Large Region Of Interest Research Articles

Quantitative ultrasound for steatosis assessment using Hepatoscope®: Confounding technical factors

Quantitative ultrasound (QUS) is a well-suited modality to address large-scale screening and monitoring of liver steatosis as it is low-cost, non-invasive, and point-of-care. However, technical and biological confounders lead to difficulties in establishing universal cutoff values for diagnosis. Hepatoscope® remedies this issue as it integrates a unique QUS measurement technique enabling the simultaneous measurements of the backscattering coefficient, the attenuation coefficient and the speed of sound. Such measurements are performed in a large two-dimensional region of interest (ROI) and in a free breathing regime such that a relatively large portion of the liver is sampled. We studied the influence of the size of the ROI, its depth and the number of measurements on the QUS parameters with Hepatoscope® both in vitro on four calibrated phantoms and clinically on 60 participants referred to a hepatology consultation for chronic liver disease. We demonstrated that using large ROIs consistently improves the system reliability and the clinical applicability. We did not observe any systematic effect related to the depth of the ROI. We also showed that averaging consecutive measurements leads to better system reliability and better clinical applicability.

High-quality lipid suppression and B0 shimming for human brain 1H MRSI

Magnetic Resonance Spectroscopic Imaging (MRSI) is a powerful technique that can map the metabolic profile in the brain non-invasively. Extracranial lipid contamination and insufficient B0 homogeneity however hampers robustness, and as a result has hindered widespread use of MRSI in clinical and research settings. Over the last six years we have developed highly effective extracranial lipid suppression methods with a second order gradient insert (ECLIPSE) utilizing inner volume selection (IVS) and outer volume suppression (OVS) methods. While ECLIPSE provides > 100-fold in lipid suppression with modest radio frequency (RF) power requirements and immunity to B1+ field variations, axial coverage is reduced for non-elliptical head shapes. In this work we detail the design, construction, and utility of MC-ECLIPSE, a pulsed second order gradient coil with Z2 and X2Y2 fields, combined with a 54-channel multi-coil (MC) array. The MC-ECLIPSE platform allows arbitrary region of interest (ROI) shaped OVS for full-axial slice coverage, in addition to MC-based B0 field shimming, for robust human brain proton MRSI.In vivo experiments demonstrate that MC-ECLIPSE allows axial brain coverage of 92–95 % is achieved following arbitrary ROI shaped OVS for various head shapes. The standard deviation (SD) of the residual B0 field following SH2 and MC shimming were 25 ± 9 Hz and 18 ± 8 Hz over a 5 cm slab, and 18 ± 5 Hz and 14 ± 6 Hz over a 1.5 cm slab, respectively. These results demonstrate that B0 magnetic field shimming with the MC array supersedes second order harmonic capabilities available on standard MRI systems for both restricted and large ROIs. Furthermore, MC based B0 shimming provides comparable shimming performance to an unrestricted SH5 shim set for both restricted, and 5-cm slab shim challenges.Phantom experiments demonstrate the high level of localization performance achievable with MC-ECLIPSE, with ROI edge chemical shift displacements ranging from 1–3 mm with a median value of 2 mm, and transition width metrics ranging from 1–2.5 mm throughout the ROI edge. Furthermore, MC based B0 shimming is comparable to performance following a full set of unrestricted spherical harmonic fields up to order 5. Short echo time MRSI and GABA-edited MRSI acquisitions in the human brain following MC-shimming and arbitrary ROI shaping demonstrate full-axial slice coverage and extracranial lipid artifact free spectra. MC-ECLIPSE allows full-axial coverage and robust MRSI acquisitions, while allowing interrogation of cortical tissue proximal to the skull, which has significant value in a wide range of neurological and psychiatric conditions.

Optimizing prostate cancer detection in transition zone: an analysis of apparent diffusion coefficient values in prostate magnetic resonance imaging evaluation with Prostate Imaging Reporting and Data System (PI-RADS) assessment.

