Journal of Otolaryngology and Ophthalmology of Shandong University ›› 2022, Vol. 36 ›› Issue (2): 113-119.doi: 10.6040/j.issn.1673-3770.0.2021.175
Previous Articles Next Articles
HUA Hongli1, LI Song1,TAO Zezhang1,2
CLC Number:
[1] Goecks J, Jalili V, Heiser LM, et al. How Machine Learning Will Transform Biomedicine[J]. Cell, 2020, 181(1): 92-101. doi:10.1016/j.cell.2020.03.022. [2] Erickson BJ, Korfiatis P, Akkus Z, et al. Machine Learning for Medical Imaging[J]. Radiographics, 2017, 37(2): 505-515. doi:10.1148/rg.2017160130. [3] Chartrand G, Cheng PM, Vorontsov E, et al. Deep Learning: A Primer for Radiologists[J]. Radiographics, 2017, 37(7): 2113-2131. doi:10.1148/rg.2017170077. [4] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 2015, 521(7553): 436-444. doi:10.1038/nature14539. [5] Soffer S, Ben-Cohen A, Shimon O, et al. Convolutional neural networks for radiologic images: a radiologist's guide[J]. Radiology, 2019, 290(3): 590-606. doi:10.1148/radiol.2018180547. [6] Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Trans Pattern Anal Mach Intell, 2017, 39(4): 640-651. doi:10.1109/TPAMI.2016.2572683. [7] Ronneberger O, Fischer P, Brox T, et al. U-Net: convolutional networks for biomedical image segmentation[J]. Springer International Publishing, 2015, 9351: 234-241. DOI: 10.1007/978-3-319-24574-4_28 [8] Fu Y, Lei Y, Wang T, et al. A review of deep learning based methods for medical image multi-organ segmentation[J]. Phys Med, 2021, 85: 107-122. doi:10.1016/j.ejmp.2021.05.003 [9] Wu YP, Cai PQ, Tian L, et al. Hypertrophic adenoids in patients with nasopharyngeal carcinoma: appearance at magnetic resonance imaging before and after treatment[J]. Chin J Cancer, 2015, 34(3): 130-136. doi:10.1186/s40880-015-0005-y. [10] Cengiz K, Kumral TL, Yildirim G. Diagnosis of pediatric nasopharynx carcinoma after recurrent adenoidectomy[J]. Case Rep Otolaryngol, 2013, 2013: 653963. doi:10.1155/2013/653963. [11] Li C, Jing B, Ke L, et al. Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies[J]. Cancer Commun(Lond), 2018, 38(1): 59. doi:10.1186/s40880-018-0325-9. [12] Chuang WY, Chang SH, Yu WH, et al. Successful Identification of Nasopharyngeal Carcinoma in Nasopharyngeal Biopsies Using Deep Learning[J]. Cancers(Basel), 2020, 12(2): E507. doi:10.3390/cancers12020507. [13] Du D, Feng H, Lv W, et al. Machine learning methods for optimal radiomics-based differentiation between recurrence and Inflammation: application to nasopharyngeal carcinoma post-therapy PET/CT images[J]. Mol Imaging Biol, 2020, 22(3): 730-738. doi:10.1007/s11307-019-01411-9. [14] Wong LM, King AD, Ai QYH, et al. Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI[J]. Eur Radiol, 2021, 31(6): 3856-3863. doi:10.1007/s00330-020-07451-y. [15] Yang Q, Guo Y, Ou X, et al. Automatic t staging using weakly supervised deep learning for nasopharyngeal carcinoma on MR Images[J]. J Magn Reson Imaging, 2020, 52(4): 1074-1102. doi:10.1002/jmri.27202. [16] Chan AT, Gregoire V, Lefebvre JL, et al. Nasopharyngeal cancer: EHNS-ESMO-ESTRO Clinical Practice Guidelines for diagnosis, treatment and follow-up[J]. Ann Oncol,2012,23(17):vii83-vii85. doi:10.1093/annonc/mds266. [17] Zhang L, Huang Y, Hong S, et al. Gemcitabine plus cisplatin versus fluorouracil plus cisplatin in recurrent or metastatic nasopharyngeal carcinoma: a multicentre, randomised, open-label, phase 3 trial[J]. The Lancet, 2016, 388(10054): 1883-1892. doi:10.1016/S0140-6736(16)31388-5. [18] 曾娜. 基于MRI影像组学建立鼻咽癌早期疗效预测模型[D].衡阳:南华大学.2020. doi: 10.27234/d.cnki.gnhuu.2020.000686 [19] Liu J, Mao Y, Li Z, et al. