CT影像组学对中轴骨脊索瘤与骨巨细胞瘤的鉴别诊断价值

目的:建立术前鉴别中轴骨脊索瘤与骨巨细胞瘤的影像组学模型,并验证其诊断效能.方法:回顾性纳入中轴骨脊索瘤59例、骨巨细胞瘤33例共92例患者,64例为训练集,28例为验证集.基于CT图像进行影像组学特征提取,采用LASSO模型进行特征选择,构建影像组学模型,并计算影像组学得分(Rad-score).通过Logistic...     

基于MRI征象及影像组学的列线图预测腮腺良性与恶性肿瘤的价值

目的建立并验证基于MRI征象和影像组学的列线图鉴别腮腺良性与恶性肿瘤的效能。方法回顾性收集2015年1月至2020年5月青岛大学附属医院86例经手术病理证实的腮腺肿瘤患者为训练集,收集2013年1月至2020年1月香港大学深圳医院35例患者为独立外部验证集。采用logistic回归基于临床及MRI征象建立临床诊断模型。基于术前平扫T1WI和预饱和脂肪抑制T2WI(fs-T2WI)进行影像组学特征提取,建立影像组学诊断模型。基于影像组学评分及临床诊断模型,通过logistic回归建立影像组学+临床联合诊断模型及列线图。采用受试者操作特征(ROC)曲线评价各模型诊断腮腺良性与恶性肿瘤的效能,ROC曲线下面积(AUC)的比较采用DeLong检验。结果Logistic回归结果显示,腮腺深叶受累(OR值为3.285,P=0.040)和周围组织结构侵犯(OR值为15.919,P=0.013)是腮腺恶性肿瘤的独立影响因素,将二者构建临床诊断模型。基于平扫T1WI和fs-T2WI,共提取19个特征构建影像组学诊断模型。联合影像组学评分以及腮腺深叶受累、周围组织结构侵犯2个常规影像学特征建立联合诊断模型及列线图。临床诊断模型、影像组学诊断模型、联合诊断模型在训练集和验证集中诊断腮腺良性与恶性肿瘤的AUC分别为0.758、0.951、0.953和0.752、0.941、0.964。在训练集和验证集中,影像组学诊断模型、联合诊断模型的AUC均高于临床诊断模型(训练集:Z=3.95、4.31,P均<0.001;验证集:Z=2.16、2.67,P=0.031、0.008),影像组学诊断模型、联合诊断模型间AUC差异无统计学意义(训练集:Z=0.39,P=0.697;验证集:Z=1.10,P=0.273)。结论本研究所建立的MRI影像组学模型以及由腮腺深叶受累、周围组织结构侵犯、MRI影像组学特征组成的联合诊断模型,能有效鉴别腮腺良恶性肿瘤,具有较高的预测效能。     

Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer

To develop a T2-weighted (T2W) image-based radiomics signature for the individual prediction of KRAS mutation status in patients with rectal cancer. Three hundred four consecutive patients from center I with pathologically diagnosed rectal adenocarcinoma (training dataset, n = 213; internal validation dataset, n = 91) were enrolled in our retrospective study. The patients from center II (n = 86) were selected as an external validation dataset. A total of 960 imaging features were extracted from high-resolution T2W images for each patient. Five steps, mainly univariate statistical tests, were applied for feature selection. Subsequently, three classification methods, i.e., logistic regression (LR), decision tree (DT), and support vector machine (SVM) algorithm, were applied to develop the radiomics signature for KRAS prediction in the training dataset. The predictive performance was evaluated by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). Seven radiomics features were screened as a KRAS-associated radiomics signature of rectal cancer. Our best prediction model was obtained with SVM classifiers with AUC of 0.722 (95%CI, 0.654–0.790) in the training dataset. This was validated in the internal and external validation datasets with good calibration, and the corresponding AUCs were 0.682 (95% CI, 0.569–0.794) and 0.714 (95% CI, 0.602–0.827), respectively. DCA confirmed its clinical usefulness. The proposed T2WI-based radiomics signature has a moderate performance to predict KRAS status, and may be useful for supplementing genomic analysis to determine KRAS expression in rectal cancer patients. • T2WI-based radiomics showed a moderate diagnostic significance for KRAS status. • The best prediction model was obtained with SVM classifier. • The baseline clinical and histopathological characteristics were not associated with KRAS mutation.     