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for the early detection of clinically significant prostate cancer (csPCa). However, the achievement of accurate detection rates, particularly for transition zone (TZ) lesions, remains challenging. We investigated the relationship between apparent diffusion coefficient (ADC) values in Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions and csPCa within the TZ. We retrospectively evaluated TZ lesions in patients who underwent 3.0 Tesla MRI followed by MRI-targeted/transrectal ultrasound fusion biopsies (MRI-FBx). Fusion biopsies were performed for potentially cancerous lesions, defined as lesions with PI-RADS scores 3-5. We analyzed 196 lesions for which fusion biopsies were performed. The overall prostate cancer (PCa) detection rate was 53.6% (105/196); csPCa constituted 33.7% (66/196) of cases. The minimum ADC value was significantly lower for patients with csPCa (484.9±112.3 µm2/s) than for patients with benign histology or non-csPCa (P<0.001). Older age, higher initial prostate-specific antigen level, larger region of interest, and minimum and mean ADC values were associated with the presence of csPCa. Multivariate analysis indicated that only the minimum ADC value was an independent predictor of csPCa. Using a cutoff minimum ADC value <561 µm2/s to detect csPCa in TZ lesions increased the detection rate to 57.4% (54/94). The minimum ADC value provides substantial additional information regarding the presence of csPCa in the TZ, potentially improving the detection rates for lesions rated as PI-RADS 3-5 and informing the need for follow-up biopsies in areas that are initially cancer-free.

Development of an initial training and evaluation programme for manual lower limb muscle MRI segmentation

BackgroundMagnetic resonance imaging (MRI) quantification of intramuscular fat accumulation is a responsive biomarker in neuromuscular diseases. Despite emergence of automated methods, manual muscle segmentation remains an essential foundation. We aimed to develop a training programme for new observers to demonstrate competence in lower limb muscle segmentation and establish reliability benchmarks for future human observers and machine learning segmentation packages.MethodsThe learning phase of the training programme comprised a training manual, direct instruction, and eight lower limb MRI scans with reference standard large and small regions of interest (ROIs). The assessment phase used test–retest scans from two patients and two healthy controls. Interscan and interobserver reliability metrics were calculated to identify underperforming outliers and to determine competency benchmarks.ResultsThree experienced observers undertook the assessment phase, whilst eight new observers completed the full training programme. Two of the new observers were identified as underperforming outliers, relating to variation in size or consistency of segmentations; six had interscan and interobserver reliability equivalent to those of experienced observers. The calculated benchmark for the Sørensen-Dice similarity coefficient between observers was greater than 0.87 and 0.92 for individual thigh and calf muscles, respectively. Interscan and interobserver reliability were significantly higher for large than small ROIs (all p < 0.001).ConclusionsWe developed, implemented, and analysed the first formal training programme for manual lower limb muscle segmentation. Large ROI showed superior reliability to small ROI for fat fraction assessment.Relevance statementObservers competent in lower limb muscle segmentation are critical to application of quantitative muscle MRI biomarkers in neuromuscular diseases. This study has established competency benchmarks for future human observers or automated segmentation methods.Key points• Observers competent in muscle segmentation are critical for quantitative muscle MRI biomarkers.• A training programme for muscle segmentation was undertaken by eight new observers.• We established competency benchmarks for future human observers or automated segmentation methods.Graphical

23Na MRI: inter-reader reproducibility of normal fibroglandular sodium concentration measurements at 3 T

BackgroundTo study the reproducibility of 23Na magnetic resonance imaging (MRI) measurements from breast tissue in healthy volunteers.MethodsUsing a dual-tuned bilateral 23Na/1H breast coil at 3-T MRI, high-resolution 23Na MRI three-dimensional cones sequences were used to quantify total sodium concentration (TSC) and fluid-attenuated sodium concentration (FASC). B1-corrected TSC and FASC maps were created. Two readers manually measured mean, minimum and maximum TSC and mean FASC values using two sampling methods: large regions of interest (LROIs) and small regions of interest (SROIs) encompassing fibroglandular tissue (FGT) and the highest signal area at the level of the nipple, respectively. The reproducibility of the measurements and correlations between density, age and FGT apparent diffusion coefficient (ADC) values were evaluatedss.ResultsNine healthy volunteers were included. The inter-reader reproducibility of TSC and FASC using SROIs and LROIs was excellent (intraclass coefficient range 0.945−0.979, p < 0.001), except for the minimum TSC LROI measurements (p = 0.369). The mean/minimum LROI TSC and mean LROI FASC values were lower than the respective SROI values (p < 0.001); the maximum LROI TSC values were higher than the SROI TSC values (p = 0.009). TSC correlated inversely with age but not with FGT ADCs. The mean and maximum FGT TSC and FASC values were higher in dense breasts in comparison to non-dense breasts (p < 0.020).ConclusionsThe chosen sampling method and the selected descriptive value affect the measured TSC and FASC values, although the inter-reader reproducibility of the measurements is in general excellent.Relevance statement23Na MRI at 3 T allows the quantification of TSC and FASC sodium concentrations. The sodium measurements should be obtained consistently in a uniform manner.Key points• 23Na MRI allows the quantification of total and fluid-attenuated sodium concentrations (TSC/FASC).• Sampling method (large/small region of interest) affects the TSC and FASC values.• Dense breasts have higher TSC and FASC values than non-dense breasts.• The inter-reader reproducibility of TSC and FASC measurements was, in general, excellent.• The results suggest the importance of stratifying the sodium measurements protocol.Graphical

