目的探讨乳腺肿瘤的多参数MRI特征(T_(2)-WI、ADC值和DCE)以及乳腺密度和背景实质增强(BPE)特征在不同乳腺癌(BC)分子亚型中的差异,以期为临床诊断提供重要参考。方法本研究为回顾性研究,纳入344例患者。所有患者均接受了多参数乳房MRI(...目的探讨乳腺肿瘤的多参数MRI特征(T_(2)-WI、ADC值和DCE)以及乳腺密度和背景实质增强(BPE)特征在不同乳腺癌(BC)分子亚型中的差异,以期为临床诊断提供重要参考。方法本研究为回顾性研究,纳入344例患者。所有患者均接受了多参数乳房MRI(T_(2)WI、ADC和DCE序列),并根据最新的BIRADS提取特征,使用ROI之间的类内系数(ICC)来评估读者间协议。结果研究人群分为:luminal A 89例(26%),luminal B HER2阳性39例(11.5%),luminal B HER2阴性168例(48.5%),三阴性(TNBC)41例(12%),HER2富集7例(2%)。Luminal内A肿瘤与特殊的组织学类型、最小的肿瘤大小和持续的动力学曲线相关(P均<0.05)。Luminal B HER2阴性肿瘤与最低ADC值相关(0.77×10^(-3)mm^(2)/s^(2)),其预测BC分子亚型的准确性为0.583。TNBC与不对称和中度/显著BPE,圆形/椭圆形肿块,边缘受限和边缘增强相关(P均<0.05)。HER2富集的BC与最大肿瘤大小相关(平均37.28mm,p值=0.02)。结论BC分子亚型与T_(2)WI、ADC和DCE MRI特征相关,ADC有助于预测luminal B HER2阴性病例。展开更多
AIM:To describe the clinical characteristics of eyes using multimodal imaging features with acute macular neuroretinopathy(AMN)lesions following severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.MET...AIM:To describe the clinical characteristics of eyes using multimodal imaging features with acute macular neuroretinopathy(AMN)lesions following severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.METHODS:Retrospective case series study.From December 18,2022 to February 14,2023,previously healthy cases within 1-week infection with SARS-CoV-2 and examined at Tianjin Eye Hospital to confirm the diagnosis of AMN were included in the study.Totally 5 males and 9 females[mean age:29.93±10.32(16-49)y]were presented for reduced vision,with or without blurred vision.All patients underwent best corrected visual acuity(BCVA),intraocular pressure,slit lamp microscopy,indirect fundoscopy.Simultaneously,multimodal imagings fundus photography(45°or 200°field of view)was performed in 7 cases(14 eyes).Near infrared(NIR)fundus photography was performed in 9 cases(18 eyes),optical coherence tomography(OCT)in 5 cases(10 eyes),optical coherence tomography angiography(OCTA)in 9 cases(18 eyes),and fundus fluorescence angiography(FFA)in 3 cases(6 eyes).Visual field was performed in 1 case(2 eyes).RESULTS:Multimodal imaging findings data from 14 patients with AMN were reviewed.All eyes demonstrated different extent hyperreflective lesions at the level of the inner nuclear layer and/or outer plexus layer on OCT or OCTA.Fundus photography(45°or 200°field of view)showed irregular hypo-reflective lesion around the fovea in 7 cases(14 eyes).OCTA demonstrated that the superficial retinal capillary plexus(SCP)vascular density,deep capillary plexus(DCP)vascular density and choriocapillaris(CC)vascular density was reduced in 9 case(18 eyes).Among the follow-up cases(2 cases),vascular density increased in 1 case with elevated BCVA;another case has vascular density decrease in one eye and basically unchanged in other eye.En face images of the ellipsoidal zone and interdigitation zone injury showed a low wedge-shaped reflection contour appearance.NIR image mainly show the absence of the outer retinal interdigitation zone in AMN.No abnormal fluorescence was observed in FFA.Corresponding partial defect of the visual field were visualized via perimeter in one case.CONCLUSION:The morbidity of SARS-CoV-2 infection with AMN is increased.Ophthalmologists should be aware of the possible,albeit rare,AMN after SARS-CoV-2 infection and focus on multimodal imaging features.OCT,OCTA,and infrared fundus phase are proved to be valuable tools for detection of AMN in patients with SARS-CoV-2.展开更多
In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality.The technique rising on daily basis for detecting illn...In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality.The technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of humans.Automatic(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic applications.Various diseases that cause death need to be identified through such techniques and technologies to overcome the mortality ratio.The brain tumor is one of the most common causes of death.Researchers have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved efficiency.However,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving accuracy.On the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation technique.The results show that SVM outperforms other algorithms,with 95.3%accuracy.展开更多
