Combined genicular artery embolization and genicular nerve block to treat chronic pain following total knee arthroplasty.

BACKGROUND: Chronic knee pain after total knee arthroplasty (TKA) is a common complication that is difficult to treat. This report aims to highlight the benefit of combining embolotherapy and neurolysis intervention for symptomatic relief of post-TKA pain in a patient with long-standing pain refractory to conservative management. CASE PRESENTATION: A 77-year-old man who had previously undergone left knee arthroplasty has been grappling with worsening knee effusion and debilitating pain, resulting in limited mobility and progressive musculature deconditioning over a 20-year period. Diagnostic arteriography showed marked diffuse periarticular hyperemia around the medial and lateral joint spaces of the left knee, along with capsular distention. The patient initially underwent microsphere embolization to selectively target multiple branches of the genicular arteries, achieving a 50% reduction in pain at the one-month follow-up. Subsequently, the patient underwent image-guided genicular nerve neurolysis, targeting multiple branches of the genicular nerves, which led to further pain reduction (80% compared to the initial presentation or 60% compared to post-embolization) at the one-month follow-up. This improvement facilitated weight-bearing and enabled participation in physical therapy, with sustained pain relief over the 10-month follow-up period. CONCLUSION: The combination of genicular artery embolization and genicular nerve block may be a technically safe and effective option for alleviating chronic pain after total knee arthroplasty.

Artificial Intelligence System for Automatic Quantitative Analysis and Radiology Reporting of Leg Length Radiographs.

Leg length discrepancies are common orthopedic problems with the potential for poor functional outcomes. These are frequently assessed using bilateral leg length radiographs. The objective was to determine whether an artificial intelligence (AI)-based image analysis system can accurately interpret long leg length radiographic images. We built an end-to-end system to analyze leg length radiographs and generate reports like radiologists, which involves measurement of lengths (femur, tibia, entire leg) and angles (mechanical axis and pelvic tilt), describes presence and location of orthopedic hardware, and reports laterality discrepancies. After IRB approval, a dataset of 1,726 extremities (863 images) from consecutive examinations at a tertiary referral center was retrospectively acquired and partitioned into train/validation and test sets. The training set was annotated and used to train a fasterRCNN-ResNet101 object detection convolutional neural network. A second-stage classifier using a EfficientNet-D0 model was trained to recognize the presence or absence of hardware within extracted joint image patches. The system was deployed in a custom web application that generated a preliminary radiology report. Performance of the system was evaluated using a holdout 220 image test set, annotated by 3 musculoskeletal fellowship trained radiologists. At the object detection level, the system demonstrated a recall of 0.98 and precision of 0.96 in detecting anatomic landmarks. Correlation coefficients between radiologist and AI-generated measurements for femur, tibia, and whole-leg lengths were > 0.99, with mean error of < 1%. Correlation coefficients for mechanical axis angle and pelvic tilt were 0.98 and 0.86, respectively, with mean absolute error of < 1°. AI hardware detection demonstrated an accuracy of 99.8%. Automatic quantitative and qualitative analysis of leg length radiographs using deep learning is feasible and holds potential in improving radiologist workflow.

Patient and tumor characteristics can predict nondiagnostic renal mass biopsy findings.

