Novel Use of Fractal Analysis for Quantifying Polymethylmethacrylate Distribution Patterns in Osteoporotic and Malignant Vertebral Compression Fractures Following Vertebroplasty.

Purpose: Fractal analysis is a mathematical tool which allows the evaluation of complex microstructural features within materials that cannot be expressed in traditional geometric terms. The purpose of this study is to quantify the differences in polymethylmethacrylate intravertebral cement spatial distribution patterns following vertebroplasty using fractal analysis through the examination of osteoporotic and malignant compression fractures. Methods: Frontal and lateral post-vertebroplasty radiographs were evaluated from 29 patients with osteoporotic and malignant compression fractures who underwent vertebroplasty. The individually treated vertebra were divided into osteoporotic (n = 35) and malignant groups (n = 41). Images underwent segmentation, thresholding, and binarization prior to fractal analysis. Fractal dimension and lacunarity values were derived from the region of interest in treated vertebrae using the "box-counting" and "gliding-box" techniques respectively using ImageJ. The mean values of both parameters were compared between the 2 groups. Results: The mean fractal dimension was significantly higher in the malignant vertebral compression fracture group (1.53 ± 0.08) compared to the osteoporotic group (1.34 ± 0.17; P < .001). Similarly, mean lacunarity values were significantly higher in the malignant fracture group (0.50 ± 0.09) compared to the osteoporotic group (0.37 ± 0.10; P < .001). Conclusions: Fractal dimension and lacunarity values of cement spatial distribution patterns obtained from the post-vertebroplasty radiographs can differentiate between benign osteoporotic and malignant vertebral compression fractures. This novel technique may be useful for evaluating cement spatial distribution patterns in spine augmentation procedures, although further research is warranted in this area.

Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology.

BACKGROUND AND PURPOSE: Interest in artificial intelligence (AI) and machine learning (ML) has been growing in neuroradiology, but there is limited knowledge on how this interest has manifested into research and specifically, its qualities and characteristics. This study aims to characterize the emergence and evolution of AI/ML articles within neuroradiology and provide a comprehensive overview of the trends, challenges, and future directions of the field. MATERIALS AND METHODS: We performed a bibliometric analysis of the American Journal of Neuroradiology (AJNR): the journal was queried for original research articles published since inception (Jan. 1, 1980) to Dec. 3, 2022 that contained any of the following key terms: "machine learning", "artificial intelligence", "radiomics", "deep learning", "neural network", "generative adversarial network", "object detection", or "natural language processing". Articles were screened by two independent reviewers, and categorized into Statistical Modelling (Type 1), AI/ML Development (Type 2), both representing developmental research work but without a direct clinical integration, or End-user Application (Type 3) which is the closest surrogate of potential AI/ML integration into day-to-day practice. To better understand the limiting factors to Type 3 articles being published, we analyzed Type 2 articles as they should represent the precursor work leading to Type 3. RESULTS: A total of 182 articles were identified with 79% being non-integration focused (Type 1 n = 53, Type 2 n = 90) and 21% (n = 39) being Type 3. The total number of articles published grew roughly five-fold in the last five years, with the non-integration focused articles mainly driving this growth. Additionally, a minority of Type 2 articles addressed bias (22%) and explainability (16%). These articles were primarily led by radiologists (63%), with most of them (60%) having additional postgraduate degrees. CONCLUSIONS: AI/ML publications have been rapidly increasing in neuroradiology with only a minority of this growth being attributable to end-user application. Areas identified for improvement include enhancing the quality of Type 2 articles, namely external validation, and addressing both bias and explainability. These results ultimately provide authors, editors, clinicians, and policymakers important insights to promote a shift towards integrating practical AI/ML solutions in neuroradiology. ABBREVIATIONS: AI = artificial intelligence; ML = machine learning.

Management of Tarlov cysts: an uncommon but potentially serious spinal column disease-review of the literature and experience with over 1000 referrals.

Tarlov cysts were thought to be anatomic variants of uncertain etiology and clinical significance when initially described over 80 years ago. They are often detected in routine lumbosacral imaging and generally not reported in a differential diagnosis. There is increasing evidence that at least some Tarlov cysts are symptomatic and can have a significant adverse impact on patients' health and well-being. Women are disproportionately affected with this condition, often presenting with long-standing pain and neurological dysfunctions. Significant gender bias has been a concern in the management of these patients. Unfortunately, there is no consensus on patient selection or management approaches for symptomatic Tarlov cysts. This review article updates information on the prevalence, diagnosis, clinical significance, and treatments of these cysts. Based on these findings and experience with over 1000 patient referrals, a treatment decision algorithm for symptomatic Tarlov cysts was constructed to provide guidance for appropriate management of patients with these complex cysts.

Cost-effectiveness and willing-to-pay thresholds for vertebral augmentation of osteoporotic vertebral fractures, what are they based on: a systematic review.