MRI of non-specific low back pain and/or lumbar radiculopathy: do we need T1 when using a sagittal T2-weighted Dixon sequence?

To show that for the MRI workup of non-specific low back pain and/or lumbar radiculopathy, the acquisition of T1-weighted sequences in the sagittal plane could be waived when using an FSE T2-weighted Dixon sequence. Three musculoskeletal radiologists retrospectively reviewed fifty lumbar spine MRI examinations performed for non-specific low back pain and/or lumbar radiculopathy. Two protocols were separately analyzed in the sagittal plane: a standard protocol (T1-weighted, in-phase, and water-only images of an FSE T2-weighted Dixon sequence) and a simplified protocol (fat-only, in-phase, and water-only images of an FSE T2-weighted Dixon sequence). Eight items usually assessed on T1-weighted sequences were analyzed for each of the vertebrae (n = 250), vertebral endplates (n = 500), vertebral corners (n = 1000), foramina (n = 500), lamina (n = 500), and facet joints (n = 500). Interchangeability of these protocols was tested using the individual equivalence index. A decrease in interobserver agreement of ≥ 5% when one reader used the simplified protocol compared with when both readers used the standard protocol was considered clinically significant. Interreader and intrareader agreement were assessed using kappa statistics. Rates of findings with each protocol were compared using odd ratios. The standard and simplified protocols were interchangeable (range of upper bound of the 95%CI of individual equivalence index = 0.25 to 1.38%). Intraprotocol and interprotocol interreader kappa values were similar (0.253–0.671 vs. 0.236–0.723, respectively). Rates of findings were not statistically significantly different (p ≥ 0.074), or were higher with the simplified protocol (p ≤ 0.036). In our target population, a single sagittal T2-weighted Dixon sequence may replace the recommended combination of T1-, T2-, and fat-suppressed T2-weighted sequences. • In patients with non-specific low back pain or lumbar radiculopathy, spine MRI in the sagittal plane could be limited to a single FSE T2-weighted Dixon sequence, hereby reducing the acquisition time. • A simplified protocol of spine MRI in the sagittal plane combining FSE T2-weighted Dixon sequence provides the same information as a standard protocol including T1-, T2-, and fat-suppressed T2-weighted sequences for the workup of degenerative lumbar spine lesions. • For some findings shown on the simplified protocol, such as focal bone marrow replacement lesions or signs of infection, additional sequences including pre- and post-contrast T1-weighted sequences may be required, as is currently the case when using the standard protocol.     

Texture analysis of deep medullary veins on susceptibility-weighted imaging in infants: evaluating developmental and ischemic changes

Susceptibility-weighted imaging (SWI) can be used to evaluate deep medullary veins (DMVs). This study aimed to apply texture analysis on SWI to evaluate developmental and ischemic changes of DMV in infants. A total of 38 infants with normal brain MRI (preterm [n = 12], term-equivalent age [TEA] [n = 18], and term [n = 8]) and seven infants with ischemic injury (preterm [n = 2], TEA [n = 1], and term [n = 4]) were included. Regions of interests were manually drawn to include DMVs. First-order texture parameters including entropy, skewness, and kurtosis were derived from SWI. The parameters were compared between groups according to age and presence of ischemic injury. A regression analysis was performed to correlate postmenstrual age (PMA) and parameters. A ROC analysis was performed to differentiate ischemic infants from normal infants. Among parameters, entropy showed a significant difference between the age groups (preterm vs. TEA vs. term; 5.395 vs. 4.885 vs. 4.883, p = 0.001). There was a significant positive relationship between PMA and entropy (R square = 0.402, p < 0.001). Skewness was significantly higher in the ischemic group compared with that in the normal group (1.37 vs. 0.70, p = 0.001). The ROC on skewness resulted in an AUC of 0.87 (accuracy, 83.2%) for differentiating infants with ischemic injury. A texture analysis of DMVs on SWI showed differences according to age and presence of ischemic injury. The texture parameters can potentially be used as quantitative markers for differentiating infants with ischemic injury through DMV changes. • The DMV structure of the infant brain could be quantified on SWI with texture analysis. • Entropy from texture analysis on SWI increased as infants got older. • Normal and ischemic injured infants could be differentiated with a cutoff value of 1.025 for skewness.     

