Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Proteases and their inhibitors as prognostic factors for high-grade serous ovarian cancer

Ovarian carcinoma is one of the most lethal malignancies, but only very few prognostic biomarkers are known. The degradome, comprising proteases, protease non-proteolytic homologues and inhibitors, have been involved in the prognosis of many cancer types, including ovarian carcinoma. The prognostic significance of the whole degradome family has not been specifically studied in high-grade serous ovarian cancer. A targeted DNA microarray known as the CLIP-CHIP microarray was used to identify potential prognostic factors in ten high-grade serous ovarian cancer women who had early recurrence (<1.6 years) or late/no recurrence after first line surgery and chemotherapy. In women with early recurrence, we identified seven upregulated genes (TMPRSS4, MASP1/3, SPC18, PSMB1, IGFBP2, CFI – encoding Complement Factor I – and MMP9) and one down-regulated gene (ADAM-10). Using immunohistochemistry, we evaluated the prognostic effect of these 8 candidate genes in an independent cohort of 112 high-grade serous ovarian cancer women. Outcomes were progression, defined according to CA-125 criteria, and death. Multivariate Cox proportional hazard regression models were done to estimate the associations between each protein and each outcome. High ADAM-10 expression (intensity of 2–3) was associated with a lower risk of progression (adjusted hazard ratio (HR): 0.51; 95% confidence interval (CI): 0.29-0.87). High complement factor I expression (intensity 2–3) was associated with a higher risk of progression (adjusted HR: 2.30, 95% CI: 1.17–4.53) and death (adjusted HR: 3.42; 95% CI: 1.72–6.79). Overall, we identified the prognostic value of two proteases, ADAM-10 and complement factor I, for high-grade serous ovarian cancer which could have clinical significance.     

Germline gain-of-function MMP11 variant results in an aggressive form of colorectal cancer

Matrix metalloproteinase-11 (MMP11) is an enzyme with proteolytic activity against matrix and nonmatrix proteins. Although most MMPs are secreted as inactive proenzymes and are later activated extracellularly, MMP11 is activated intracellularly by furin within the constitutive secretory pathway. It is a key factor in physiological tissue remodeling and its alteration may play an important role in the progression of epithelial malignancies and other diseases. TCGA colon and colorectal adenocarcinoma data showed that upregulation of MMP11 expression correlates with tumorigenesis and malignancy. Here, we provide evidence that a germline variant in the MMP11 gene (NM_005940: c.232C>T; p.(Pro78Ser)), identified by whole exome sequencing, can increase the tumorigenic properties of colorectal cancer (CRC) cells. P78S is located in the prodomain region, which is responsible for blocking MMP11's protease activity. This variant was detected in the proband and all the cancer-affected family members analyzed, while it was not detected in healthy relatives. In silico analyses predict that P78S could have an impact on the activation of the enzyme. Furthermore, our in vitro analyses show that the expression of P78S in HCT116 cells increases tumor cell invasion and proliferation. In summary, our results show that this variant could modify the structure of the MMP11 prodomain, producing a premature or uncontrolled activation of the enzyme that may contribute to an early CRC onset in these patients. The study of this gene in other CRC cases will provide further information about its role in CRC development, which might improve patient treatment in the future.     

Improving Prenatal Diagnosis of Coarctation of the Aorta

Background

The purpose of the study was to evaluate the association between fetal echocardiographic measurements and the need for intervention (primary coarctation repair, staged coarctation repair, or catheter intervention) in prenatally diagnosed coarctation of the aorta.

Building and Exploitation of Learning Curves to Train Radiographer Students in X-Ray CT Image Postprocessing

IntroductionThis study aims to construct learning curves related to the realization of standardized postprocessing by radiographer students and to discuss their exploitation and interest.Materials and MethodsThis study was carried out in 21 French students in their 3rd year of training. Two postprocessing protocols in CT (#1 traumatic shoulder; #2 petrous bone) were repeated 15 times by each student. Each achievement was timed to obtain overall learning curves. The realization accuracy was also assessed for each student at each repetition.ResultsThe learning rates for the two protocols are 63% and 56%, respectively. The number of repetitions to reach the reference time for each protocol is 11 and 12, respectively. In both protocols, the standard deviations are significantly reduced and stabilized during repetitions. The mean accuracy progresses more quickly in protocol #1.DiscussionThe measured learning rates reflect a rapid learning process for each protocol. The analysis of the standard deviations shows that students have reached a homogeneous level. The average times and accuracies measured during the last repetitions show that the group has reached a high level of performance. Building learning curves helps students measure their progress and motivates them.ConclusionObtaining learning curves allows trainers/supervisors to qualify the learning difficulty of a task while motivating students/radiographers. The use of learning curves is inline with the competency-based training paradigm.     