OBJECTIVE: Although there is substantial clinical evidence on the safety and effectiveness of vertebral augmentation for osteoporotic vertebral fractures, cost-effectiveness is less well known. The objective of this study is to provide a systematic review of cost-effectiveness studies and policy-based willingness-to-pay (WTP) thresholds for different vertebral augmentation (VA) procedures, vertebroplasty (VP) and balloon kyphoplasty (BK), for osteoporotic vertebral fractures (OVFs). DESIGN: A systematic review targeting cost-effectiveness studies of VA procedures for OVFs. DATA SOURCES: Six bibliographic databases were searched from inception up to May 2021. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Studies were eligible if meeting all predefined criteria: (1) VP or BK intervention, (2) OVFs and (3) cost-effectiveness study. Articles not written in English, abstracts, editorials, reviews and those reporting only cost data were excluded. DATA EXTRACTION AND SYNTHESIS: Information was extracted on study characteristics, cost-effective estimates, summary decisions and payer WTP thresholds. Incremental cost-effective ratio (ICER) was the main outcome measure. Studies were summarised by a structured narrative synthesis organised by comparisons with conservative management (CM). Two independent reviewers assessed the quality (risk of bias) of the systematic review and cost-effectiveness studies by peer-reviewed checklists. RESULTS: We identified 520 references through database searching and 501 were excluded as ineligible by titles and abstract. Ten reports were identified as eligible from 19 full-text reviews. ICER for VP versus CM evaluated as cost per quality-adjusted life-year (QALY) ranged from €22 685 (*US$33 395) in Netherlands to £-2240 (*US$-3273), a cost-saving in the UK. ICERs for BK versus CM ranged from £2706 (*US$3954) in UK to kr600 000 (*US$90 910) in Sweden. ICERs were within payer WTP thresholds for a QALY based on historical benchmarks. CONCLUSIONS: Both VP and BK were judged cost-effective alternatives to CM for OVFs in economic studies and were within WTP thresholds in multiple healthcare settings.

Successful radiological embolization of a low output jejunal enterocutaneous fistula using a cyanoacrylate and lipiodol mixture.

Enterocutaneous fistulas (ECFs) are a significant complication of abdominal surgery which present a significant therapeutic challenge for clinicians. Definitive surgical treatment of these fistulas is not without significant risk, which both patients and clinicians would seek to avoid. We present a case of successful treatment of a low output jejunal ECF by percutaneous embolization using an ethiodized oil and n-butyl-2-cyanoacrylate glue mixture in a 40-year-old man who developed an ECF after inadvertent jejunostomy tube removal. This case demonstrates the technique and suitability of a widely available embolic agent for treatment of proximal small bowel ECFs. In addition, the case illustrates the potential of minimally invasive interventional radiological procedures in the management of ECFs, particularly in high-risk patients, as an alternative to surgery.

Aortic Pulsatility Propagates Intracranially and Correlates with Dilated Perivascular Spaces and Small Vessel Compliance.

INTRODUCTION: To test the hypotheses that changes in the aortic pulse-wave produced by arterial stiffening are (1) propagated into cerebral small vessels, (2) associated with reduced compliance of small cerebral arterial vessels, and (3) associated with the presence of dilated perivascular spaces (PVS). METHODS: Fifteen volunteers and 19 patients with late-onset depression (LOD) were prospectively recruited, of which 6 fulfilled the criteria for treatment-resistant depression (TRD). Aortic pulse-wave velocity (PWV) was determined using Carotid-Femoral Doppler. Pulse-wave analysis (PWA) was performed using a SphygmoCor system. White-matter lesion load and PVS were scored on established MRI scales. Cerebral arterial and aqueductal cerebrospinal fluid (CSF) flow patterns were studied using quantitative phase-contrast angiography. RESULTS: Depressed patients had more PVS (P < .05) and prolongation of the width of the arterial systolic pulse-wave in the carotid arteries (P < .01). There was no significant group difference for any PWV or PWA measurement. TRD patients showed more PVS than other LOD patients (P < .05). The fractional width of the arterial systolic peak correlated significantly with augmentation index (AIx) and heart rate-corrected augmentation index (AIx75; R2 = 0.302, P < .01and R2 = 0.363, P < .01 respectively). Arterial-aqueductal delay showed a negative correlation with estimated aortic systolic pressure (PWVsys; R2 =  0.293; P < .01), AIx (R2 = -0.491; P < .01) and AIx75 (R2 = -0.310; P < .01). PVS scores correlated with AIx (R2 = 0.485; P < .01) and AIx75 (R2 = -0.292; P < .01). CONCLUSION: Our findings support the hypothesis that increased arterial pulsatility resulting from central arterial stiffness propagates directly into cerebral vessels and is associated with the development of microvascular angiopathy, characterized by dilated PVS and decreased compliance of small arterial vessels.