Non-echoplanar diffusion weighed imaging and T1-weighted imaging for cholesteatoma mastoid extension

Baba, Akira; Kurihara, Sho; Fukuda, Takeshi; Yamauchi, Hideomi; Matsushima, Satoshi; Ikeda, Koshi; Kurokawa, Ryo; Ota, Yoshiaki; Takahashi, Masahiro; Sakurai, Yuika; Motegi, Masaomi; Komori, Manabu; Yamamoto, Kazuhisa; Yamamoto, Yoshiharu; Kojima, Hiromi; Ojiri, Hiroya

doi:10.1016/j.anl.2021.01.010

Cited by 8 publications

(8 citation statements)

References 12 publications

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“…Benson et al 15 used a thinner layer (0.6 mm) with the T2 sampling perfection with applicationoptimized contrasts by using different flip angle evolution (SPACE sequence; Siemens) technique, and the thinner scan thickness allowed a clearer display of the cholesteatoma border. The sensitivity and specificity for the mastoid region in this study was slightly lower than those reported in other studies, 17 probably due to the absence of a combined T1WI sequence to exclude cholesterol granulomas.…”

Section: Discussioncontrasting

confidence: 93%

“…When the cholesteatoma lesion is confined to the attic or tympanic cavity and does not extend to the posterior limb of the lateral semicircular canal, it is resected using only the transcanal endoscopic approach; involvement of the mastoid antrum or mastoid process requires conversion to mastoidectomy (microscopic ear surgery) or the combined microscopic and endoscopic approach to resect the lesion. [17][18][19][20][21] Although the semicircular canal was scored slightly lower in the T2WI-DWI fusion images than in the CT-DWI fusion images, there was no statistical difference between the 2 in terms of the clarity of the cholesteatoma margins and diagnostic confidence. The sensitivity and accuracy of T2WI-DWI fusion images for involvement of the mastoid antrum and mastoid were slightly higher than those of CT-DWI fusion images in this study, though there was no statistical difference between them.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of the Utility of High-Resolution CT-DWI and T2WI-DWI Fusion Images for the Localization of Cholesteatoma

Fan

Ding

Liu

2022

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE: Cholesteatoma is an aggressive disease that may lead to hearing impairment. This study aimed to compare the utility of high-resolution CT and TSE-DWI fusion images with that of T2WI and TSE-DWI fusion images in the localization of middle ear cholesteatoma. MATERIALS AND METHODS:Seventy-one patients with middle ear cholesteatoma were retrospectively recruited. High-resolution CT, T2WI with fat suppression, and TSE-DWI scans were obtained, and image fusion was performed using a 3D reconstruction postprocessing workstation to form CT-DWI and T2WI-DWI fusion images. The quality of the 2 fused images was subjectively evaluated using a 5-point Likert scale with the horizontal semicircular canal transverse position as the reference. Receiver operating characteristic analysis was performed, and the diagnostic efficacies of CT-DWI and T2WI-DWI fusion images in localizing middle ear cholesteatoma were calculated.

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Section: Discussioncontrasting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Comparison of the Utility of High-Resolution CT-DWI and T2WI-DWI Fusion Images for the Localization of Cholesteatoma

Fan

Ding

Liu

2022

AJNR Am J Neuroradiol

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“…MRI is characterized by high signal on non‐echoplanar (non‐EP) DWI and low signal on T1WI, and these findings are also useful in evaluating the presence of mastoid extension of cholesteatoma (Figure 13A,B). 58 In particular, non‐EP DWI for the detection of middle ear cholesteatoma has a very high sensitivity and specificity of .91 and .92, respectively 59 . There are reports that it is useful in differentiating cholesteatoma from non‐cholesteatoma (mean, 0.87 vs. 1.87 × 10 −3 mm 2 /second), and in predicting the risk of recurrence after surgery (less than mean 1.00 × 10 −3 mm 2 /second) based on ADC values derived from DWI (Figure 13C).…”

Section: Temporal Bone/skull Basementioning

confidence: 99%

Advanced imaging of head and neck infections

Baba

Kurokawa

et al. 2023

Journal of Neuroimaging

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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.

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“…However, there are no imaging criteria for the expansion of the aditus ad antrum; therefore, evaluation by radiologists or otolaryngologists lacks objectivity and reproducibility. MRI (especially non-EP diffusion-weighted imaging) can be used to identify some of them [ 5 – 7 ], but there are multiple limitations, including large regional differences in the number of facilities that can perform MRI studies [ 8 ], low temporal resolution, high cost, time-consuming and contraindications, such as internal metal and claustrophobia. Furthermore, even if MRI is performed, its limited resolution makes it difficult to accurately determine an extent of the disease ( Fig 1B ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Preoperative prediction by artificial intelligence for mastoid extension in pars flaccida cholesteatoma using temporal bone high-resolution computed tomography: A retrospective study

Takahashi

Noda²,

Yoshida³

et al. 2022

PLoS ONE

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Cholesteatoma is a progressive middle ear disease that can only be treated surgically but with a high recurrence rate. Depending on the extent of the disease, a surgical approach, such as microsurgery with a retroarticular incision or transcanal endoscopic surgery, is performed. However, the current examination cannot sufficiently predict the progression before surgery, and changes in approach may be made during the surgery. Large amounts of data are typically required to train deep neural network models; however, the prevalence of cholesteatomas is low (1-in-25, 000). Developing analysis methods that improve the accuracy with such a small number of samples is an important issue for medical artificial intelligence (AI) research. This paper presents an AI-based system to automatically detect mastoid extensions using CT. This retrospective study included 164 patients (80 with mastoid extension and 84 without mastoid extension) who underwent surgery. This study adopted a relatively lightweight neural network model called MobileNetV2 to learn and predict the CT images of 164 patients. The training was performed with eight divided groups for cross-validation and was performed 24 times with each of the eight groups to verify accuracy fluctuations caused by randomly augmented learning. An evaluation was performed by each of the 24 single-trained models, and 24 sets of ensemble predictions with 23 models for 100% original size images and 400% zoomed images. Fifteen otolaryngologists diagnosed the images and compared the results. The average accuracy of predicting 400% zoomed images using ensemble prediction model was 81.14% (sensitivity = 84.95%, specificity = 77.33%). The average accuracy of the otolaryngologists was 73.41% (sensitivity, 83.17%; specificity, 64.13%), which was not affected by their clinical experiences. Noteworthily, despite the small number of cases, we were able to create a highly accurate AI. These findings represent an important first step in the automatic diagnosis of the cholesteatoma extension.

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Non-echoplanar diffusion weighed imaging and T1-weighted imaging for cholesteatoma mastoid extension

Cited by 8 publications

References 12 publications

Comparison of the Utility of High-Resolution CT-DWI and T2WI-DWI Fusion Images for the Localization of Cholesteatoma

Comparison of the Utility of High-Resolution CT-DWI and T2WI-DWI Fusion Images for the Localization of Cholesteatoma

Advanced imaging of head and neck infections

Preoperative prediction by artificial intelligence for mastoid extension in pars flaccida cholesteatoma using temporal bone high-resolution computed tomography: A retrospective study

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