A novel phantom for measuring the 10% and 50% values of the modulation transfer function (MTF) for computed tomography scanners (CT) was investigated. The phantom was constructed by drilling rows of holes of different sizes and frequencies into a small block of polymethyl methacrylate (PMMA). The MTF at a given frequency was determined from the ratio of the range of Hounsfield units within the rows of holes at different frequencies, and the difference in Hounsfield units between air and PMMA. A MTF curve was plotted from measurements at different frequencies and the 10% and 50% MTF values were obtained from a cubic spline interpolation. The MTF results obtained with the drilled hole phantom method were compared to a conventional method - using a thin wire and Spice-CT ImageJ Plugin- and with identical acquisition and reconstruction parameters. The drilled hole phantom measured the 50% MTF with reasonable accuracy but underestimated the 10% MTF by 8.2% on average. MTF measurements were reproducible for repeated image acquisitions and with different users analysing the images, and the phantom was able to accurately measure the change in MTF when measured on images using different reconstruction kernels. The tool may find application as a cheap, easy to use method for routine QC testing of CT scanners.

Currently, the relationship between axial rotation of the vertebrae and bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) remains controversial. The aim of this study is to quantitatively assess the effect of vertebral rotation on volumetric bone mineral density (v-BMD) and areal bone mineral density (a-BMD), further to propose the corrected strategies. To achieve this, a phantom, which was rotated from 0° to 25° in 5° increments, was utilized. Bone mineral content (BMC), a-BMD, v-BMD, and projected area (p-AREA) were measured. The Kruskal-Wallis non-parametric test or one-way ANOVA was used to examine the differences in variables between the different groups. The Pearson and Spearman correlation was used to test the relationships between quantitative parameters and rotated angles. Linear regression analysis was used to evaluate the relationship between angles and quantitative parameters. The findings indicate that, as the angle increased, a-BMD and v-BMD decreased (P < 0.001) , and the p-AREA increased (P < 0.001), but the BMC stays constant. The rotated angle was negative correlated (r = - 0.925, P < 0.001) with a-BMD and v-BMD (r = - 0.880, P < 0.001), positive (r = 0.930, P =  < 0.001) correlated with p-AREA. The linear regression analysis showed that a-BMD = 0.808-0.01 × Angle and v-BMD = 151.808-1.588 × Angle. This study showed that, axial rotation might lead to a lower measured for a-BMD and v-BMD, it should be modified. This gives clinicians some insights into how to deal with osteoporosis in scoliosis patients. It\'s essential for clinicians to incorporate these findings into their diagnostic processes to prevent potential misdiagnosis and over-treatment of osteoporosis.

Recreating cerebral tissue using a tissue-mimicking phantom is valuable because it provides a tool for studying physiological and biological processes related to tissues without the necessity of performing the study directly in the tissue or even in a patient. The reproduction of the optical properties allows investigation in areas such as imaging, optics, and ultrasound, among others. This paper presents a methodology for manufacturing agarose-based phantoms that mimic the optical characteristics of brain tissue using scattering and absorbing agents and proposes combinations of these agents to recreate the healthy brain tissue optical coefficients within the wavelength range of 350 to 500 nm. The results of the characterization of the manufactured phantoms propose ideal combinations of the used materials for their use in controlled environment experiments in the UV range, following a cost-effective methodology.

BACKGROUND: Unilateral condylar hyperplasia (UCH) of the mandible is a rare condition characterized by asymmetric growth of the mandibular condyles. Bone scintigraphy with SPECT(/CT) is commonly used to diagnose UCH and guide treatment. Still, varying results have been reported using the traditional threshold of 55%:45% in relative tracer uptake. While absolute quantification of uptake on SPECT/CT could improve results, optimal correction and reconstruction settings are currently unknown.
METHODS: Three anthropomorphic phantoms representing UCH were developed from patient CT volumes and produced using 3D printing technology. Fillable spherical inserts of different sizes (Ø: 8-15 mm) were placed in the condylar positions representing symmetrical and asymmetrical distributions. Recovery coefficients were determined for SPECT/CT using various reconstruction corrections, including attenuation and scatter correction (ACSC), resolution modeling (RM), and partial volume correction (PVC) using phantom measurements. Uptake ratios between condyles and condyle to clivus were evaluated. Finally, the impact of these correction techniques on absolute activity and diagnostic accuracy was assessed in a retrospective patient cohort for the diagnostic threshold of 55%:45%.
RESULTS: The activity was only partially recovered in all spherical inserts (range: 22.5-64.9%). However, RM improved relative recovery by 20.2-62.3% compared to ACSC. In the symmetric phantoms, the 95% confidence interval (CI) of condyle ratios included the diagnostic threshold (57.6%:42.4%) for UCH when using ACSC potentially leading to false positives, but not for ACSCRM datasets. Partial volume corrections coefficients from the NEMA IQ phantom was positionally dependent, with improvements seen performing PVC using coefficients derived from anthropomorphic phantoms. Retrospective application in a patient cohort showed only a weak linear correlation (R²: 0.25-0.67) and large limits of agreement (9.6-12.5%) between different reconstructions. Up to 44% of patients were reclassified using the 55%:45% threshold. Using clinical outcome data, ACSCRM had highest sensitivity (91%; 95% CI 59-100%) and specificity (66%; 95% CI 47-81%), significantly improving specificity (P = 0.038).
CONCLUSIONS: Anthropomorphic phantoms were shown to be essential in determining optimal settings for acquisition, reconstruction, and analysis. SPECT/CT reconstructions with attenuation and scatter correction and resolution modeling are recommended and could improve specificity when using the 55%:45% threshold to assess condylar growth.