Modeling soil organic carbon based on field soil-texture measurements

There are many studies about soil organic carbon (SOC) around the world but, in extensive territories, it is more difficult to obtain data due to the number of variables involved in the models and their high cost. In large regions with poor infrastructure, low-cost SOC models are needed. With this in mind, our objective was to estimate the SOC using a simple model based on soil textural data. The work was focused on savanna soil and validated the model in the Brazilian Savanna. Two models were constructed, one for topsoil (0–0.3 m) and other for subsoil (0.3–1.0 m). The SOC models can be carried out in a textural triangle together with SOC values. The results showed that subsoil models were more accurate than topsoil models, but both had good performance. The models give support to SOC-related preliminary research in gross and fast estimates, requiring only reduced financial contribution to calculate SOC in a large region of interest.

Quantitative Comparison of Liver Volume, Proton Density Fat Fraction, and Time Burden between Automatic Whole Liver Segmentation and Manual Sampling MRI Strategies for Diagnosing Metabolic Dysfunction-associated Steatotic Liver Disease in Obese Patients.

The performance of automatic liver segmentation and manual sampling MRI strategies needs be compared to determine interchangeability. To compare automatic liver segmentation and manual sampling strategies (manual whole liver segmentation and standardized manual region of interest) for performance in quantifying liver volume and MRI-proton density fat fraction (MRI-PDFF), identifying steatosis grade, and time burden. Fifty patients with obesity who underwent liver biopsy and MRI between December 2017 and November 2018 were included. Sampling strategies included automatic and manual whole liver segmentation and 4 and 9 large regions of interest. Intraclass correlation coefficient (ICC), Bland-Altman, linear regression, receiver operating characteristic curve, and Pearson correlation analyses were performed. Automatic whole liver segmentation liver volume and manual whole liver segmentation liver volume showed excellent agreement (ICC=0.97), high correlation (R2=0.96), and low bias (3.7%, 95% limits of agreement, -4.8%, 12.2%) in liver volume. There was the best agreement (ICC=0.99), highest correlation (R2=1.00), and minimum bias (0.84%, 95% limits of agreement, -0.20%, 1.89%) between automated whole liver segmentation MRI-PDFF and manual whole liver segmentation MRI-PDFF. There was no difference of each paired comparison of receiver operating characteristic curves for detecting steatosis (P=0.07-1.00). The minimum time burden for automatic whole liver segmentation was 0.32 s (0.32-0.33 s). Automatic measurement has similar effects to manual measurement in quantifying liver volume, MRI-PDFF, and detecting steatosis. Time burden of automatic whole liver segmentation is minimal among all sampling strategies. Manual measurement can be replaced by automatic measurement to improve quantitative efficiency.

Image reconstruction from truncated fan-beam projections along a circular trajectory using the virtual fan-beam method

Objective. In this paper, we investigate how the virtual fan-beam (VFB) method can be used to perform mathematically correct 2D reconstruction in a region-of-interest (ROI), using truncated fan-beam projections acquired on a circular scan, for truncation that only occurs on one side of the object. Approach. We start by choosing a virtual fan-beam trajectory and specifying how to obtain the corresponding virtual projections. Then, three VFB formulas are obtained by applying known super-short-scan (SSS) formulas to this virtual trajectory. Two of them perform the backprojection in a virtual parallel geometry and the third in the virtual fan-beam geometry. Next, we develop two VFB formulas that perform the backprojection step in the fan-beam acquisition geometry. Main results. We present five VFB reconstruction formulas for this truncation setting. To our knowledge, the two VFB formulas performing the backprojection in the fan-beam acquisition geometry are new. Moreover, the five VFB formulas presented here obtain accurate reconstruction in a larger ROI than what has been previously reported in the literature in the same setting. A complete mathematical derivation of these five VFB formulas is given, and their implementation is described step by step. Numerical simulations, using the Forbild head and thorax phantoms, demonstrate the efficacy of these formulas. A spatial resolution analysis and a variance study indicate minor differences between these five VFB formulas. Significance. This work shows that many different VFB formulas can be applied to perform mathematically correct 2D reconstruction in a ROI, in case of truncated fan-beam projections acquired on a circular scan. Moreover, the two new VFB formulas, with backprojection in the acquisition geometry, may open the path for an extension of the VFB method to 3D reconstruction from transversely truncated cone-beam projection acquired on a circular scan.

