<strong>Background: </strong>Partial segmental thrombosis of the corpus cavernosum, known as partial priapism, is an uncommon urological condition which predominantly affects young men in which the proxima...<strong>Background: </strong>Partial segmental thrombosis of the corpus cavernosum, known as partial priapism, is an uncommon urological condition which predominantly affects young men in which the proximal part of one corpus cavernosum is thrombosed. Many risk factors have been described in the literature, however, the exact etiology of penile thrombosis and its pathogenesis remains unclear. Several treatment options are available ranging from conservative medical treatment, surgical intervention, or simple follow-up observation without treatment. <strong>Aim:</strong> In this study, we describe a patient with sickle cell anemia who presented with pain and a perineal swelling that was eventually diagnosed as partial priapism utilizing MRI scan and was treated conservatively with a successful outcome. We then performed a literature search of similar cases highlighting incidence, risk factors and management of this rare presentation. <strong>Case Presentation: </strong>A 23-year-old male who is known with sickle cell anemia presented to casualty with a 1-day history of perineal pain of a sudden onset associated with perineal swelling and vomiting. Genitourinary exam findings confirmed the absence of classic priapism. Careful examination of his perineal area revealed the presence of a fixed, hard, and tender mass at the proximal part of the penis. It was not attached to the overlying skin and no enlarged pelvic lymph nodes were felt. Once stabilized, MRI of the pelvis was performed showing right intra-tunical corpus cavernosum features suggestive of hematoma in keeping with partial segmental thrombosis of the corpus cavernosum. Conservative treatment was initiated, and the patient was managed expectantly in which he improved gradually with eventual disappearance of the perineal mass. <strong>Conclusion:</strong> Partial segmental thrombosis of the corpus cavernosum is a rare urological condition. Pathogenesis and etiologies are poorly understood but risk factors have been advocated of which sickle cell anemia is one of them. MRI has a crucial role in the diagnosis under this condition. Conservative treatment appears to be a reliable initial therapeutic option.展开更多
Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult to segment gravel objects. In...Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult to segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fast calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.展开更多
针对腹部部分注释数据集的嗜铬细胞瘤图像分割缺乏不同器官间的特征学习,导致分割中难以准确区分肿瘤及周边器官边缘的问题,提出一种基于多尺度与空间频率特征的嗜铬细胞瘤图像分割网络(MF-Net)。首先,构建多尺度空间频率通道注意力模块...针对腹部部分注释数据集的嗜铬细胞瘤图像分割缺乏不同器官间的特征学习,导致分割中难以准确区分肿瘤及周边器官边缘的问题,提出一种基于多尺度与空间频率特征的嗜铬细胞瘤图像分割网络(MF-Net)。首先,构建多尺度空间频率通道注意力模块(MSFCA)对图像频域信息和相邻编码器的多尺度特征图进行加权融合,以强化器官间纹理和边界特征的捕捉,从而突出肿瘤区域的特征表示能力;其次,引入上采样多尺度特征融合模块(UMFF)通过结合上采样得到的不同尺度特征图,增强模型对图像中不同大小对象的识别能力;最后,利用自适应目标损失函数(AOb)对有注释腹部器官标签进行损失计算,并根据注释器官类别调整损失权重大小,从而优化分割网络的学习过程。实验结果表明,在腹部器官和嗜铬细胞瘤数据集上,MF-Net的分割准确率相较于单独训练的nnU-Net(no new U-Net)分别提升了3.33和3.18个百分点,而Dice系数(Dice)和归一化表面距离(NSD)分别为89.07%和92.85%;在域外数据集上,MF-Net的Dice和NSD分别为84.66%和90.55%。此外,可视化结果表明,MF-Net能更好地处理嗜铬细胞瘤图像中的复杂背景和模糊边界,为嗜铬细胞瘤的精确诊断和治疗提供了更好的技术支持。展开更多
BACKGROUND Split liver transplantation(SLT)effectively expands the donor pool but carries a higher risk of early postoperative complications(EPC)due to the extensive transection surface and altered hemodynamics of par...BACKGROUND Split liver transplantation(SLT)effectively expands the donor pool but carries a higher risk of early postoperative complications(EPC)due to the extensive transection surface and altered hemodynamics of partial grafts.AIM To establish an interpretable machine learning framework to identify risk factors for EPC in adult recipients undergoing right tri-segment SLT.METHODS We retrospectively analyzed 109 adult SLT recipients,including 37 who developed EPC.A comprehensive set of perioperative donor and recipient variables was evaluated using four