1
|
Gu Z, Dai W, Chen J, Jiang Q, Lin W, Wang Q, Chen J, Gu C, Li J, Ying G, Zhu Y. Convolutional neural network-based magnetic resonance image differentiation of filum terminale ependymomas from schwannomas. BMC Cancer 2024; 24:350. [PMID: 38504164 PMCID: PMC10949807 DOI: 10.1186/s12885-024-12023-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 02/20/2024] [Indexed: 03/21/2024] Open
Abstract
PURPOSE Preoperative diagnosis of filum terminale ependymomas (FTEs) versus schwannomas is difficult but essential for surgical planning and prognostic assessment. With the advancement of deep-learning approaches based on convolutional neural networks (CNNs), the aim of this study was to determine whether CNN-based interpretation of magnetic resonance (MR) images of these two tumours could be achieved. METHODS Contrast-enhanced MRI data from 50 patients with primary FTE and 50 schwannomas in the lumbosacral spinal canal were retrospectively collected and used as training and internal validation datasets. The diagnostic accuracy of MRI was determined by consistency with postoperative histopathological examination. T1-weighted (T1-WI), T2-weighted (T2-WI) and contrast-enhanced T1-weighted (CE-T1) MR images of the sagittal plane containing the tumour mass were selected for analysis. For each sequence, patient MRI data were randomly allocated to 5 groups that further underwent fivefold cross-validation to evaluate the diagnostic efficacy of the CNN models. An additional 34 pairs of cases were used as an external test dataset to validate the CNN classifiers. RESULTS After comparing multiple backbone CNN models, we developed a diagnostic system using Inception-v3. In the external test dataset, the per-examination combined sensitivities were 0.78 (0.71-0.84, 95% CI) based on T1-weighted images, 0.79 (0.72-0.84, 95% CI) for T2-weighted images, 0.88 (0.83-0.92, 95% CI) for CE-T1 images, and 0.88 (0.83-0.92, 95% CI) for all weighted images. The combined specificities were 0.72 based on T1-WI (0.66-0.78, 95% CI), 0.84 (0.78-0.89, 95% CI) based on T2-WI, 0.74 (0.67-0.80, 95% CI) for CE-T1, and 0.81 (0.76-0.86, 95% CI) for all weighted images. After all three MRI modalities were merged, the receiver operating characteristic (ROC) curve was calculated, and the area under the curve (AUC) was 0.93, with an accuracy of 0.87. CONCLUSIONS CNN based MRI analysis has the potential to accurately differentiate ependymomas from schwannomas in the lumbar segment.
Collapse
Affiliation(s)
- Zhaowen Gu
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Wenli Dai
- Zhejiang University School of Mathematical Sciences, Hangzhou, Zhejiang, China
| | - Jiarui Chen
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Qixuan Jiang
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Weiwei Lin
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Qiangwei Wang
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Jingyin Chen
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Chi Gu
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China
| | - Jia Li
- Ningbo Medical Center Lihuili Hospital, Department of Neurosurgery, Ningbo University, 1111, Jiangnan Road, Ningbo, Zhejiang, China.
| | - Guangyu Ying
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China.
| | - Yongjian Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University, 88, Jiefang Road, Hangzhou, China.
- Clinical Research Center for Neurological Diseases of Zhejiang Province, Hangzhou, China.
| |
Collapse
|
2
|
Soto CJ, Novick SD, Naga Laxmi Poojita A, Khan S, Khan MW, Holder SS. Spinal Myxopapillary Ependymoma: A Rare Case and Review of Management Strategies. Cureus 2023; 15:e39381. [PMID: 37362475 PMCID: PMC10286524 DOI: 10.7759/cureus.39381] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/22/2023] [Indexed: 06/28/2023] Open
Abstract
Intramedullary myxopapillary ependymomas are rare spinal cord tumors primarily affecting young adults. Grade 2 tumors are associated with a higher proliferative index and potentially more aggressive behavior compared to grade 1 tumors. We present a case of a 30-year-old male who presented with a three-month history of progressive unilateral lower back pain that was refractory to analgesics. Neurological examination revealed bilateral lower limb weakness and sensory impairments in the L2 region. MRI confirmed a well-defined, enhancing intramedullary lesion at the L2 level, causing cord enlargement and edema. Diagnosis of grade 2 intramedullary myxopapillary ependymoma was made. Complete surgical resection was performed, confirming a grade 2 myxopapillary ependymoma. Postoperatively, the patient demonstrated significant improvement in lower limb function and sensation, with no tumor recurrence during long-term follow-up. Rehabilitation therapy was initiated, while close monitoring for complications and tumor progression was maintained. This case explores the etiology and features of intramedullary myxopapillary ependymomas and underscores the importance of early recognition, accurate diagnosis, and aggressive surgical management.
Collapse
Affiliation(s)
| | - Samuel D Novick
- General Surgery, Nassau University Medical Center, East Meadow, USA
- Medical Student, University of Nicosia Medical School, Nicosia, CYP
| | | | - Saima Khan
- Internal Medicine, Sir Syed College of Medical Sciences for Girls, Karachi, PAK
| | | | - Shaniah S Holder
- Medicine, American University of Barbados School of Medicine, Bridgetown, BRB
| |
Collapse
|
3
|
Extra-Neural Metastases of Late Recurrent Myxopapillary Ependymoma to Left Lumbar Paravertebral Muscles: Case Report and Review of the Literature. Brain Sci 2022; 12:brainsci12091227. [PMID: 36138961 PMCID: PMC9497216 DOI: 10.3390/brainsci12091227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 09/04/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
Ependymomas are commonly classified as low-grade tumors, although they may harbor a malignant behavior characterized by distant neural dissemination and spinal drop metastasis. Extra-CNS ependymoma metastases are extremely rare and only few cases have been reported in the lung, lymph nodes, pleura, mediastinum, liver, bone, and diaphragmatic, abdominal, and pelvic muscles. A review of the literature yielded 14 other case reports metastasizing outside the central nervous system, but to our knowledge, no studies describe metastasis in the paravertebral muscles. Herein, we report the case of a 39-year-old patient with a paraspinal muscles metastasis from a myxopapillary ependymoma. The neoplasm was surgically excised and histologically and molecularly analyzed. Both the analyses were consistent with the diagnosis of muscle metastases of myxopapillary ependymoma. The here-presented case report is first case in the literature of a paraspinal muscles metastasis of myxopapillary ependymoma.
Collapse
|