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma[J]. J Magn Reson Imaging, 2016, 44(2): 445-455. doi:10.1002/jmri.25156. [20] Zhang L, Ye Z, Ruan L, et al. Pretreatment MRI-Derived radiomics may evaluate the response of different induction chemotherapy regimens in locally advanced nasopharyngeal carcinoma[J]. Acad Radiol, 2020, 27(12): 1655-1664. doi:10.1016/j.acra.2020.09.002. [21] Zhao L, Gong J, Xi Y, et al. MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma[J]. Eur Radiol, 2020, 30(1): 537-546. doi:10.1007/s00330-019-06211-x. [22] Peng H, Dong D, Fang MJ, et al. Prognostic value of deep learning PET/CT-Based radiomics: potential role for future individual induction chemotherapy in advanced nasopharyngeal carcinoma[J]. Clin Cancer Res, 2019, 25(14): 4271-4279. doi:10.1158/1078-0432.CCR-18-3065. [23] Liu K, Xia W, Qiang M, et al. Deep learning pathological microscopic features in endemic nasopharyngeal cancer: prognostic value and protentional role for individual induction chemotherapy[J]. Cancer Med, 2020, 9(4): 1298-1306. doi:10.1002/cam4.2802. [24] Cui C, WANG S, ZHOU J, et al. Machine learning analysis of image data based on detailed MR image reports for nasopharyngeal carcinoma prognosis[J]. Biomed Res Int, 2020: 8068913. doi:10.1155/2020/8068913. [25] Zhang L, Wu X, Liu J, et al. MRI-based deep-learning model for distant metastasis-free survival in locoregionally advanced nasopharyngeal carcinoma[J]. J Magn Reson Imaging, 2021, 53(1): 167-178. doi:10.1002/jmri.27308. [26] Zhang B, Lian Z, Zhong L, et al. Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma[J]. BMC Cancer, 2020, 20(1): 502. doi:10.1186/s12885-020-06957-4. [27] Blanchard P, Lee A, Marguet S, et al. Chemotherapy and radiotherapy in nasopharyngeal carcinoma: an update of the MAC-NPC meta-analysis[J]. The Lancet Oncology, 2015, 16(6): 645-655. doi:10.1016/S1470-2045(15)70126-9. [28] Wang WY, Twu CW, Chen HH, et al. Plasma EBV DNA clearance rate as a novel prognostic marker for metastatic/recurrent nasopharyngeal carcinoma[J]. Clin Cancer Res,2010,16(3):1016-1024. doi:10.1158/1078-0432.CCR-09-2796. [29] Zhang L, Dong D, Li H, et al. Development and validation of a magnetic resonance imaging-based model for the prediction of distant metastasis before initial treatment of nasopharyngeal carcinoma: a retrospective cohort study[J]. EBioMedicine,2019,40:327-335. doi:10.1016/j.ebiom.2019.01.013. [30] Zhou Z, Wang K, Folkert M, et al. Multifaceted radiomics for distant metastasis prediction in head & neck cancer[J]. Phys Med Biol,2020,65(15):155009. doi:10.1088/1361-6560/ab8956. [31] Diamant A, Chatterjee A, Vallières M, et al. Deep learning in head & neck cancer outcome prediction[J]. Scientific Reports, 2019, 9(1): 2764. doi:10.1038/s41598-019-39206-1. [32] Wu Q, Wang S, Zhang S, et al. Development of a deep learning model to identify lymph node metastasis on magnetic resonance imaging in patients with cervical cancer[J]. JAMA Netw Open, 2020, 3(7): e2011625. doi:10.1001/jamanetworkopen.2020.11625. [33] Wu X, Dong D, Zhang L, et al. Exploring the predictive value of additional peritumoral regions based on deep learning and radiomics: a multicenter study[J]. Med Phys, 2021, 48(5): 2374-2385. doi:10.1002/mp.14767. [34] Xia WX, Zhang HB, Shi JL, et al. A prognostic model predicts the risk of distant metastasis and death for patients with nasopharyngeal carcinoma based on pre-treatment serum C-reactive protein and N-classification[J]. Eur J Cancer, 2013, 49(9): 2152-2160. doi:10.1016/j.ejca.2013.03.003. [35] Yang H, Bai X, Baoyin H. Rapid generation of time-optimal trajectories for asteroid landing via convex optimization[J]. Journal of Guidance, Control, and Dynamics, 2017, 40(3): 628-641. doi:10.2514/1.G002170. [36] An X, Wang FH, Ding PR, et al. Plasma epstein-Barr virus DNA level strongly predicts survival in metastatic/recurrent nasopharyngeal carcinoma treated with palliative chemotherapy[J]. Cancer, 2011, 117(16): 3750-3757. doi:10.1002/cncr.25932. [37] Chua MLK, Wee JTS, Hui EP, et al. Nasopharyngeal carcinoma[J]. Lancet, 2016, 387(10022): 1012-1024. doi:10.1016/S0140-6736(15)00055-0. [38] Lin L, Dou Q, Jin YM, et al. Deep learning for automated contouring of primary tumor volumes by MRI for nasopharyngeal carcinoma[J]. Radiology, 2019, 291(3): 677-686. doi:10.1148/radiol.2019182012. [39] Daoud B, Morooka K, Kurazume R, et al. 3D segmentation of nasopharyngeal carcinoma from CT images using cascade deep learning[J]. Comput Med Imaging Graph,2019,77:101644. doi:10.1016/j.compmedimag.2019.101644. [40] Ke L, Deng Y, Xia W, et al. Development of a self-constrained 3D DenseNet model in automatic detection and segmentation of nasopharyngeal carcinoma using magnetic resonance images[J]. Oral Oncology,2020,110:104862. doi:10.1016/j.oraloncology.2020.104862. [41] Liang S, Tang F, Huang X, et al. Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning[J]. Eur Radiol, 2019, 29(4): 1961-1967. doi:10.1007/s00330-018-5748-9. |
[1] | ZHOU YuxiangOverview,MIAO Beiping, LU YongtianGuidance. Treatment progress of endoscopic surgery for first diagnosed nasopharyngeal carcinoma [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(6): 108-112. |
[2] | WANG Di, CHENG JinzhangOverview,YU DanGuidance. Application of artificial intelligence based on machine learning in clinical diagnosis and treatment in otolaryngology [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(6): 125-131. |
[3] | LIU ZhaiOverview,YING MinzhengGuidance. Research progress on circRNAs in allergic rhinitis [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(5): 105-112. |
[4] | HUANG Yongwang, FU Dehui. Category and disease classification of voice medicine [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(3): 1-4. |
[5] | WANG Zhongwei, YANG Lin, GUO Ya, SUN Bin, WANG Yali, MA Xiulong, REN Hongtao, BAO Xing. Analysis of the relationship between miR-429 and miR-200C expression and prognosis in patients with nasopharyngeal carcinoma [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(3): 81-86. |
[6] | TAN Yufang, YI Tianhua. Clinical characteristics and prognosis of sudden sensorineural hearing loss in post-irradiated nasopharyngeal carcinoma survivors: a report of 18 cases [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2021, 35(1): 35-39. |
[7] | FAN Li, LI Yue, XU Ximing. Changes in and prognostic value of the inflammatory index before and after concurrent chemoradiotherapy for nasopharyngeal carcinoma [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(6): 36-41. |
[8] | Superior semicircular canal dehiscence(SSCD)syndrome occurs as a result of a bony defect of the skull base involving the superior semicircular canal, particularly at the arcuate eminence. The bony labyrinthine defect creates a direct communication between the dura and the labyrinthine membranous structure and acts as a mobile third window which may result in various auditory and vestibular manifestations. Tinnitus and autophony are the most common audiological manifestations. Dizziness and disequilibrium are the most common vestibular manifestations. Audiometric findings vary based on the severity of the disease. Low-frequency conductive hearing loss is a common finding. Bone conduction thresholds may be negative. A patient with SSCD will typically have a lower Vestibular Evoked Myogenic Potentials(VEMP)threshold response in the affected ear and may also have a larger than normal VEMP amplitude. High-resolution computed tomography(CT)scan of temporal bone plays an important role in confirming the diagnosis of SSCD. Pöschl and Stenver reformatted views are often recommended. Surgical treatment is reserved for patients presenting with debilitating vestibular and auditory manifestations that substantially interfere with their quality of life. There are two main surgical approaches(middle fossa, trans-mastoid)and several techniques(plugging, capping, resurfacing and combination). Presently, there is insufficient evidence to clearly determine which surgical approach or technique is superior. Surgical repair of SSCD through either the middle cranial fossa approach or trans-mastoid approach is highly effective for auditory and vestibular symptom improvement and is associated with a low risk of complications.. Superior semicircular canal dehiscence syndrome [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(5): 89-96. |