Clinical Efficacy of Distal Tibial Hounsfield Unit for the Diagnosis of Osteoporosis in Ankle Fractures

Category: Trauma; Ankle Introduction/Purpose: Ankle fracture is one of the most common fractures over the age of 50 years. However, there is a lack of research on osteoporotic ankle fractures compared to other osteoporotic fractures. Recently, some studies have been published that Hounsfield Unit(HU) measuring bone attenuation from CT scan is used for assessing the bone density of not only the hip and spine but also extremities such as the distal radius and proximal humerus. This study aims to evaluate the correlation between HU of distal tibia without ankle fracture and DEXA-BMD and determine the cut-off value of HU for osteoporosis diagnosis. Additionally, this study determines whether the HU of the distal tibia obtained from the preoperative CT scan of ankle fractures helps evaluate patients with osteoporotic ankle fractures. Methods: From June 2016 to August 2020, We retrospectively studied foot and ankle traumatic patients who are postmenopausal women or men over 50 years. They conducted a foot or ankle CT scan containing the axial images of the distal tibia and DEXA- BMD within three months. Patients with open fractures with severe displacement or arthritic change were excluded. The mean HU was obtained from two sequential axial images of the distal tibial metaphysis's largest region of interest (ROI), more than 1cm proximal to the tibial plafond. We divided the patients into Group A without ankle fractures and Group B with distal tibia or fibula fractures in the ankle. The correlation analysis was done between the distal tibial HU and DEXA-BMD. We obtained the cut-off value of the distal tibial HU for osteoporosis using receiver operating characteristic(ROC) curves and compared the results between the two groups. Results: Group A was 38 cases(mean age 69.9), and Group B was 59 (mean age 71.0). There were no statistical differences in patients' characteristics, the mean distal tibial HU, bone density, T-score, and rate of osteoporosis in BMD. All HU values in both groups showed excellent inter- and intra-observer reliability(All intraclass coefficients&gt;0.9). Both groups had significant correlations between the distal tibial HU and DEXA-BMD, especially in the femur neck and L3 spine(r=0.706, 0.622, p&lt; 0.001 in Group A, r=0.625,0.499, p&lt; 0.001 in Group B). The cut-off value for osteoporosis of the distal tibial HU was 153.15(sensitivity 73.9%, specificity 86.7%; area under the curve(AUC) 0.841, 95% CI 0.716-0.965, p&lt; 0.001) in Group A. The cut-off value of Group B was 167.35(sensitivity 66.7%, specificity 75.9%; AUC 0.737, 95% CI 0.610-0.865, p=0.002). Conclusion: The distal tibial HU values on the axial images on the CT showed a significant correlation with the central bone of DEXA-BMD. The distal tibial HU value showed excellent reliability with or without fracture. HU value can be easily obtained using a preoperative ankle CT scan without additional cost &amp; radiation exposure to patients with ankle fractures. Therefore, it can help treat osteoporotic ankle fractures by screening for osteoporosis and deciding the fixation method of surgery.

Comb Detection for Measuring Shear Wave Propagation.

Plane wave compounding (PWC) is widely used to measure the propagation of shear waves. Implementing PWC on most commercial ultrasound scanners is challenging because all channel (>128) data must be processed or transferred to the host computing unit in real time. Comb detection transmits multiple focused beams simultaneously and results in a reduced number of receive lines to be processed in parallel. These comb beams are scanned laterally to acquire receive lines at different lateral positions in order to obtain data over a large region of interest (ROI). One of the potential issues with using multiple simultaneously transmitted beams is the issue of crosstalk between the beams. Crosstalk is analyzed through simulated beam patterns, simulated B-mode images, and motion data from shear wave elastography (SWE) experiments. Using a Hamming window on transmit and receive can suppress crosstalk to 1.2% root-mean-square error (RMSE, normalized RMSE to the peak magnitude of the reference signal) for shear wave motion signals. Four comb beams with three laterally scanned locations cover almost the entire field of view (FOV) and achieve the same frame rate as PWC with three angles. Phantom and in vivo studies demonstrate comparable motion data of comb detection to PWC in terms of motion signal quality and measured phase velocity. In addition, comb detection provides motion with lower noise and stronger signals than PWC, which is believed to be due to the advantages of transmitting focused beams rather than plane waves (PWs).