machine learning algorithms(random forest,support vector machine,extreme gradient boosting,and logistic regression).SHapley Additive exPlanations were employed to rank variable importance.Independent predictors were further validated through multivariate logistic regression,and a diagnostic nomogram was constructed.Restricted cubic spline,receiver operating characteristic,and survival analyses were conducted to evaluate model performance and clinical outcomes.RESULTS EPC occurred in 33.9%of recipients.Among the machine learning models,random forest demonstrated the best predictive performance.SHapley Additive exPlanations analysis identified the log-transformed systemic immune-inflammation index(LnSII),albumin-to-fibrinogen ratio,model for end-stage liver disease(MELD)score,partial lobectomy of segment IV(IV PL),intraoperative blood loss,and operation time as major contributors to the model.Multivariate logistic regression confirmed LnSII,MELD scores,IV PL,and blood loss as independent predictors of EPC.The nomogram constructed from these factors showed good discrimination and calibration(area under the curve=0.788,95%confidence interval:0.734-0.906).Kaplan-Meier analysis revealed that both LnSII and MELD scores were associated with five-year overall survival(P<0.05),while MELD score and IV PL were significantly correlated with early postoperative liver function recovery.CONCLUSION IV PL during right tri-segment SLT appears to reduce the risk of EPC and enhance postoperative liver function recovery.Together with LnSII,blood loss,and MELD score,these factors offer a reliable foundation for individualized perioperative risk stratification and management.展开更多
文摘<strong>Background: </strong>Partial segmental thrombosis of the corpus cavernosum, known as partial priapism, is an uncommon urological condition which predominantly affects young men in which the proximal part of one corpus cavernosum is thrombosed. Many risk factors have been described in the literature, however, the exact etiology of penile thrombosis and its pathogenesis remains unclear. Several treatment options are available ranging from conservative medical treatment, surgical intervention, or simple follow-up observation without treatment. <strong>Aim:</strong> In this study, we describe a patient with sickle cell anemia who presented with pain and a perineal swelling that was eventually diagnosed as partial priapism utilizing MRI scan and was treated conservatively with a successful outcome. We then performed a literature search of similar cases highlighting incidence, risk factors and management of this rare presentation. <strong>Case Presentation: </strong>A 23-year-old male who is known with sickle cell anemia presented to casualty with a 1-day history of perineal pain of a sudden onset associated with perineal swelling and vomiting. Genitourinary exam findings confirmed the absence of classic priapism. Careful examination of his perineal area revealed the presence of a fixed, hard, and tender mass at the proximal part of the penis. It was not attached to the overlying skin and no enlarged pelvic lymph nodes were felt. Once stabilized, MRI of the pelvis was performed showing right intra-tunical corpus cavernosum features suggestive of hematoma in keeping with partial segmental thrombosis of the corpus cavernosum. Conservative treatment was initiated, and the patient was managed expectantly in which he improved gradually with eventual disappearance of the perineal mass. <strong>Conclusion:</strong> Partial segmental thrombosis of the corpus cavernosum is a rare urological condition. Pathogenesis and etiologies are poorly understood but risk factors have been advocated of which sickle cell anemia is one of them. MRI has a crucial role in the diagnosis under this condition. Conservative treatment appears to be a reliable initial therapeutic option.
基金the National Natural Science Foundationof China!(No.49874027)
文摘Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult to segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fast calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.