PURPOSE: Identification of patient and tumor characteristics associated with nondiagnostic biopsies is necessary to improve prebiopsy counseling and patient selection. MATERIALS AND METHODS: We reviewed the clinical records and prebiopsy imaging of all patients treated with percutaneous biopsy for a renal mass 7 cm or less. Univariate and multivariate logistic regression models were constructed to examine the association between biopsy outcome and clinical/radiographic features. RESULTS: A total of 565 biopsies of renal tumors 7 cm or less in 525 patients were included in the study. There was no significant difference in age, body mass index, Charlson comorbidity score or gender between the patient cohorts with diagnostic and nondiagnostic biopsy. In 83 of 565 patients (14.7%) overall and in 72 of the 413 (17.4%) with a mass of 4 cm or less the biopsy findings were nondiagnostic. Overall 14.7% of masses were cystic and 85.3% were solid with a median tumor size of 2.75 cm (IQR 2.05-4.25). Independent predictors of nondiagnostic biopsy included cystic features, enhancement less than 20 HU, left tumor, tumor diameter and skin-to-tumor distance. The nondiagnostic rate of repeat biopsies was 20.8%, which did not statistically differ from the nondiagnostic rate at the initial renal mass biopsy attempt. Radiologist or pathologist experience was not associated with the biopsy nondiagnostic rate. In 7 of 565 patients (1.2%) hospital admission was required for adverse events after biopsy. CONCLUSIONS: Nondiagnostic renal mass biopsies are more common in cystic, nonenhancing, small masses when patients have a skin-to-tumor distance of 13 cm or greater. Excluding patients with these criteria decreased the nondiagnostic rate from 14.7% to 8.7%.

Quantitative hepatic perfusion modeling using DCE-MRI with sequential breathholds.

PURPOSE: To develop and demonstrate the feasibility of a new formulation for quantitative perfusion modeling in the liver using interrupted DCE-MRI data acquired during multiple sequential breathholds. MATERIALS AND METHODS: A new mathematical formulation to estimate quantitative perfusion parameters using interrupted data was developed. Using this method, we investigated whether a second degree-of-freedom in the tissue residue function (TRF) improves quality-of-fit criteria when applied to a dual-input single-compartment perfusion model. We subsequently estimated hepatic perfusion parameters using DCE-MRI data from 12 healthy volunteers and 9 cirrhotic patients with a history of hepatocellular carcinoma (HCC); and examined the utility of these estimates in differentiating between healthy liver, cirrhotic liver, and HCC. RESULTS: Quality-of-fit criteria in all groups were improved using a Weibull TRF (2 degrees-of-freedom) versus an exponential TRF (1 degree-of-freedom), indicating nearer concordance of source DCE-MRI data with the Weibull model. Using the Weibull TRF, arterial fraction was greater in cirrhotic versus normal liver (39 ± 23% versus 15 ± 14%, P = 0.07). Mean transit time (20.6 ± 4.1 s versus 9.8 ± 3.5 s, P = 0.01) and arterial fraction (39 ± 23% versus 73 ± 14%, P = 0.04) were both significantly different between cirrhotic liver and HCC, while differences in total perfusion approached significance. CONCLUSION: This work demonstrates the feasibility of estimating hepatic perfusion parameters using interrupted data acquired during sequential breathholds.

Non-contrast enhanced 3D SSFP MRA of the renal allograft vasculature: a comparison between radial linear combination and Cartesian inflow-weighted acquisitions.

Renal transplant patients often require imaging to ensure appropriate graft placement, to assess integrity of transplant vessel anastomosis and to evaluate for stenosis that can be a cause of graft failure. Because there is risk for nephrogenic systemic fibrosis in the setting of renal insufficiency, the use of non-contrast MRA in these patients is helpful. In this study, the ability of two non-contrast MRA methods - 3D radial linear combination balanced SSFP (VIPR-SSFP) and inflow-weighted Cartesian SSFP (IFIR) - to visualize the transplant renal vessels is compared. Twenty-one renal transplant patients were scanned using the VIPR-SSFP and IFIR sequences. Diagnostic efficacy of the sequences was scored using a four point Likert scale according to the following criteria: overall image quality, fat suppression, and arterial/venous visualization quality. Average scores for each criterion were compared using the Wilcoxon signed-rank test. In addition to significantly improved venous visualization, the VIPR-SSFP sequence provided significantly improved fat suppression quality (p<0.03) compared to IFIR. VIPR-SSFP also identified several pathologies such as renal arterial pseudoaneurysm that were not visible on the IFIR images. However, IFIR afforded superior quality of arterial visualization (p<0.005). These two methods of non-contrast MR imaging each have significant strengths and are complementary to each other in evaluating the vasculature of renal allografts.

High-spatial and high-temporal resolution dynamic contrast-enhanced perfusion imaging of the liver with time-resolved three-dimensional radial MRI.