Preoperative prediction of tumour deposits in rectal cancer by an artificial neural network–based US radiomics model

To develop a machine learning–based ultrasound (US) radiomics model for predicting tumour deposits (TDs) preoperatively. From December 2015 to December 2017, 127 patients with rectal cancer were prospectively enrolled and divided into training and validation sets. Endorectal ultrasound (ERUS) and shear-wave elastography (SWE) examinations were conducted for each patient. A total of 4176 US radiomics features were extracted for each patient. After the reduction and selection of US radiomics features , a predictive model using an artificial neural network (ANN) was constructed in the training set. Furthermore, two models (one incorporating clinical information and one based on MRI radiomics) were developed. These models were validated by assessing their diagnostic performance and comparing the areas under the curve (AUCs) in the validation set. The training and validation sets included 29 (33.3%) and 11 (27.5%) patients with TDs, respectively. A US radiomics ANN model was constructed. The model for predicting TDs showed an accuracy of 75.0% in the validation cohort. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and AUC were 72.7%, 75.9%, 53.3%, 88.0% and 0.743, respectively. For the model incorporating clinical information, the AUC improved to 0.795. Although the AUC of the US radiomics model was improved compared with that of the MRI radiomics model (0.916 vs. 0.872) in the 90 patients with both ultrasound and MRI data (which included both the training and validation sets), the difference was nonsignificant (p = 0.384). US radiomics may be a potential model to accurately predict TDs before therapy. • We prospectively developed an artificial neural network model for predicting tumour deposits based on US radiomics that had an accuracy of 75.0%. • The area under the curve of the US radiomics model was improved than that of the MRI radiomics model (0.916 vs. 0.872), but the difference was not significant (p = 0.384). • The US radiomics–based model may potentially predict TDs accurately before therapy, but this model needs further validation with larger samples.     

“Tenomalacia”: a new sonographic sign of tendinopathy?

The purpose of this study was to assess tendon compressibility with sonography in extensor tendinopathy and in asymptomatic extensor tendons of the elbow. Sonography of both elbows was performed in eight patients with a clinical diagnosis of unilateral lateral epicondylitis. Tendons were assessed for compressibility by measuring their thickness before and after compression with the transducer. The same manoeuvre was performed while tendon vascularity was assessed with colour Doppler. All eight cases showed increased compressibility of the common extensor tendon on the painful side compared to the asymptomatic side, as well as increased vascularity with compressible vessels on colour Doppler. Other signs of tendinopathy were hypoechogenicity (n = 8), loss of fibrillar pattern (n = 8), intratendinous calcifications (n = 1), partial tears (n = 3), and enthesophytes (n = 5). Increased tendon compressibility indicative of tendon softening or “tenomalacia” is a new sonographic sign of common extensor tendinopathy. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke

ObjectiveTo develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes.Materials and MethodsData from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses.ResultsAge, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness.ConclusionThe clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.     