Comparison of absorbed doses and organ doses measured with thermoluminescent dosimeters and Gafchromic film for cone beam computed tomography examination of the posterior mandibular region in a head phantom

We aimed to map the correlation between thermoluminescent dosimeters (TLDs) and Gafchromic film for measuring absorbed doses and to compare minimum, maximum, and mean absorbed doses over larger regions of interest and at various craniofacial organs and tissues during cone beam computed tomography (CBCT) exposure of the mandibular third molar region. We positioned TLDs at 75 measurement points in a head phantom. Gafchromic film was cut to the same shape as the 5 levels of the phantom and was placed on top of the TLDs. Both dosimetry methods thus included the surface of each level simultaneously. CBCT scans were made using a 5×5 cm field of view and a rotation angle of 200°. Measurements included absorbed dose distributions, doses at all 75 points, and minimum, maximum, and mean doses within organs and tissues. The correlation of point-dose measurements at all TLD sites with doses measured on film was strong (R2=0.9687), with greatest correlation at lower doses (<2 mGy). Large deviations between TLD and film measurements of minimum and maximum doses and absorbed doses to the organs occurred at all 5 levels. TLD positioning failed to cover several organ sites; for these, only absorbed dose measurements from the film were available. TLDs were unable to sample dose distributions and gradients accurately. The characteristics of Gafchromic LD-V1 film make it a favorable alternative in dental CBCT dosimetry.

Greater increases in intratumoral apparent diffusion coefficients after chemoradiotherapy predict better overall survival of patients with cervical cancer.

To evaluate whether 1) the intratumoral apparent diffusion coefficients (ADCs) change during cervical cancer treatment and 2) the pretreatment ADC values or their change after treatment predict the treatment outcome or overall survival of patients with cervical cancer. We retrospectively enrolled 52 patients with inoperable cervical cancer treated with chemoradiotherapy, who had undergone diffusion weighted MRI before treatment and post external beam radiotherapy (EBRT) and concurrent chemotherapy. A subgroup of patients (n = 28) underwent altogether six consecutive diffusion weighted MRIs; 1) pretreatment, 2) post-EBRT and concurrent chemotherapy; 3-5) during image-guided brachytherapy (IGBT) and 6) after completing the whole treatment course. To assess interobserver and intertechnique reproducibility two observers independently measured the ADCs by drawing freehand a large region of interest (L-ROI) covering the whole tumor and three small ROIs (S-ROIs) in areas with most restricted diffusion. Reproducibility was equally good for L-ROIs and S-ROIs. The pretreatment ADCs were higher in L-ROIs (883 mm2/s) than in S-ROIs (687 mm2/s, P < 0.001). The ADCs increased significantly between the pretreatment and post-EBRT scans (L-ROI: P < 0.001; S-ROI: P = 0.001). The ADCs remained significantly higher than pretreatment values during the whole IGBT. Using S-ROIs, greater increases in ADCs between pretreatment and post-EBRT MRI predicted better overall survival (P = 0.018). ADC values significantly increase during cervical cancer treatment. Greater increases in ADC values between pretreatment and post-EBRT predicted better overall survival using S-ROIs. Standardized methods for timing and delineation of ADC measurements are advocated in future studies.

Neoadjuvant chemotherapy induces an elevation of tumour apparent diffusion coefficient values in patients with ovarian cancer