X chromosomal and autosomal loss of heterozygosity and microsatellite instability in human cervical carcinoma

The study analyzes tumor material and normal tissue from 27 patients with pure squamous cell carcinoma of the uterine cervix for loss of heterozygosity (LOH) and microsatellite instability (MSI) on 14 autosomal and 11 X chromosomal loci. Overall, 4-40% of the informative cases showed LOH at autosomal regions with the highest frequency at 3p (21-40%) and a marked frequency at 2q35-q37.1 (12.5%) and 17p13.3 (10%), representing regions with putative tumor suppressor gene (TSG) function. The frequency of X chromosomal LOH ranged from 4% to 20%, with a maximum at Xq28 (20%) and Xq11.2-q12 (17%), again indicating alterations in TSG. A 12% LOH was seen at Xq21.33-q22.3, a region encoding a protein with a regulatory function in the cell cycle via cyclin-dependent kinases. MSI was detected in autosomal regions in up to 7% in regions linked to the X chromosome in up to 11%, probably indicating alterations of mismatch repair mechanisms. Our results and those obtained from the literature suggest that autosomal LOH and MSI in carcinomas of the cervix uteri are predominantly found at regions with putative TSG function. Beside TSG alterations, X chromosomal LOH is probably more strongly connected to disturbances in cell cycle regulation.     

肝细胞癌SCT表现和相关基因表达的初步研究

目的　探讨肝细胞癌细胞中nm2 3 H1基因和C erbB 2基因的表达和其与SCT表现的关系。方法　对 3 6例经手术病理证实且行螺旋CT动、静脉双期增强扫描的肝细胞癌病例 ,观察其SCT表现特征 ,如包膜、子灶、门静脉癌栓、肝门淋巴结转移、肿瘤的大小和强化特征。用免疫组织化学的方法检测癌组织中nm2 3 H1基因和C erbB 2基因的表达情况。结果　肝细胞癌细胞中 ,nm2 3 H1阳性 2 1例 ,阳性率为 5 8.3 % ,转移高危组 (子灶、门脉癌栓、肝门淋巴结转移 )nm2 3 H1基因的表达低于转移低危组 (P <0 .0 5 ) ;C erbB 2基因阳性 2 2例 ,阳性率为 71.1% ,C erbB 2基因的表达在中等大小肝癌组表达高于小肝癌组和大肝癌组 (P <0 .0 5 )。结论　肝细胞癌的SCT表现与nm2 3 H1和C erbB 2基因的表达有一定关系     

CT对直肠癌诊断价值的探讨附54例直肠癌的回顾性分析

目的 :根据直肠癌的 CT表现 ,探讨 CT对直肠癌的诊断价值。方法 :回顾性分析了 5 4例经手术和 /或活检病理证实的直肠癌病人的 CT资料 ,观察其 CT征象。结果 :典型直肠癌在 CT平扫时表现为低密度的软组织块影 ,肠壁不规则增厚 ,肠腔狭窄 ,增强扫描强化较明显 ,对于判断肿瘤大小及侵犯范围的价值最大。 期 18例 , 期 2 9例 , 期5例 , 期 2例。结论 :CT为直肠癌早期诊断 ,临床分期 ,判断治疗效果提供可靠依据     

CT-脑立体定向手术的临床应用

目的 评价CT－脑立体定向手术的临床应用价值。方法 应用CT－脑立体定向仪完成28例次脑立体定向手术，分析其临床诊疗效果。结果 立体定向活检术10例，术后病理诊断明确；定向开放手术12例，病灶一次切除；立体定向穿刺分流术6例，术后症状改善明显。手术均一次成功，无手术并发症。结论 CT－脑立体定向手术能精确定位，确定最佳手术路径，为颅内多种疾患的诊断和治疗提供新的方法。