Usefulness of multifunctional gastrointestinal coil catheter for colorectal stent placement

The purpose of this study was to evaluate the usefulness of a multifunctional gastrointestinal coil catheter for stent placement in 98 patients with colorectal strictures. The catheter was used in 98 consecutive patients for stent placement in the rectum (n = 24), recto-sigmoid (n = 13), sigmoid (n = 38), descending (n = 6), transverse (n = 11), splenic flexure (n = 3), hepatic flexure (n = 2), and ascending (n = 1) colon. The catheter was made of a stainless steel coil (1.3 mm in inner diameter), a 0.4-mm nitinol wire, a polyolefin tube, and a hemostasis valve. Usefulness of the catheter was evaluated depending on whether the catheter could pass a stricture over a guide wire and whether measurement of the stricture length was possible. The passage of the catheter over a guide wire beyond the stricture was technically successful and well tolerated in 93 (94.9%) of 98 patients. In the failed five patients, it was not possible to negotiate the guide wire due to presence of nearly complete small bowel obstruction. The average length of stricture was 6.15 cm (range, 3 cm to 20 cm) in patients with the colorectal stricture. There were no procedure-related complications. In conclusion, the multifunctional coil catheter seems to be useful in colorectal stent placement.     

基于T2WI和增强MRI影像组学列线图预测宫颈鳞癌淋巴脉管间隙浸润

目的:探讨基于T₂WI和增强MRI影像组学列线图对宫颈鳞癌淋巴脉管间隙浸润(LVSI)的预测价值。方法:将92例经术后病理证实的宫颈鳞癌患者纳入研究,并按7:3的比例随机分为训练集(66例)和验证集(26例)。所有患者术前行MRI检查,在横轴面T₂WI和对比增强T₁WI(T1CE)上选取病灶最大层面沿肿瘤边缘勾画ROI,应用AK软件提取影像组学特征。采用mRMR和LASSO回归分析对提取的纹理特征进行初步筛选,然后进行多因素logistic回归分析,构建影像组学模型。使用单因素logistic回归分析筛选临床病理危险因素,并使用多因素logistic回归结合影像组学评分(Radscore)构建影像组学列线图。应用ROC曲线评估影像组学模型、临床病理危险因素模型和影像组学列线图模型的预测能力,并应用决策曲线分析评估影像组学列线图的临床应用价值。结果:在T₂WI和T1CE图像上分别提取病灶的396个影像组学特征,最终筛选出14个具有最大诊断效能的纹理特征。使用多因素logistic回归构建包含FIGO分期、分化程度和Radscore的影像组学列线图。影像组学列线图的预测效能优于临床病理危险因素模型(训练集中,AUC:0.96 vs.0.70;Delong检验:Z=4.04,P=5.415e-05;验证集中,AUC:0.87 vs.0.71;delong检验:Z=1.24,P=0.02)。决策曲线分析显示风险阈值为0.01~1.00时使用影像组学列线图对预测宫颈鳞癌LVSI情况的临床应用价值较大。结论:基于双序列MRI构建的影像组学列线图对宫颈鳞癌LVSI情况有较好的预测能力,可作为一种术前评估的无创性影像学生物标志。     

