Risk factors associated with complex inferior vena cava filter retrievals and complications: A 7-year retrieval database analysis and the impact on retrieval rates at an Australian tertiary centre.

INTRODUCTION: Venous thromboembolism (VTE) affects approximately 17,000 Australians annually. While anticoagulation is the mainstay of treatment, inferior vena cava filters (IVCFs) are used in patients where this is contraindicated. The primary aim was to identify risk factors for complex retrievals and IVCF-related complications following the establishment of a database at a single tertiary centre. The secondary aim was to evaluate the IVCF retrieval rate and patients lost to follow-up. METHODS: A retrospective study at a single tertiary centre was conducted on IVCFs inserted from 2012 to 2018. Logistic regression models were used to evaluate potential risk factors for filter-related complications and complex retrievals. RESULTS: In total, 402 patients had an IVCF inserted. Of these, 308 patients (77%) had a retrieval attempted, 10 (3%) of which required more than one retrieval attempt (complex retrieval). Factors associated with filter-related complications included dwell time (OR 1.02, 95% CI: 1.01-1.04) and select indications for insertion, namely VTE requiring thrombolysis/thrombectomy (OR 2.29, 95% CI: 1.02-5.16) and iliocaval/free-floating iliofemoral DVT without thrombectomy/thrombolysis (OR 5.89, 95% CI: 1.53-22.71). After mutual adjustment for all variables, only dwell time remained a significant factor for filter-related complications (adjusted OR 1.03, 95% CI: 1.01-1.05) and complex retrieval (AOR 1.05, 95% CI: 1.02-1.08). The annual retrieval rate increased from 73% (2012) to 83% (2018), with an overall retrieval rate of 75%. CONCLUSION: Dwell time is a potential risk factor for filter-related complications and complex retrievals. The annual IVCF retrieval rate was 75% since an Interventional Radiology-led database was established.

CT-based radiomics for differentiating renal tumours: a systematic review.

PURPOSE: Differentiating renal tumours into grades and tumour subtype from medical imaging is important for patient management; however, there is an element of subjectivity when performed qualitatively. Quantitative analysis such as radiomics may provide a more objective approach. The purpose of this article is to systematically review the literature on computed tomography (CT) radiomics for grading and differentiating renal tumour subtypes. An educational perspective will also be provided. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed. PubMed, Scopus and Web of Science were searched for relevant articles. The quality of each study was assessed using the Radiomic Quality Score (RQS). RESULTS: 13 studies were found. The main outcomes were prediction of pathological grade and differentiating between renal tumour types, measured as area under the curve (AUC) for either the receiver operator curve or precision recall curve. Features extracted to predict pathological grade or tumour subtype included shape, intensity, texture and wavelet (a type of higher order feature). Four studies differentiated between low-grade and high-grade clear cell renal cell cancer (RCC) with good performance (AUC = 0.82-0.978). One other study differentiated low- and high-grade chromophobe with AUC = 0.84. Finally, eight studies used radiomics to differentiate between tumour types such as clear cell RCC, fat-poor angiomyolipoma, papillary RCC, chromophobe RCC and renal oncocytoma with high levels of performance (AUC 0.82-0.96). CONCLUSION: Renal tumours can be pathologically classified using CT-based radiomics with good performance. The main radiomic feature used for tumour differentiation was texture. Fuhrman was the most common pathologic grading system used in the reviewed studies. Renal tumour grading studies should be extended beyond clear cell RCC and chromophobe RCC. Further research with larger prospective studies, performed in the clinical setting, across multiple institutions would help with clinical translation to the radiologist's workstation.