METHODS: A prospective study.
OBJECTIVE: To assess fat-water-like tissue changes on the 1st sacral vertebra using novel magnetic resonance imaging (MRI) phantombased F- and W-scores and evaluate their diagnostic performances in osteoporosis detection.
BACKGROUND: Using an uncommonly advanced MRI technique, previous studies have found that fat-water changes were consistent with osteoporosis. The role of routine MRI sequences can be extended in this regard. The S1 vertebra is considered a crucial anatomical site in spine surgeries because it seldom suffers from fractures. Thus, S1 could indicate osteoporotic fat-water changes.
METHODS: Forty-two female volunteers (aged 62.3±6.3 years) underwent spine examination with both MRI (including a phantom) and dual-energy X-ray absorptiometry (DXA) following ethical approval. MRI phantom-based F- and W-scoreS1 were defined by normalizing S1 vertebral signal intensities (SIs) by coconut oil and water SIs of the phantom on T1- and T2-weighted imaging, respectively. Using receiver operating characteristic analysis, the diagnostic performances of the new scores for evaluating osteoporosis and vertebral fractures were investigated against standard areal bone mineral density measured with DXA (DXA-aBMD).
RESULTS: The F-scoreS1 and W-scoreS1 were greater (4.11 and 2.43, respectively) in patients with osteoporosis than those without osteoporosis (3.25 and 1.92, respectively) and achieved areas under the curve (AUCs) of 0.82 and 0.76 (p<0.05), respectively, for osteoporosis detection. Similarly, the mean F-scoreS1 and W-scoreS1 were higher (4.11 and 2.63, respectively) in patients with vertebral fractures than in those without fractures (3.30 and 1.82, respectively) and had greater AUCs (0.90 for W-scoreS1 and 0.74 for F-scoreS1) than DXA-aBMD (AUC, 0.26; p<0.03). In addition, the F- and W-scoreS1 demonstrated a strong correlation (r=0.65, p<0.001).
CONCLUSIONS: The new S1 vertebral-based MRI scores were developed to detect osteoporotic changes and demonstrated improvements over DXA-aBMD in differentiating patients with vertebral fractures.

UNASSIGNED: Radiomics analysis extracts quantitative data (features) from medical images. These features could potentially reflect biological characteristics and act as imaging biomarkers within precision medicine. However, there is a lack of cross-comparison and validation of radiomics outputs which is paramount for clinical implementation. In this study, we compared radiomics outputs across two computed tomography (CT)-based preclinical scanners.
UNASSIGNED: Cone beam CT (CBCT) and µCT scans were acquired using different preclinical CT imaging platforms. The reproducibility of radiomics features on each scanner was assessed using a phantom across imaging energies (40 & 60 kVp) and segmentation volumes (44-238 mm3). Retrospective mouse scans were used to compare feature reliability across varying tissue densities (lung, heart, bone), scanners and after voxel size harmonisation. Reliable features had an intraclass correlation coefficient (ICC) > 0.8.
UNASSIGNED: First order and GLCM features were the most reliable on both scanners across different volumes. There was an inverse relationship between tissue density and feature reliability, with the highest number of features in lung (CBCT=580, µCT=734) and lowest in bone (CBCT=110, µCT=560). Comparable features for lung and heart tissues increased when voxel sizes were harmonised. We have identified tissue-specific preclinical radiomics signatures in mice for the lung (133), heart (35), and bone (15).
UNASSIGNED: Preclinical CBCT and µCT scans can be used for radiomics analysis to support the development of meaningful radiomics signatures. This study demonstrates the importance of standardisation and emphasises the need for multi-centre studies.