基于增强CT影像组学评分和临床分期的列线图预测胃癌脉管浸润的价值

目的 探讨基于增强CT影像组学评分（Radscore）和TNM分期的列线图预测胃癌脉管浸润（LVI）的价值。 方法 回顾性收集160例术前行上腹部CT增强检查且行术后胃癌LVI状态评估的病人,男109例,女51例,平均年龄（62.23±10.74）岁。160例病人（包括LVI阴性者92例,阳性者68例）按照7∶3比例随机分为训练集（112例）和测试集（48例）;其中,训练集中LVI阴性者60例、阳性者52例,测试集中LVI阴性者32例、阳性者16例。基于增强CT影像提取并筛选影像组学特征,建立影像组学标签并计算Radscore。采用t检验、Mann-Whitney U检验、卡方检验或Kruskal-Wallis H 检验比较LVI阳性组和阴性组间临床病理特征[病人性别、年龄、肿瘤直径、TNM分期、AJCC分期、肿瘤分化程度及癌胚抗原（CEA）、糖类抗原199（CA199）]的差异,将差异有统计学意义的特征和影像组学标签纳入多因素logistic回归,建立临床影像联合模型和列线图。采用受试者操作特征（ROC）曲线评估影像组学模型和列线图的预测效能并计算相应的曲线下面积（AUC）。采用决策曲线评价影像组学模型和列线图的临床净获益。分别基于训练集及测试集中的数据绘制校准曲线对列线图进行验证。 结果 LVI阳性组和阴性组间肿瘤T分期、N分期、AJCC分期的差异均有统计学意义（均P<0.05）,且LVI阳性组的Radscore高于阴性组（P<0.05）。在测试集中,基于T分期、N分期、AJCC分期和Radscore的临床影像联合模型预测LVI的AUC值、准确度和特异度较影像组学模型分别提高了8.2%、18.2%和21.9%。决策曲线分析显示应用联合模型的临床净获益优于影像组学模型。联合模型的列线图显示Radscore得分最高,其次是AJCC分期,最后是N分期和T分期。训练集和测试集中的校准曲线显示列线图的预测结果与真实结果具有较好的一致性。 结论 联合T分期、N分期、AJCC分期和增强CT的Radscore建立的列线图能够成功预测胃癌LVI。     

Transpulmonary chemoembolization (TPCE) as a treatment for unresectable lung metastases

To evaluate tumor response after treating unresectable lung metastases with transpulmonary chemoembolization (TPCE) in palliative intention. From 2001 to 2005, 52 patients (mean: 59.8 years; 32 males/20 females) suffering from 106 unresectable lung metastases (mean:6 metastases/patient; range,1–21) were treated with 2–10 TPCE-sessions (mean: 3.3 sessions/patient). Metastases originated from primaries, including colorectal carcinoma (n = 20), breast cancer (n = 6), renal cellular carcinoma (n = 5), thyroid cancer (n = 4), cholangiocellular carcinoma (n = 2), leiomyosarcoma (n = 2), and others (n = 13). Tumor-feeding pulmonary arteries were selectively probed after puncturing the femoral vein, and administering 10 ml lipiodol, mitomycin C, and microspheres (Spherex) each via balloon catheter over pulmonary approach. During therapy, follow-up was accomplished at 4-week intervals using unenhanced and contrast-enhanced CT. After sequential therapy, follow-up was performed every 3 months for a period of 6 months up to 2.25 years. All patients tolerated the treatments well without major side effects or complications. In 24% (n = 13) moderate to high lipiodol uptake was found, while 75% (n = 39) of the tumors showed a low uptake. According to the RECIST criteria, “partial response” was achieved in 16 cases, “stable disease” in 11 cases, and “progressive disease” in 25 cases [mean survival: 17 months/median: 21.1 months (Kaplan-Meyer)]. According to these findings, TPCE is a well-tolerated procedure for palliative treatment of unresectable lung metastases.     