PURPOSE: Detection, characterization, and monitoring the treatment of hepatocellular carcinomas (HCC) in patients with cirrhosis is challenging because of their variable and rapid arterial enhancement. Multiphase dynamic contrast-enhanced MRI is used clinically for HCC assessment; however, the method suffers from limited temporal resolution and difficulty in coordinating imaging and breath-hold timing within a narrow temporal window of interest. In this article, a volumetric, high-spatial resolution, and high-temporal resolution dynamic contrast-enhanced liver imaging method for improved detection and characterization of HCC is demonstrated. METHODS: A time-resolved three-dimensional radial acquisition with iterative sensitivity-encoding reconstruction images the entire abdomen and thorax with high spatial and temporal resolution, using real-time three-dimensional fluoroscopy to match the breath hold to contrast arrival. The sequence was tested on 17 subjects, including eight patients with HCC or other hypervascular focal lesions. RESULTS: This technique was successful in acquiring volumetric imaging of the entire liver with 2.1-mm isotropic spatial and true 4-s temporal resolution. CONCLUSION: This technique may be suitable for detecting, characterizing, and monitoring the treatment of HCC. It also holds significant potential for perfusion modeling, which may provide a noninvasive means to rapidly determine the efficacy of chemotherapeutic agents in these tumors over the entire liver volume.

Validation of MRI biomarkers of hepatic steatosis in the presence of iron overload in the ob/ob mouse.

PURPOSE: To validate the utility and performance of a T 2 correction method for hepatic fat quantification in an animal model of both steatosis and iron overload. MATERIALS AND METHODS: Mice with low (n = 6), medium (n = 6), and high (n = 8) levels of steatosis were sedated and imaged using a chemical shift-based fat-water separation method to obtain magnetic resonance imaging (MRI) fat-fraction measurements. Imaging was performed before and after each of two superparamagnetic iron oxide (SPIO) injections to create hepatic iron overload. Fat-fraction maps were reconstructed with and without T 2 correction. Fat-fraction with and without T 2 correction and T 2 measurements were compared after each injection. Liver tissue was harvested and imaging results were compared to triglyceride extraction and histology grading. RESULTS: Excellent correlation was seen between MRI fat-fraction and tissue-based fat quantification. Injections of SPIOs led to increases in R 2 (=1/T 2). Measured fat-fraction was unaffected by the presence of iron when T 2 correction was used, whereas measured fat-fraction dramatically increased without T 2 correction. CONCLUSION: Hepatic fat-fraction measured using a T 2-corrected chemical shift-based fat-water separation method was validated in an animal model of steatosis and iron overload. T 2 correction enables robust fat-fraction estimation in both the presence and absence of iron, and is necessary for accurate hepatic fat quantification.

Pulsed EPR investigations of systems modeling molybdenum enzymes: hyperfine and quadrupole parameters of oxo-17O in [Mo 17O(SPh)4]-.

Ka band ESEEM spectroscopy was used to determine the hyperfine (hfi) and nuclear quadrupole (nqi) interaction parameters for the oxo-17O ligand in [Mo 17O(SPh)4]-, a spectroscopic model of the oxo-Mo(V) centers of enzymes. The isotropic hfi constant of 6.5 MHz found for the oxo-17O is much smaller than the values of approximately 20-40 MHz typical for the 17O nucleus of an equatorial OH(2) ligand in molybdenum enzymes. The 17O nqi parameter (e2qQ/h = 1.45 MHz, eta approximately = 0) is the first to be obtained for an oxo group in a metal complex. The parameters of the oxo-17O ligand, as well as other magnetic resonance parameters of [Mo 17O(SPh)4]- predicted by quasi-relativistic DFT calculations, were in good agreement with those obtained in experiment. From the electronic structure of the complex revealed by DFT, it follows that the SOMO is almost entirely molybdenum d(xy) and sulfur p, while the spin density on the oxo-17O is negative, determined by spin polarization mechanisms. The results of this work will enable direct experimental identification of the oxo ligand in a variety of chemical and biological systems.