文摘针对腹部部分注释数据集的嗜铬细胞瘤图像分割缺乏不同器官间的特征学习,导致分割中难以准确区分肿瘤及周边器官边缘的问题,提出一种基于多尺度与空间频率特征的嗜铬细胞瘤图像分割网络(MF-Net)。首先,构建多尺度空间频率通道注意力模块(MSFCA)对图像频域信息和相邻编码器的多尺度特征图进行加权融合,以强化器官间纹理和边界特征的捕捉,从而突出肿瘤区域的特征表示能力;其次,引入上采样多尺度特征融合模块(UMFF)通过结合上采样得到的不同尺度特征图,增强模型对图像中不同大小对象的识别能力;最后,利用自适应目标损失函数(AOb)对有注释腹部器官标签进行损失计算,并根据注释器官类别调整损失权重大小,从而优化分割网络的学习过程。实验结果表明,在腹部器官和嗜铬细胞瘤数据集上,MF-Net的分割准确率相较于单独训练的nnU-Net(no new U-Net)分别提升了3.33和3.18个百分点,而Dice系数(Dice)和归一化表面距离(NSD)分别为89.07%和92.85%;在域外数据集上,MF-Net的Dice和NSD分别为84.66%和90.55%。此外,可视化结果表明,MF-Net能更好地处理嗜铬细胞瘤图像中的复杂背景和模糊边界,为嗜铬细胞瘤的精确诊断和治疗提供了更好的技术支持。
基金Supported by Tianjin Key Medical Discipline Construction Project,No.TJYXZDXK-3-006ATianjin Municipal Health Commission General Fund Project,No.TJWJ2024MS017+3 种基金Key Project of Tianjin Science and Technology Bureau Applied Basic Research,No.23JCZDJC01200The Independent Research Fund of the Institute of Transplant Medicine at Nankai University,No.NKTM2023004The General Project of the China Medicine Education Association,No.ZJWYH-2023-YIZHI-028General Project of Scientific Research Plan of Tianjin Municipal Education Commission,No.2024ZX013。
文摘BACKGROUND Split liver transplantation(SLT)effectively expands the donor pool but carries a higher risk of early postoperative complications(EPC)due to the extensive transection surface and altered hemodynamics of partial grafts.AIM To establish an interpretable machine learning framework to identify risk factors for EPC in adult recipients undergoing right tri-segment SLT.METHODS We retrospectively analyzed 109 adult SLT recipients,including 37 who developed EPC.A comprehensive set of perioperative donor and recipient variables was evaluated using four machine learning algorithms(random forest,support vector machine,extreme gradient boosting,and logistic regression).SHapley Additive exPlanations were employed to rank variable importance.Independent predictors were further validated through multivariate logistic regression,and a diagnostic nomogram was constructed.Restricted cubic spline,receiver operating characteristic,and survival analyses were conducted to evaluate model performance and clinical outcomes.RESULTS EPC occurred in 33.9%of recipients.Among the machine learning models,random forest demonstrated the best predictive performance.SHapley Additive exPlanations analysis identified the log-transformed systemic immune-inflammation index(LnSII),albumin-to-fibrinogen ratio,model for end-stage liver disease(MELD)score,partial lobectomy of segment IV(IV PL),intraoperative blood loss,and operation time as major contributors to the model.Multivariate logistic regression confirmed LnSII,MELD scores,IV PL,and blood loss as independent predictors of EPC.The nomogram constructed from these factors showed good discrimination and calibration(area under the curve=0.788,95%confidence interval:0.734-0.906).Kaplan-Meier analysis revealed that both LnSII and MELD scores were associated with five-year overall survival(P<0.05),while MELD score and IV PL were significantly correlated with early postoperative liver function recovery.CONCLUSION IV PL during right tri-segment SLT appears to reduce the risk of EPC and enhance postoperative liver function recovery.Together with LnSII,blood loss,and MELD score,these factors offer a reliable foundation for individualized perioperative risk stratification and management.