[9] | Pathologic myopia(PM)is a major cause of vision loss worldwide, particularly in Asian countries. Choroidal neovascularization(CNV)is a severe complication of PM, which can cause macular disorders, leading to central scotoma, metamorphopsia, visual field loss, and finally blindness if not treated. The advents of optical coherence topography(OCT), OCT angiography, and fundus fluorescein angiography are helpful in diagnosing CNV due to PM, which can show the position and size of CNV, whether active or passive. For the treatment, photodynamic and anti-vascular endothelial growth factor(anti-VEGF)therapies are widely applied. In recent years, administering the intravitreal anti-VEGF injection has become the first-line treatment for CNV secondary to PM. Many clinical studies have indicated that intravitreal anti-VEGF injections affect antagonizing neovascularization and reduce macular edema, thereby contributing to visual improvements and better long-term outcomes. This article provides an overview of the current diagnosis and treatment options for myopic CNV.. Diagnosis and treatment of choroidal neovascularization in pathologic myopia [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(5): 157-162. |
[10] | ObjectiveTo discuss the early diagnosis and multidisciplinary diagnosis and treatment of neovascular glaucoma in ocular ischemic syndrome. MethodsThe medical records of a 54-year-old male patient with cerebral infarction who presented with right-eye vision loss that had persisted for a week were reviewed. After slit-lamp examination and fluorescence angiography, he was diagnosed with ocular ischemic syndrome(OIS)complicated by neovascular glaucoma in the right eye and treated with intravitreal injection of anti-VEGF drugs and panretinal photocoagulation. ResultsAfter three months of treatment, the right-eye iris neovascularization subsided, and the intraocular pressure was controlled within normal limits. ConclusionOcular ischemia is often missed or misdiagnosed by ophthalmologists, neurologists, cardiologists, and vascular surgeons due to its insidious onset and complex clinical manifestations. Therefore, the establishment of multidisciplinary diagnosis and treatment can improve the prognosis of OIS patients.. Neovascular glaucoma in ocular ischemic syndrome: a case report and literature reviewQIN Shuqi1, WANG Luping1, JIANG Bin2, WANG Yanling1 1. Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, China; 2. Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, ChinaAbstract: [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(4): 53-55. |
[11] | The objective of this study was to analyze the effects and possible regulatory mechanisms that Notch receptors could have on cisplatin resistance, observed in nasopharyngeal carcinoma. MethodsWestern blot analysis was used for the detection of Notch receptor expression in nasopharyngeal carcinoma cells and cisplatin-resistant nasopharyngeal carcinoma cells(5-8F, 5-8F/CDDP). Flow cytometry was used to investigate how the combined treatment with 10 μM CDDP and different concentrations of γ-secretase inhibitor(DAPT)could affect apoptosis in 5-8F/CDDP cells. Flow cytometry was also used for the detection of cell cycle stages in DAPT-treated 5-8F / CDDP cells. Finally, western blotting was also used for the detection of drug resistance-related protein expression. All experiments were followed by statistical data analysis. ResultsWe observed significantly higher Notch1 and Notch4 receptor expression in 5-8F/CDDP cells than in 5-8F cells(P=0.003, P=0.004). Furthermore, we described that Notch signaling was inhibited by DAPT in 5-8F/CDDP cells, followed by a significant increase in the apoptosis rate and decrease in cell proliferation, induced by cisplatin