3D-navigation for SI screw fixation - How does it affect radiation exposure for patients and medical personnel?

BACKGROUND: 3D-navigation for percutaneous sacroiliac (SI) screw fixation is becoming increasingly common and several studies report great advantages of this technology. However, there is still limited clinical evidence on the efficacy regarding radiation exposure for patient and personnel. METHODS: This is a retrospective, single-center cohort study. All patients who underwent percutaneous sacroiliac screw fixation for an injury of the posterior pelvic ring from 2014 to 2021 were screened. Inclusion criteria were: conclusive radiation dosage reports, signed informed consent, a twelve month follow up and a complete data set. Patients were stratified in two groups (3D-navigation (Group 3D-N) vs. control (Group F)) based on the imaging modality used. Primary outcomes were radiation exposure for patient and personnel. Secondary outcomes were reoperations, complications, and intraoperative precision. RESULTS: Of 392 patients screened, 174 patients (3D-N: n = 50, F: n = 124) could be included for final analysis. We noted a significant reduction of the dose corresponding to potential radiation exposure for medical personnel (-15.3 mGy, 95 %CI: -2.1 to -28.5, p = 0.0232), but also a significant increase of the dose quantifying radiation exposure for patients (+77.0 mGy, 95 %CI: +53.3 to +100.6, p < 0.0001), when using navigation. In addition, the rate of radiographic malplacement was significantly reduced (F: 11.3% vs. 3D-N: 0 %, p = 0.0113) despite a substantial increase in transsacral screw placement (F: 19.4% vs. 3D-N: 76 %). CONCLUSION: Our data clearly suggests that the use of 3D-navigation for percutaneous SI screw fixation decreases radiation exposure for medical personnel, while increasing radiation exposure for patients. Furthermore, intraoperative precision is improved, even in more challenging operations.

Fully automated breast segmentation on spiral breast computed tomography images.

INTRODUCTION: The quantification of the amount of the glandular tissue and breast density is important to assess breast cancer risk. Novel photon-counting breast computed tomography (CT) technology has the potential to quantify them. For accurate analysis, a dedicated method to segment the breast components-the adipose and glandular tissue, skin, pectoralis muscle, skinfold section, rib, and implant-is required. We propose a fully automated breast segmentation method for breast CT images. METHODS: The framework consists of four parts: (1) investigate, (2) segment the components excluding adipose and glandular tissue, (3) assess the breast density, and (4) iteratively segment the glandular tissue according to the estimated density. For the method, adapted seeded watershed and region growing algorithm were dedicatedly developed for the breast CT images and optimized on 68 breast images. The segmentation performance was qualitatively (five-point Likert scale) and quantitatively (Dice similarity coefficient [DSC] and difference coefficient [DC]) demonstrated according to human reading by experienced radiologists. RESULTS: The performance evaluation on each component and overall segmentation for 17 breast CT images resulted in DSCs ranging 0.90-0.97 and in DCs 0.01-0.08. The readers rated 4.5-4.8 (5 highest score) with an excellent inter-reader agreement. The breast density varied by 3.7%-7.1% when including mis-segmented muscle or skin. CONCLUSION: The automatic segmentation results coincided with the human expert's reading. The accurate segmentation is important to avoid the significant bias in breast density analysis. Our method enables accurate quantification of the breast density and amount of the glandular tissue that is directly related to breast cancer risk.

Efficiency evaluation of leaded glasses and visors for eye lens dose reduction during fluoroscopy guided interventional procedures.

PURPOSE: Fluoroscopy guided interventional procedures guarantee high benefits for patients, but are associated with high levels of radiation exposure for the medical staff. Their increasing use and complexity results in even higher radiation exposures, with a risk to exceed the annual dose limit of 20 mSv for the eye lens. The aim of the study was to evaluate the potential dose reduction of eye lens exposure for lead glasses and for two types of visors (half and full), used by physicians performing interventional procedures. METHODS: Eye lens dose measurements were carried out on an anthropomorphic phantom simulating a physician performing a fluoroscopy guided interventional procedure. Dose reduction factors were calculated using high sensitivity thermoluminescent dosimeters. Moreover, a spatial dose distribution was generated for the two visors. RESULTS: The dose reduction coefficient was found to be 1.6 for the glasses, 1.2 for the half visor and 4.5 for the full visor. CONCLUSIONS: Optimal radiation protection requires a combination of different radiation protection equipment. Full visors that cover all the face of the operator are recommended, as they absorb scattered radiation reaching the eyes from all directions. Full visors should be prioritized over radiation protection glasses for cases where other protective equipment such as ceiling shielding cannot be used.

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance.