UNASSIGNED: Deep learning features (DLFs) derived from radiomics features (RFs) fused with deep learning have shown potential in enhancing diagnostic capability. However, the limited repeatability and reproducibility of DLFs across multiple centers represents a challenge in the clinically validation of these features. This study thus aimed to evaluate the repeatability and reproducibility of DLFs and their potential efficiency in differentiating subtypes of lung adenocarcinoma less than 10 mm in size and manifesting as ground-glass nodules (GGNs).
UNASSIGNED: A chest phantom with nodules was scanned repeatedly using different thin-slice computed tomography (TSCT) scanners with varying acquisition and reconstruction parameters. The robustness of the DLFs was measured using the concordance correlation coefficient (CCC) and intraclass correlation coefficient (ICC). A deep learning approach was used for visualizing the DLFs. To assess the clinical effectiveness and generalizability of the stable and informative DLFs, three hospitals were used to source 275 patients, in whom 405 nodules were pathologically differentially diagnosed as GGN lung adenocarcinoma less than 10 mm in size and were retrospectively reviewed for clinical validation.
UNASSIGNED: A total of 64 DLFs were analyzed, which revealed that the variables of slice thickness and slice interval (ICC, 0.79±0.18) and reconstruction kernel (ICC, 0.82±0.07) were significantly associated with the robustness of DLFs. Feature visualization showed that the DLFs were mainly focused around the nodule areas. In the external validation, a subset of 28 robust DLFs identified as stable under all sources of variability achieved the highest area under curve [AUC =0.65, 95% confidence interval (CI): 0.53-0.76] compared to other DLF models and the radiomics model.
UNASSIGNED: Although different manufacturers and scanning schemes affect the reproducibility of DLFs, certain DLFs demonstrated excellent stability and effectively improved diagnostic the efficacy for identifying subtypes of lung adenocarcinoma. Therefore, as the first step, screening stable DLFs in multicenter DLFs research may improve diagnostic efficacy and promote the application of these features.

UNASSIGNED: Photoacoustic imaging (PAI) is an emerging technology that holds high promise in a wide range of clinical applications, but standardized methods for system testing are lacking, impeding objective device performance evaluation, calibration, and inter-device comparisons. To address this shortfall, this tutorial offers readers structured guidance in developing tissue-mimicking phantoms for photoacoustic applications with potential extensions to certain acoustic and optical imaging applications.
UNASSIGNED: The tutorial review aims to summarize recommendations on phantom development for PAI applications to harmonize efforts in standardization and system calibration in the field.
UNASSIGNED: The International Photoacoustic Standardization Consortium has conducted a consensus exercise to define recommendations for the development of tissue-mimicking phantoms in PAI.
UNASSIGNED: Recommendations on phantom development are summarized in seven defined steps, expanding from (1) general understanding of the imaging modality, definition of (2) relevant terminology and parameters and (3) phantom purposes, recommendation of (4) basic material properties, (5) material characterization methods, and (6) phantom design to (7) reproducibility efforts.
UNASSIGNED: The tutorial offers a comprehensive framework for the development of tissue-mimicking phantoms in PAI to streamline efforts in system testing and push forward the advancement and translation of the technology.

Impaired retinal blood flow is associated with ocular diseases such as glaucoma, macular degeneration, and diabetic retinopathy. Among several ocular imaging techniques developed to measure retinal blood flow both invasively and non-invasively, adaptive optics (AO)-enabled scanning laser ophthalmoscopy (AO-SLO) resolves individual red blood cells and provides a high resolution with which to measure flow across retinal microvasculature. However, cross-validation of flow measures remains a challenge owing to instrument and patient-specific variability in each imaging technique. Hence, there is a critical need for a well-controlled clinical flow phantom for standardization and to establish blood-flow measures as clinical biomarkers for early diagnosis. Here, we present the design and validation of a simple, compact, portable, linear flow phantom based on a direct current motor and a conveyor-belt system that provides linear velocity tuning within the retinal microvasculature range (0.5-7 mm/s). The model was evaluated using a sensitive AO-SLO line-scan technique, which showed a <6% standard deviation from the true velocity. Further, a clinical SLO instrument showed a linear correlation with the phantom\'s true velocity (r2 > 0.997). This model has great potential to calibrate, evaluate, and improve the accuracy of existing clinical imaging systems for retinal blood flow and aid in the diagnosis of ocular diseases with abnormal blood flow.

The urinary volume and residual urine volume are pieces of information that can provide relevant clinical data for dogs and cats, especially those hospitalized. Thus, the present study aimed to evaluate mathematical formulas described in human and veterinary literature to estimate urinary volume in dogs and experimental models. For this purpose, nine male dog cadavers and twelve experimental models were used to evaluate residual volume, small, medium, and large, using three different formulas. Data were obtained by three different examiners: two ultrasonographers and one nonultrasonographer. Each examiner recorded three longitudinal and transverse images, obtaining measurements of width, length, and height at each proposed volume. The measurements were then averaged, and the result was added to the formulas, thus estimating urinary volume. All three formulas achieved higher accuracy in estimating smaller volumes, with a gradual decrease as urinary volume increased. The error of all formulas was less than 10%, even when compared with evaluations in experimental models and dogs. There was variation in estimation between ultrasonographers and nonultrasonographer examiners; however, this variation was low, allowing for the assertion that both can apply the technique. Thus, it is concluded that estimating urinary bladder volume using mathematical formulas and 2D ultrasound is accurate and, therefore, an alternative and viable option for evaluating the urinary tract.