (arrows), with calculated apparent diffusion coefficient values of 1.21 and 1.17 ×10-3mm2/s for each reviewer respectively.

Figure 2

Table 1. Mean apparent diffusion coefficients of skull base in necrotising otitis externa patients with and without skull base osteomyelitis

Figure 3

Fig. 3. Receiver operating characteristic curve. The optimal threshold apparent diffusion coefficient (ADC) used to predict skull base osteomyelitis in patients with necrotising otitis externa was 0.945 ×10-3mm2/s and 0.915 ×10-3mm2/s, with an area under the curve of 0.825 and 0.800, accuracy of 87.5 per cent and 83.3 per cent, sensitivity of 85.7 per cent and 90.0 per cent, and specificity of 90.0 per cent and 78.6 per cent for each reviewer respectively.

Figure 4

Table 2. Receiver operating characteristic curve results of apparent diffusion coefficients for both reviewers