文摘目的探讨乳腺肿瘤的多参数MRI特征(T_(2)-WI、ADC值和DCE)以及乳腺密度和背景实质增强(BPE)特征在不同乳腺癌(BC)分子亚型中的差异,以期为临床诊断提供重要参考。方法本研究为回顾性研究,纳入344例患者。所有患者均接受了多参数乳房MRI(T_(2)WI、ADC和DCE序列),并根据最新的BIRADS提取特征,使用ROI之间的类内系数(ICC)来评估读者间协议。结果研究人群分为:luminal A 89例(26%),luminal B HER2阳性39例(11.5%),luminal B HER2阴性168例(48.5%),三阴性(TNBC)41例(12%),HER2富集7例(2%)。Luminal内A肿瘤与特殊的组织学类型、最小的肿瘤大小和持续的动力学曲线相关(P均<0.05)。Luminal B HER2阴性肿瘤与最低ADC值相关(0.77×10^(-3)mm^(2)/s^(2)),其预测BC分子亚型的准确性为0.583。TNBC与不对称和中度/显著BPE,圆形/椭圆形肿块,边缘受限和边缘增强相关(P均<0.05)。HER2富集的BC与最大肿瘤大小相关(平均37.28mm,p值=0.02)。结论BC分子亚型与T_(2)WI、ADC和DCE MRI特征相关,ADC有助于预测luminal B HER2阴性病例。
文摘AIM:To describe the clinical characteristics of eyes using multimodal imaging features with acute macular neuroretinopathy(AMN)lesions following severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.METHODS:Retrospective case series study.From December 18,2022 to February 14,2023,previously healthy cases within 1-week infection with SARS-CoV-2 and examined at Tianjin Eye Hospital to confirm the diagnosis of AMN were included in the study.Totally 5 males and 9 females[mean age:29.93±10.32(16-49)y]were presented for reduced vision,with or without blurred vision.All patients underwent best corrected visual acuity(BCVA),intraocular pressure,slit lamp microscopy,indirect fundoscopy.Simultaneously,multimodal imagings fundus photography(45°or 200°field of view)was performed in 7 cases(14 eyes).Near infrared(NIR)fundus photography was performed in 9 cases(18 eyes),optical coherence tomography(OCT)in 5 cases(10 eyes),optical coherence tomography angiography(OCTA)in 9 cases(18 eyes),and fundus fluorescence angiography(FFA)in 3 cases(6 eyes).Visual field was performed in 1 case(2 eyes).RESULTS:Multimodal imaging findings data from 14 patients with AMN were reviewed.All eyes demonstrated different extent hyperreflective lesions at the level of the inner nuclear layer and/or outer plexus layer on OCT or OCTA.Fundus photography(45°or 200°field of view)showed irregular hypo-reflective lesion around the fovea in 7 cases(14 eyes).OCTA demonstrated that the superficial retinal capillary plexus(SCP)vascular density,deep capillary plexus(DCP)vascular density and choriocapillaris(CC)vascular density was reduced in 9 case(18 eyes).Among the follow-up cases(2 cases),vascular density increased in 1 case with elevated BCVA;another case has vascular density decrease in one eye and basically unchanged in other eye.En face images of the ellipsoidal zone and interdigitation zone injury showed a low wedge-shaped reflection contour appearance.NIR image mainly show the absence of the outer retinal interdigitation zone in AMN.No abnormal fluorescence was observed in FFA.Corresponding partial defect of the visual field were visualized via perimeter in one case.CONCLUSION:The morbidity of SARS-CoV-2 infection with AMN is increased.Ophthalmologists should be aware of the possible,albeit rare,AMN after SARS-CoV-2 infection and focus on multimodal imaging features.OCT,OCTA,and infrared fundus phase are proved to be valuable tools for detection of AMN in patients with SARS-CoV-2.
基金support of the Deputy for Research and Innovation-Ministry of Education,Kingdom of Saudi Arabia for this research through a grant(NU/IFC/ENT/01/014)under the institutional Funding Committee at Najran University,Kingdom of Saudi Arabia.
文摘In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality.The technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of humans.Automatic(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic applications.Various diseases that cause death need to be identified through such techniques and technologies to overcome the mortality ratio.The brain tumor is one of the most common causes of death.Researchers have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved efficiency.However,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving accuracy.On the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation technique.The results show that SVM outperforms other algorithms,with 95.3%accuracy.
