著者

Hidekazu AOKI Shunji MUGIKURA Reizo SHIRANE Toshiaki HAYASHI Tomomi KIMIWADA Kiyohide SAKAI Keiko AINOYA Hideki OTA Kei TAKASE Yoshihisa SHIMANUKI

出版者

The Japan Neurosurgical Society

雑誌

Neurologia medico-chirurgica (ISSN:04708105)

巻号頁・発行日

pp.2023-0002, (Released:2023-08-30)

参考文献数

22

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Closed spinal dysraphism (CSD) encompasses a heterogeneous group of spinal cord deformities, which can be accompanied by several types of skin stigmata. These skin stigmata may include inconspicuous features, such as sacral dimples and deformed gluteal clefts, but the association between such mild skin stigmata and CSD is uncertain. This study aimed to reevaluate the indication for magnetic resonance imaging (MRI) in patients with skin stigmata while considering the indication for surgery. A retrospective analysis was conducted on magnetic resonance images of 1255 asymptomatic children with skin stigmata between 2003 and 2015. Skin stigmata classification was based on medical chart data. All subtypes of CSDs except for filum terminale lipomas (FTL), FTL thicker than 2 mm or with low conus medullaris, were considered to meet the surgical indication. CSD prevalence was estimated while considering the surgical indications and assessed after excluding all FTL cases. Skin stigmata were classified into seven types, dimple, deformed gluteal cleft, hair, subcutaneous mass, appendage, discoloration, and protruding bone, and included 1056 isolated and 199 complex ones. The prevalence of CSD was 19.5%, 6.8%, and 0.5% among patients with isolated dimples (n = 881) and 13.9%, 5.8%, and 0.7% among those with isolated deformed gluteal clefts (n = 136) for all cases, surgical indications, and patients without FTL, respectively. Dimples and deformed gluteal clefts had a low prevalence of CSD requiring surgical intervention, and cases without FTL were rare. Asymptomatic patients with mild skin stigmata may not require immediate MRI.

著者

Hiroaki Shimizu Naoko Mori Shunji Mugikura Yui Maekawa Minoru Miyashita Tatsuo Nagasaka Satoko Sato Kei Takase

出版者

Japanese Society for Magnetic Resonance in Medicine

雑誌

Magnetic Resonance in Medical Sciences (ISSN:13473182)

巻号頁・発行日

pp.mp.2022-0091, (Released:2023-03-01)

参考文献数

43

被引用文献数

1

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Purpose: To evaluate the effectiveness of the texture analysis of axillary high-resolution 3D T2-weighted imaging (T2WI) in distinguishing positive and negative lymph node (LN) metastasis in patients with clinically node-negative breast cancer.Methods: Between December 2017 and May 2021, 242 consecutive patients underwent high-resolution 3D T2WI and were classified into the training (n = 160) and validation cohorts (n = 82). We performed manual 3D segmentation of all visible LNs in axillary level I to extract the texture features. As the additional parameters, the number of the LNs and the total volume of all LNs for each case were calculated. The least absolute shrinkage and selection operator algorithm and Random Forest were used to construct the models. We constructed the texture model using the features from the LN with the largest least axis length in the training cohort. Furthermore, we constructed the 3 models combining the selected texture features of the LN with the largest least axis length, the number of LNs, and the total volume of all LNs: texture-number model, texture-volume model, and texture-number-volume model. As a conventional method, we manually measured the largest cortical diameter. Moreover, we performed the receiver operating curve analysis in the validation cohort and compared area under the curves (AUCs) of the models.Results: The AUCs of the texture model, texture-number model, texture-volume model, texture-number-volume model, and conventional method in the validation cohort were 0.7677, 0.7403, 0.8129, 0.7448, and 0.6851, respectively. The AUC of the texture-volume model was higher than those of other models and conventional method. The sensitivity, specificity, positive predictive value, and negative predictive value of the texture-volume model were 90%, 69%, 49%, and 96%, respectively.Conclusion: The texture-volume model of high-resolution 3D T2WI effectively distinguished positive and negative LN metastasis for patients with clinically node-negative breast cancer.