in a dose-dependent manner(P<0.05). Moreover, after inhibiting the Notch signaling pathway in 5-8F/CDDP cells, DAPT treatment significantly decreased the expression of Cyclin E and CDK-2, proteins involved in cell cycle regulation, and contributed to blocking the cells in the G1/S phase(P<0.05). At the same time, the expression levels of both the EMT-related protein Slug and the DNA excision repair protein ERCC1 significantly decreased, while that of E-Cadherin was up-regulated. ConclusionUp-regulated expression of Notch1 and Notch4 receptors is associated with cisplatin resistance in nasopharyngeal carcinoma cells. The inactivation of the Notch signaling pathway might thus have the potential to enhance the efficiency of cisplatin chemotherapy in drug-resistant nasopharyngeal carcinoma cells by inhibiting EMT rather than blocking the G1/S cell cycle phase.. Cisplatin resistance in nasopharyngeal carcinoma cells is affected by Notch receptors through the regulation of epithelial-mesenchymal transition rather than cell cycle controlHAN Jibo, ZOU You, YANG Rui, TAO Zezhang Department of Otolaryngology-Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, ChinaAbstract:Objective〓 [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(4): 105-110. |
[12] | To explore the genesis, clinical diagnosis, treatment, and prevention mechanisms of the formation of stones within the nasal cavity and sinus as well as measures toreduce the rate of clinical misdiagnosis. MethodsA comprehensive analysis was conducted on six patients with nasal and sinus calculi who visited the hospital between April 2012 and November 2017. The etiology, pathology, clinical diagnosis, differential diagnosis, treatment, prevention, and complication management of the disease were summarized for each patient. ResultFive patients underwent surgery for the removal of stones from the nasal cavity and sinus under general anesthesia. Nasal endoscopy was also performed for the assessment of the related sinus passages. One patient recovered upon nasal irrigation and anti-inflammation treatment. All the patients were followed up for six months and the mucosal layer within the operation area that was epithelialized, recovered well. The symptoms disappeared without any additional complications. ConclusionNasal endoscopy in combination with the assessment of clinical manifestation and imaging are conducive to the diagnosis of the disease. Together, these could develop into an effective treatment regimen for nasal cavity and sinusoidal lithiasis.. Clinical experience in diagnosis and treatment of stone in nasal cavity and sinusZHAI Xingyou1, HOU Junsheng2, LI Xinjian1, WANG Xin1, XIE Yingli1, WANG Wenjia1 1. Department of Otorhinolaryngology Head and Neck Surgery, Hainan Hospital, General Hospital of PLA, Hainan Province Otorhinolaryngology Head and Neck Surgery Clinical Medical Research Center, Sanya 572013, Hainan, China; 2. Department of Otorhinolaryngology Head and Neck Surgery, the First Affiliated Hospital of Henan University, Kaifeng 475001, Henan, ChinaAbstract:Objective [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(4): 92-96. |
[13] | CHEN Haibing, WEI Ya'nan, XU Xiaoquan, CHEN Xi. Prediction of cervical lymph node metastasis in papillary thyroid cancer based on XGBoost artificial intelligence and enhanced computed tomography [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(3): 40-45. |
[14] | Zhenhua JIANG,Lijun ZHANG,Ying LI,Yanqin XIAO,Chao LI,Bo SHI,Guiying ZHANG,Bin XU,Wei DENG,Gang LUO,Jifang LUO,Guoqi LIU. Epidemic control practices of an otolaryngology-head and neck surgery ward in an area with non-high incidence of COVID-19 [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(2): 93-98. |
[15] | ZHU Zhiling, LI SongOverview,GUAN GuofangGuidance. Application and prospect of artificial intelligence in otolaryngology [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(2): 115-120. |
|