BACKGROUND: To compare task-based image quality (TB-IQ) among virtual monoenergetic images (VMI) and linear-blended images (LBI) from dual-energy CT as a function of contrast task, radiation dose, size, and lesion diameter. METHODS: A TB-IQ phantom (Mercury Phantom 4.0, Sun Nuclear Corporation) was imaged on a third-generation dual-source dual-energy CT with 100/Sn150 kVp at three volume CT dose levels (5, 10, 15 mGy). Three size sections (diameters 16, 26, 36 cm) with subsections for image noise and spatial resolution analysis were used. High-contrast tasks (e.g., calcium-containing stone and vascular lesion) were emulated using bone and iodine inserts. A low-contrast task (e.g., low-contrast lesion or hematoma) was emulated using a polystyrene insert. VMI at 40-190 keV and LBI were reconstructed. Noise power spectrum (NPS) determined the noise magnitude and texture. Spatial resolution was assessed using the task-transfer function (TTF) of the three inserts. The detectability index (d') served as TB-IQ metric. RESULTS: Noise magnitude increased with increasing phantom size, decreasing dose, and decreasing VMI-energy. Overall, noise magnitude was higher for VMI at 40-60 keV compared to LBI (range of noise increase, 3-124%). Blotchier noise texture was found for low and high VMIs (40-60 keV, 130-190 keV) compared to LBI. No difference in spatial resolution was observed for high contrast tasks. d' increased with increasing dose level or lesion diameter and decreasing size. For high-contrast tasks, d' was higher at 40-80 keV and lower at high VMIs. For the low-contrast task, d' was higher for VMI at 70-90 keV and lower at 40-60 keV. CONCLUSIONS: Task-based image quality differed among VMI-energy and LBI dependent on the contrast task, dose level, phantom size, and lesion diameter. Image quality could be optimized by tailoring VMI-energy to the contrast task. Considering the clinical relevance of iodine, VMIs at 50-60 keV could be proposed as an alternative to LBI.

Sources of Variability in Shear Wave Speed and Dispersion Quantification with Ultrasound Elastography: A Phantom Study.

There is a growing interest in quantifying shear-wave dispersion (SWD) with ultrasound shear-wave elastography (SWE). Recent studies suggest that SWD complements shear-wave speed (SWS) in diffuse liver disease diagnosis. To accurately interpret these metrics in clinical practice, we analyzed the impact of operator-dependent acquisition parameters on SWD and SWS measurements. Considered parameters were the acquisition depth, lateral position and size of the region of interest (ROI), as well as the size of the SWE acquisition box. Measurements were performed using the Canon Aplio i800 system (Canon Medical Systems, Otawara, Tochigi, Japan) and four homogeneous elasticity phantoms with certified stiffness values ranging from 3.7 to 44 kPa. In general, SWD exhibited two to three times greater variability than SWS. The acquisition depth was the main variance-contributing factor for both SWS and SWD, which decayed significantly with depth. The lateral ROI position contributed as much as the acquisition depth to the total variance in SWD. Locations close to the initial shear-wave excitation pulse were more robust to biases because of inaccurate probe-phantom coupling. The size of the ROI and acquisition box did not introduce significant variations. These results suggest that future guidelines on multiparametric elastography should account for the depth- and lateral-dependent variability of measurements.

Virtual Monoenergetic Images of Dual-Energy CT-Impact on Repeatability, Reproducibility, and Classification in Radiomics.

The purpose of this study was to (i) evaluate the test-retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance-correlation-coefficient (CCC) and dynamic range (DR) ≥0.9. Test-retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 keV and 15 mGy to 86% for DSDE at 190 keV and 15 mGy), while reproducibility varied substantially across different VMI energies and DECTs (percentage of reproducible features ranging from 32.8% for SFDE at 5 mGy comparing 40 with 190 keV to 99.2% for DSDE at 15 mGy comparing 40 with 50 keV). No major differences were observed between the two radiation doses (<10%) in all pair-wise comparisons. In vivo, machine learning classification using penalized regression and random forests resulted in the best discrimination of hemangiomas and metastases at low-energy VMI (40 keV), and for cysts at high-energy VMI (120 keV). Feature selection based on feature repeatability did not improve classification performance. Our results demonstrate the high repeatability of radiomics features when keeping scan and reconstruction conditions constant. Reproducibility diminished when using different VMI energies or DECT approaches. The choice of optimal VMI energy improved lesion classification in vivo and should hence be adapted to the specific task.

Radiomics in medical imaging-"how-to" guide and critical reflection.

Radiomics is a quantitative approach to medical imaging, which aims at enhancing the existing data available to clinicians by means of advanced mathematical analysis. Through mathematical extraction of the spatial distribution of signal intensities and pixel interrelationships, radiomics quantifies textural information by using analysis methods from the field of artificial intelligence. Various studies from different fields in imaging have been published so far, highlighting the potential of radiomics to enhance clinical decision-making. However, the field faces several important challenges, which are mainly caused by the various technical factors influencing the extracted radiomic features.The aim of the present review is twofold: first, we present the typical workflow of a radiomics analysis and deliver a practical "how-to" guide for a typical radiomics analysis. Second, we discuss the current limitations of radiomics, suggest potential improvements, and summarize relevant literature on the subject.