ObjectivesMultiparametric magnetic resonance imaging (mMRI) is the modality of choice in the imaging of ovarian cancer (OC). We aimed to investigate the feasibility of different types of regions of interest (ROIs) in the measurement of apparent diffusion coefficient (ADC) values of diffusion-weighted imaging in OC patients treated with neoadjuvant chemotherapy (NACT).MethodsWe retrospectively enrolled 23 consecutive patients with advanced OC who had undergone NACT and mMRI. Seventeen of them had been imaged before and after NACT. Two observers independently measured the ADC values in both ovaries and in the metastatic mass by drawing on a single slice of (1) freehand large ROIs (L-ROIs) covering the solid parts of the whole tumour and (2) three small round ROIs (S-ROIs). The side of the primary ovarian tumour was defined. We evaluated the interobserver reproducibility and statistical significance of the change in tumoural pre- and post-NACT ADC values. Each patient’s disease was defined as platinum-sensitive, semi-sensitive, or resistant. The patients were deemed either responders or non-responders.ResultsThe interobserver reproducibility of the L-ROI and S-ROI measurements ranged from good to excellent (ICC range: 0.71–0.99). The mean ADC values were significantly higher after NACT in the primary tumour (L-ROI p < 0.001, S-ROIs p < 0.01), and the increase after NACT was associated with sensitivity to platinum-based chemotherapy. The changes in the ADC values of the omental mass were associated with a response to NACT.ConclusionThe mean ADC values of the primary tumour increased significantly after NACT in the OC patients, and the amount of increase in omental mass was associated with the response to platinum-based NACT. Our study indicates that quantitative analysis of ADC values with a single slice and a whole tumour ROI placement is a reproducible method that has a potential role in the evaluation of NACT response in patients with OC.Trial registrationRetrospectively registered (institutional permission code: 5302501; date of the permission: 31.7.2020).

Flowmotion imaging analysis of spatiotemporal variations in skin microcirculatory perfusion.

Flowmotion is the rhythmical variations in measured skin blood flow that arise due to global and local regulation of the vessels and can be studied using frequency analysis of time-resolved blood flow signals. It has the potential to reveal clinically useful information about microvascular diseases, but the spatial heterogeneous nature of the microvasculature makes interpretation difficult. However, recent technological advances in multi-exposure laser speckle contrast imaging (MELSCI) enable new possibilities for simultaneously studying spatial and temporal variations in flowmotion. To develop a method for flowmotion analysis of MELSCI perfusion images. Furthermore, to investigate the spatial and temporal variations in flowmotion in forearm baseline skin perfusion. In four healthy subjects, forearm skin perfusion was imaged at 15.6 fps for 10 min in baseline. The time-trace signal in each pixel was analyzed using the wavelet transform and summarized in five physiologically relevant frequency intervals, resulting in images of flowmotion. Furthermore, a method for reducing the effect of motion artifacts in the flowmotion analysis was developed. The flowmotion images displayed patterns of high spatial heterogeneity that differed between the frequency intervals. The spatial variations in flowmotion, quantified as the coefficient of variation, was between 11 % and 31 % in four subjects. Furthermore, significant temporal variations in flowmotion were also observed, indicating the importance of a spatiotemporal analysis. The new imaging technique reveals significant spatial differences in flowmotion that cannot be obtained with single-point measurements. The results indicate that global statistics of flowmotion, such as the mean value in a large region of interest, is more representative of the microcirculation than data measured only in a single point. Therefore, imaging techniques have potential to increase the clinical usefulness of flowmotion analysis. • Flowmotion imaging displays significant spatiotemporal variations in forearm skin blood flow. • Flowmotion imaging has potential to be more accurate than single-point techniques. • A simple and effective method for motion artifact removal is presented.

Exploration of convolutional neural network architectures for large region map automation

Deep learning semantic segmentation algorithms have provided improved frameworks for the automated production of Land-Use and Land-Cover (LULC) maps, which significantly increases the frequency of map generation as well as consistency of production quality. In this research, a total of 28 different model variations were examined to improve the accuracy of LULC maps. The experiments were carried out using Landsat 5/7 or Landsat 8 satellite images with the North American Land Change Monitoring System labels. The performance of various CNNs and extension combinations were assessed, where VGGNet with an output stride of 4, and modified U-Net architecture provided the best results. Additional expanded analysis of the generated LULC maps was also provided. Using a deep neural network, this work achieved 92.4% accuracy for 13 LULC classes within southern Manitoba representing a 15.8% improvement over published results for the NALCMS. Based on the large regions of interest, higher radiometric resolution of Landsat 8 data resulted in better overall accuracies (88.04%) compare to Landsat 5/7 (80.66%) for 16 LULC classes. This represents an 11.44% and 4.06% increase in overall accuracy compared to previously published NALCMS results, including larger land area and higher number of LULC classes incorporated into the models compared to other published LULC map automation methods.