基于增强CT影像组学列线图预测单发肝细胞癌GPC3表达状态

目的 探讨增强CT影像组学列线图在鉴别单发肝细胞癌（HCC）磷脂酰肌醇蛋白聚糖3（GPC3）表达中的价值。方法 回顾性收集来自2个医疗机构共152例单发HCC病人的临床及影像资料,所有病人均行上腹部增强CT扫描并记录GPC3表达水平。天津市第一中心医院的106例病人资料作为训练集（GPC3阳性83例、阴性23例）,天津医科大学肿瘤医院的46例病人资料作为验证集（GPC3阳性35例、阴性11例）。对所有病人术前1个月内增强CT影像进行影像组学特征提取。在训练集中,对所有影像组学特征进行降维并得到最优子集,计算影像组学评分（Radscore）;比较GPC3阳性组和阴性组间临床资料[包括血清甲胎蛋白（AFP）、糖类抗原199（CA199）等]的差异,将差异有统计学意义的指标进行二元logistic回归分析,获得GPC3阳性的独立预测因素。将获得的临床信息及Radscore分别建立临床列线图、影像组学列线图及联合列线图。采用受试者操作特征曲线下面积（AUC）分析各列线图对GPC3表达状态的预测能力,采用DeLong检验比较各列线图间的诊断效能,并用决策曲线分析评估列线图的临床价值。使用验证集数据对列线图预测效能进行验证。结果 二元logistic回归显示血清AFP、CA199、Radscore是GPC3阳性的独立危险因素[优势比（OR）分别为8.503、1.090、13 300.044,均P<0.05]。校准曲线显示联合列线图对GPC3阳性表达的预测概率与实际概率一致性良好。训练集中,联合列线图的AUC（0.918）高于影像组学列线图（0.842）和临床列线图（0.787）（均P<0.05）,联合列线图的敏感度最高,而临床列线图的特异度最高;验证集中,联合列线图的AUC（0.896）高于影像组学列线图（0.726）和临床列线图（0.803）（均P<0.05）,联合列线图的敏感度和特异度均最高。决策曲线分析显示当阈值概率处于16%~86%时,联合列线图的临床净获益高于临床列线图和影像组学列线图。结论 基于增强CT的影像组学列线图可以术前鉴别单发HCC GPC3阳性和阴性表达,联合列线图进一步提高了预测效能。     

基于乳腺X线图像影像组学列线图对乳腺癌腋窝淋巴结转移的预测价值

目的:探讨基于乳腺X线图像影像组学列线图对乳腺癌腋窝淋巴结(ALN)转移的预测价值.方法:回顾性分析188例乳腺癌患者的乳腺X线图像和临床资料,按照7:3的比例将患者随机分割为训练组(n=130)和验证组(n=58).使用MaZda软件在乳腺X线图像内提取影像组学特征,应用方差选择法和最小绝对收缩与选择算子算法(LAS...     

Prediction of lymph node metastases using pre-treatment PET radiomics of the primary tumour in esophageal adenocarcinoma: an external validation study

Objectives:To improve clinical lymph node staging (cN-stage) in oesophageal adenocarcinoma by developing and externally validating three prediction models; one with clinical variables only, one with positron emission tomography (PET) radiomics only, and a combined clinical and radiomics model.Methods:Consecutive patients with fluorodeoxyglucose (FDG) avid tumours treated with neoadjuvant therapy between 2010 and 2016 in two international centres (n = 130 and n = 60, respectively) were included. Four clinical variables (age, gender, clinical T-stage and tumour regression grade) and PET radiomics from the primary tumour were used for model development. Diagnostic accuracy, area under curve (AUC), discrimination and calibration were calculated for each model. The prognostic significance was also assessed.Results:The incidence of lymph node metastases was 58% in both cohorts. The areas under the curve of the clinical, radiomics and combined models were 0.79, 0.69 and 0.82 in the developmental cohort, and 0.65, 0.63 and 0.69 in the external validation cohort, with good calibration demonstrated. The area under the curve of current cN-stage in development and validation cohorts was 0.60 and 0.66, respectively. For overall survival, the combined clinical and radiomics model achieved the best discrimination performance in the external validation cohort (X² = 6.08, df = 1, p = 0.01).Conclusion:Accurate diagnosis of lymph node metastases is crucial for prognosis and guiding treatment decisions. Despite finding improved predictive performance in the development cohort, the models using PET radiomics derived from the primary tumour were not fully replicated in an external validation cohort.Advances in knowledge:This international study attempted to externally validate a new prediction model for lymph node metastases using PET radiomics. A model combining clinical variables and PET radiomics improved discrimination of lymph node metastases, but these results were not externally replicated.     

Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer

Objectives:To investigate the ability of radiomic signatures based on MRI to evaluate the response and efficiency of neoadjuvant chemotherapy (NAC) for treating breast cancers.Methods:152 patients were included in this study at our institution between March 2017 and September 2019. All patients with breast cancer underwent a preoperative breast MRI and the Miller–Payne grading system was applied to evaluate response to NAC. Quantitative parameters were compared between patients with sensitive and insensitive responses to NAC and between those with pathological complete responses (pCR) and non-pCR. Four radiomic signatures were built based on T2W imaging, diffusion-weighted imaging, dynamic contrast-enhanced imaging and their combination, and radiomics scores (Rad-score) were calculated. The combination of the clinical factors and Rad-scores created a nomogram model. Multivariate logistic regression was performed to assess the association between MRI features and independent clinical risk factors.Results:20 features and 18 features were selected to build the radiomic signature for evaluating sensitivity and the possibility of pCR, respectively. The combined radiomic signature and nomogram model showed a similar discrimination in the training (AUC 0.91, 0.92, 95% confidence interval [CI], 0.85–0.96, 0.86–0.98) and validation (AUC 0.93, 0.91, 95% CI, 0.86–1.00, 0.82–1.00) sets. The clinical factor model exhibited reduced performance (AUC 0.74, 0.64, 95% CI, 0.64–0.84, 0.46–0.82) in terms of NAC sensitivity and pCR.Conclusions:The combined radiomic signature and nomogram model exhibited potential predictive power for predicting effective NAC treatment which can aid in the prognosis and guidance of treatment regimens.Advances in knowledge:Identifying a means of assessing the efficacy of NAC before surgery can guide follow-up treatment and avoid chemotherapy-induced toxicity.     

Post-mortem MRI-based volumetry of the hippocampus in forensic cases of decedents with severe mental illness

A decrease in the volume of the hippocampus is associated with severe mental illness, especially schizophrenia, and has been studied extensively in the living using magnetic resonance imaging. Autopsy cohorts also represent a valuable data source for imaging studies. However, post-mortem magnetic resonance imaging (PMMRI) is subject to unique challenges, such as the lower core temperature of scanned subjects and the influence of decomposition processes. This study aimed to determine if results from in vivo studies could be replicated on a post-mortem cohort of decedents who suffered from severe mental illness. We included 96 decedents with either schizophrenia (n = 34), depressive disorder (n = 17), or no known psychiatric diagnosis (n = 45) from April 2015 to January 2017. All cases underwent a T2-weighted cerebral MRI less than 24 h before autopsy. We used a manual segmentation algorithm to define the hippocampus on coronal images and subsequently estimate the volume of the region. The group with schizophrenia had a statistically significant 9.5% decrease in mean hippocampal volume compared with control subjects, while the group with depression trended towards a reduced volume, but this difference was not statistically significant. Thus we were able to replicate previous results from in vivo studies. PMMRI has unique potential for research in that it can be combined with procedures possible only in the research fields of clinical pathology and forensic science, e.g. histopathological sampling.     

Long-term safety and outcome of a temporary self-expanding metallic stent for achalasia: a prospective study with a 13-year single-center experience

To prospectively evaluate the long-term clinical safety and efficacy of a newly designed self-expanding metallic stent (SEMS) in the treatment of patients with achalasia. Seventy-five patients with achalasia were treated with a temporary SEMS with a 30-mm diameter. The SEMSs were placed under fluoroscopic guidance and removed by gastroscopy 4–5 days after stent placement. Follow-up data focused on dysphagia score, technique and clinical success, clinical remissions and failures, and complications and was performed at 6 months, 1 year, and within 3 to 5 years, 5 to 8 years, 8 to 10 years, and >10 years postoperatively. Stent placement was technically successful in all patients. Complications included stent migration (n = 4, 5.33%), chest pain (n = 28, 38.7%), reflux (n = 15, 20%), and bleeding (n = 9, 12%). No perforation or 30-day mortality occurred. Clinical success was achieved in all patients 1 month after stent removal. The overall remission rates at 6 months, 1, 1–3, 3–5, 5–8, 8–10, and >10 year follow-up periods were 100%, 96%, 93.9%, 90.9%, 100%, 100%, and 83.3%, respectively. Stent treatment failed in six patients, and the overall remission rate in our series was 92%. The median and mean primary patencies were 2.8 ± 0.28 years (95% CI: 2.25–3.35) and 4.28 ± 0.40 years (95% CI: 3.51–5.05), respectively. The use of temporary SEMSs with 30-mm diameter proved to be a safe and effective approach for managing achalasia with a long-term satisfactory clinical remission rate. Supported by the National Key Medical Research and Development Program of China during the 9th Five-year Plan Period (no. 96–907–03–04), Shanghai Nature Science Funds (no. 02Z1314073), Shanghai Medical Development Funds (no. 00419), the National Natural Science Foundation of China (no. 30670614).     

