Radiological Society of North America (RSNA) 3D Printing Special Interest Group (SIG) clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: Abdominal, hepatobiliary, and gastrointestinal conditions

BACKGROUND: Medical 3D printing has demonstrated value in anatomic models for abdominal, hepatobiliary, and gastrointestinal conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for abdominal, hepatobiliary, and gastrointestinal 3D printing indications. METHODS: A literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of abdominal pathologic processes. Each included study was graded according to published guidelines. RESULTS: Evidence-based appropriateness guidelines are provided for the following areas: intra-hepatic masses, hilar cholangiocarcinoma, biliary stenosis, biliary stones, gallbladder pathology, pancreatic cancer, pancreatitis, splenic disease, gastric pathology, small bowel pathology, colorectal cancer, perianal fistula, visceral trauma, hernia, abdominal sarcoma, abdominal wall masses, and intra-abdominal fluid collections. CONCLUSION: This document provides initial appropriate use criteria for medical 3D printing in abdominal, hepatobiliary, and gastrointestinal conditions

Gene hunting of the Genetic Analysis Workshop 16 rheumatoid arthritis data using rough set theory

We propose to use the rough set theory to identify genes affecting rheumatoid arthritis risk from the data collected by the North American Rheumatoid Arthritis Consortium. For each gene, we employ generalized dynamic reducts in the rough set theory to select a subset of single-nucleotide polymorphisms (SNPs) to represent the genetic information from this gene. We then group the study subjects into different clusters based on their genotype similarity at the selected markers. Statistical association between disease status and cluster membership is then studied to identify genes associated with rheumatoid arthritis. Based on our proposed approach, we are able to identify a number of statistically significant genes associated with rheumatoid arthritis. Aside from genes on chromosome 6, our identified genes include known disease-associated genes such as PTPN22 and TRAF1. In addition, our list contains other biologically plausible genes, such as ADAM15 and AGPAT2. Our findings suggest that ADAM15 and AGPAT2 may contribute to a genetic predisposition through abnormal angiogenesis and adipose tissue

Two-stage joint selection method to identify candidate markers from genome-wide association studies

The interaction among multiple genes and environmental factors can affect an individual's susceptibility to disease. Some genes may not show strong marginal associations when they affect disease risk through interactions with other genes. As a result, these genes may not be identified by single-marker methods that are widely used in genome-wide association studies. To explore this possibility in real data, we carried out a two-stage model selection procedure of joint single-nucleotide polymorphism (SNP) analysis to detect genes associated with rheumatoid arthritis (RA) using Genetic Analysis Workshop 16 genome-wide association study data. In the first stage, the genetic markers were screened through an exhaustive two-dimensional search, through which promising SNP and SNP pairs were identified. Then, LASSO was used to choose putative SNPs from the candidates identified in the first stage. We then use the RA data collected by the Wellcome Trust Case Control Consortium to validate the putative genetic factors. Balancing computational load and statistical power, this method detects joint effects that may fail to emerge from single-marker analysis. Based on our proposed approach, we not only replicated the identification of important RA risk genes, but also found novel genes and their epistatic effects on RA. To our knowledge, this is the first two-dimensional scan based analysis for a real genome-wide association study

Regional Multiple Pathology Scores Are Associated with Cognitive Decline in Lewy Body Dementias.

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are characterized by the presence of α-synuclein-containing Lewy bodies and Lewy neurites. However, both dementias also show variable degrees of Alzheimer's disease (AD) pathology (senile plaques and neurofibrillary tangles), particularly in areas of the cortex associated with higher cognitive functions. This study investigates the contribution of the individual and combined pathologies in determining the rate of cognitive decline. Cortical α-synuclein, phosphorylated tau (phosphotau) and Aβ plaque pathology in 34 PDD and 55 DLB patients was assessed semi-quantitatively in four regions of the neocortex. The decline in cognition, assessed by Mini Mental State Examination, correlated positively with the cortical α-synuclein load. Patients also had varying degrees of senile Aβ plaque and phosphotau pathology. Regression analyses pointed to a combined pathology (Aβ plaque plus phosphotau plus α-synuclein-positive features), particularly in the prefrontal cortex (BA9) and temporal lobe neocortex with the superior and middle temporal gyrus (BA21, 22), being a major determining factor in the development of dementia. Thus, cognitive decline in Lewy body dementias is not a consequence of α-synuclein-induced neurodegeneration alone but senile plaque and phosphorylated tau pathology also contribute to the overall deficits.The main fundingwas provided by the Alzheimer’s SocietyUK and the BUPA Foundation. The research in Newcastle was supported in part by the Dunhill Medical Trust (R173/1110). Tissue for this study was provided by (i) the Newcastle Brain Tissue Resource; (ii) the London Neurodegenerative Brain Bank; and (iii) the Thomas Willis Oxford Brain Collection. All three resources are funded in part by grants from the UK Medical Research Council and by Brains for Dementia Research, a joint venture between Alzheimer’s Society and Alzheimer’s Research UK. In Singapore, funding was provided by a Centre grant (NMRC/CG/NUHS/2010) and a Clinical Scientist Award (NMRC/CSA/032/2011) from the National Medical Research Council.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1111/bpa.12182/abstract

Regional Multiple Pathology Scores Are Associated with Cognitive Decline in Lewy Body Dementias

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Decision-making based on 3D printed models in laparoscopic liver resections with intraoperative ultrasound: A prospective observational study

OBJECTIVES: The aim of this study was to evaluate impact of 3D printed models on decision-making in context of laparoscopic liver resections (LLR) performed with intraoperative ultrasound (IOUS) guidance. METHODS: Nineteen patients with liver malignances (74% were colorectal cancer metastases) were prospectively qualified for LLR or radiofrequency ablation in a single center from April 2017 to December 2018. Models were 3DP in all cases based on CT and facilitated optical visualization of tumors\u27 relationships with portal and hepatic veins. Planned surgical extent and its changes were tracked after CT analysis and 3D model inspection, as well as intraoperatively using IOUS. RESULTS: Nineteen patients were included in the analysis. Information from either 3DP or IOUS led to changes in the planned surgical approach in 13/19 (68%) patients. In 5/19 (26%) patients, the 3DP model altered the plan of the surgery preoperatively. In 4/19 (21%) patients, 3DP independently changed the approach. In one patient, IOUS modified the plan post-3DP. In 8/19 (42%) patients, 3DP model did not change the approach, whereas IOUS did. In total, IOUS altered surgical plans in 9 (47%) cases. Most of those changes (6/9; 67%) were caused by detection of additional lesions not visible on CT and 3DP. CONCLUSIONS: 3DP can be helpful in planning complex and major LLRs and led to changes in surgical approach in 26.3% (5/19 patients) in our series. 3DP may serve as a useful adjunct to IOUS. KEY POINTS: • 3D printing can help in decision-making before major and complex resections in patients with liver cancer. • In 5/19 patients, 3D printed model altered surgical plan preoperatively. • Most surgical plan changes based on intraoperative ultrasonography were caused by detection of additional lesions not visible on CT and 3D model