Nearly-lossless-to-lossy medical image compression by the optimized JPEGXT and JPEG algorithms through the anatomical regions of interest

Currently, plenty of image data is generated that complicate storage and image transmission. Great efforts have been attempted on how to increase compression ratio (CR) without loss of critical diagnostic information. In this study, we designed two optimized JPEGXT (JPEGXT_OPT) and JPEG (JPEG_OPT) approaches by amplifying discrete cosine transform coefficients and using the entire anatomical region as ROI (region of interest). We found that ROI percentages have a great impact CR: smaller ROI percentages (10–30 %) could obtain a larger CR. Under the near-lossless compression, JPEGXT_OPT could have CRs up to 4.0 under small ROI percentages (10–30 %), while only ∼ 1.2 for large ROI percentages (90–100 %). JPEG_OPT could obtain a much higher CR: up to over 20.0 for both CT and MRI images under small ROI percentages (10 %-30 %), and over 10.0 in CT and 5.0 in MRI under large ROI percentages (90 %). Both of them show a compression efficiency than the DICOM-recommended JPEGXT and JEPG_2000. From the distortion analysis, MSSIM (Multiscale Structural Similarity) and PRD (percent ratio of distortion) indicate our methods have a less image distortion than DICOM-recommended JPEGXT (PDR > 20 %) and JPEG_2000: approximately 3.0 % PRD were seen under JPEG_OPT, while<0.15 % PRD were observed under JPEGXT_OPT. MSSIM > 0.98 was found in JPEG_OPT, which the reconstructed images have almost no changes in luminance, contrast, and structure, and this was confirmed by low PRD (about 3.0 %). Overall, our two methods could provide a high compression ratio of medical images without significant loss of important diagnostic information in reconstructed images.

Numerically Stable and Computationally Efficient Expression for the Magnetic Field of a Current Loop

In this work, it is demonstrated that straightforward implementations of the well-known textbook expressions of the off-axis magnetic field of a current loop are numerically unstable in a large region of interest. Specifically, close to the axis of symmetry and at large distances from the loop, complete loss of accuracy happens surprisingly fast. The origin of the instability is catastrophic numerical cancellation, which cannot be avoided with algebraic transformations. All exact expressions found in the literature exhibit similar instabilities. We propose a novel exact analytic expression, based on Bulirsch’s complete elliptic integral, which is numerically stable (15–16 significant figures in 64 bit floating point arithmetic) everywhere. Several field approximation methods (dipole, Taylor expansions, Binomial series) are studied in comparison with respect to accuracy, numerical stability and computation performance. In addition to its accuracy and global validity, the proposed method outperforms the classical solution, and even most approximation schemes in terms of computational efficiency.

Use of specific contrast-enhanced CT regions of interest to differentiate renal oncocytomas from small clear cell and chromophobe renal cell carcinomas.

PURPOSE We aimed to examine the usefulness of utilizing a specific contrast-enhanced computed tomog raphy (CT) region of interest (ROI) to differentiate renal oncocytoma (RO) from small clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC). METHODS A retrospective analysis of pre-contrast phase (PCP), corticomedullary phase (CMP), and nephro graphic phase (NP) contrast-enhanced CT images of the histopathologically confirmed initial cohort (27 ROs, 74 ccRCCs, and 36 chRCCs) was conducted. Small, medium, large, and whole ROIs (S-ROI, M-ROI, L-ROI, and W-ROI, respectively) were utilized for CT attenuation value of tumor (AVT), lesion-to-cortex attenuation (L/C), and heterogeneous degree of tumor (HDT) calcula tions. Differences in these parameters were then compared between RO and ccRCC/chRCC, with receiver operating characteristic (ROC) curves being utilized to gauge the diagnostic utility of the statistically significant parameters. Logistic regression analyses were employed to identify key factors capable of differentiating RO and ccRCC/chRCC, with predictive models further being established. A validation cohort (6 ROs, 30 ccRCCs, and 12 chRCCs) was then employed to vali date the performance of the predictive models. RESULTS Of the parameters evaluated using different ROIs, L/C-CMP (S-ROI) (0.88 ± 0.15 vs. 1.13 ± 0.25, P < .001) and HDT-CMP (W-ROI) (23.02 (12.00-51.21) vs. 37.81 (16.09-89.45), P < .001) were best suited to differentiating RO and ccRCC, yielding respective area under the curve (AUC) values of 0.803 and 0.834. AVT-NP (S-ROI) (122.85 ± 18.87 vs. 86.50 ± 18.65, P < .001) and AVT-NP (M-ROI) (119 (86-167) vs. 81.5 (53-142), P < .001) were better able to differentiate RO and chRCC, yielding respective AUC values of 0.918 and 0.906. Logistic regression analyses revealed that L/C-CMP (S-ROI) and HDT-PCP, as well as AVT-NP (S-ROI) and HDT-CMP, were the primary factors capable of differentiating RO from ccRCC and chRCC, respectively. The predictive model developed to dif ferentiate between RO and ccRCC exhibited a sensitivity of 66.67% and 55.14% in the initial and validation cohorts, respectively, with corresponding specificity of 94.59% and 93.55%, accuracy of 87.13% and 86.84%, and AUC of 0.908 and 0.876. The predictive model developed to differ entiate between RO and chRCC exhibited a sensitivity of 85.19% and 100.00% in the initial and validation cohorts, respectively, with corresponding specificity of 94.59% and 92.86%, accuracy of 87.30% and 95.24%, and AUC of 0.944 and 0.959. CONCLUSION These data demonstrate that a combination of quantitative parameters measured with particu lar ROIs can enable the efficient and reliable differentiation of RO from ccRCC and chRCC for use in routine patient differential diagnosis.