Superior performance of 18F-fluorocholine digital PET/CT in the detection of parathyroid adenomas

To compare detectability of hyperfunctioning parathyroid tissue (HPT) by digital and analog 18F-fluorocholine PET/CT in patients with primary hyperparathyroidism and negative/inconclusive 99mTc-MIBI scintigraphy-SPECT/CT. Thirty-three patients with primary hyperparathyroidism and negative/inconclusive 99mTc-MIBI scintigraphy-SPECT/CT were prospectively included. All patients accepted to be scanned by digital and analog PET/CT in the same imaging session after a single injection of 18F-fluorocholine. Three nuclear medicine physicians evaluated the digital and analog PET/CT datasets to assess the detection rate of HPT. Maximum standard uptake values (SUVmax) of HPT and locoregional lymph nodes were measured in both systems. HPT was detected in 30/33 patients by the digital system, whereas it was detected in 22/33 patients by the analog system (p < 0.01). Moreover, in 21 of these 33 patients, both systems detected one focal 18F-fluorocholine uptake, and in one patient the digital system detected two foci. Histopathology demonstrated HPT in 32 patients and it was inconclusive in one patient. The digital PET/CT detected HPT in 29 of the 32 patients, and the analog system in 22 of the 32 (p < 0.01). All HPT suspected lesions resected and detected only by the digital system (n = 8) were < 10 mm (7.5 ± 1.3 mm), while those detected by both systems (n = 22) were > 10 mm (13 ± 3.8 mm). SUVmax of HPT lesions was significantly higher than SUVmax of locoregional lymph node independently of the PET/CT system used (4.5 ± 1.9 vs. 2.9 ± 1.3, p < 0.0001). Digital PET/CT offers superior performance over analog system in patients with suspected HPT and previous negative/inconclusive imaging examinations, particularly in sub-centimeter lesions. SUVmax can help in the differentiation between HTP and locoregional lymph nodes.     

Diagnostic accuracy of contrast-enhanced FDG-PET/CT in primary staging of cutaneous malignant melanoma

Purpose  To evaluate the diagnostic accuracy of contrast-enhanced FDG-PET/CT (ce-PET/CT), PET-only, and CT-only in patients with newly diagnosed and resected cutaneous malignant melanoma. Methods  A final group of 56 patients (mean age 62 years, range 23–86 years; 29 women, 27 men) were staged with ce-PET/CT after resection of the primary tumour. Histopathology as well as clinical follow-up (mean 780 days, range 102–1,390 days) served as the standards of reference. Differences between the staging modalities were tested for statistical significance with McNemar’s test. Results  All imaging procedures provided low sensitivities in the detection of lymph nodes (sensitivity N-stage: PET/CT and PET-only 38.5%; CT-only 23.1%) and distant metastases (sensitivity M-stage: PET/CT 41.7%, PET-only 33.3%, CT-only 25.0%) in initial staging after resection of the primary tumour. No statistically significant differences were detected between the imaging procedures (p > 0.05). PET/CT resulted in an alteration in further treatment in two patients compared to PET-only and in four patients compared to CT-only. Conclusion  All imaging modalities had a low sensitivity on initial staging of patients with malignant melanoma. Thus, close patient follow-up must be considered mandatory.