Can the body mass index influence the skin temperature of adolescents assessed by infrared thermography?

Infrared thermography (IRT) is a technology that has been used as an auxiliary tool in the diagnostic process of several diseases and in sports monitoring to prevent injuries. However, the evaluation of a thermogram can be influenced by several factors that need to be understood and controlled to avoid a misinterpretation of the thermogram and, consequently, an inappropriate clinical action. Among the possible factors that can affect IRT are anthropometric factors, especially those related to body composition. Based on these, our objective was to verify the influence of Body Mass Index (BMI) on skin temperature (Tsk) in male adolescents. One hundred male adolescents (age: 16.83 ± 1.08 years; body mass: 66.51 ± 13.35 kg; height: 1.75 ± 7.04 m and BMI: 21.57 ± 4.06 kg/m2) were evaluated and divided into three groups, based on the World Health Organization (WHO) proposed classification ranges: underweight (n = 33), normal weight (n = 34) and overweight/obesity (n = 34). Thermograms were obtained using the FLIR T420 thermal imager after a period of acclimatization of the subjects in a controlled environment (temperature: 21.3 ± 0.7 °C and humidity: 55.3 ± 2.2%); they were evaluated using the ThermoHuman® software, integrating the original regions of interest (ROI) into seven larger ROIs. The results showed that underweight individuals had higher Tsk values than normal weight and overweight/obese individuals for all evaluated ROIs, and overweight/obese individuals had lower Tsk values than normal weight individuals for most evaluated ROIs, except for arms region. BMI showed a correlation of −0.68 and −0.64 for the anterior and posterior regions of the trunk, respectively. Thermal normality tables were proposed for various ROIs according to BMI classification. Our study demonstrated that BMI can affect the Tsk values assessed by IRT and needs to be considered to interpret the thermograms.

Characterization of COVID-19-Related Lung Involvement in Patients Undergoing Magnetic Resonance T1 and T2 Mapping Imaging: A Pilot Study.

Tissue characterization by mapping techniques is a recent magnetic resonance imaging (MRI) tool that could aid the tissue characterization of lung parenchyma in coronavirus disease-2019 (COVID-19). The aim of the present study was to compare lung MRI findings, including T1 and T2 mapping, in a group of n = 11 patients with COVID-19 pneumonia who underwent a scheduled cardiac MRI, and a cohort of healthy controls. MRI scout images were used to identify affected and remote lung regions within the patients' cohort and appropriate regions of interest (ROIs) were drawn accordingly. Both lung native T1 and T2 values were significantly higher in the affected areas of patients with COVID-19 as compared to the controls (1375 ms vs. 1201 ms, p = 0.016 and 70 ms vs. 30 ms, p &lt; 0.001, respectively), whereas no significant differences were detected between the remote lung parenchyma of the COVID-19 patients and the controls (both p &gt; 0.05). When a larger ROI was identified, comprising the whole lung parenchyma within the image irrespective of the affected and remote areas, the COVID-19 patients still retained higher native T1 (1278 ms vs. 1149 ms, p = 0.003) and T2 values (38 ms vs. 34 ms, p = 0.04). According to the receiver operator characteristics curves, the T2 value of the affected region retained the higher accuracy for the differentiation of the COVID-19 patients against the controls (area under the curve 0.934, 95% confidence interval 0.826-0.999). These findings, possibly driven by the ability of MRI tissue mapping to detect ongoing inflammation in the lungs of patients with COVID-19, suggest that T1 and T2 mapping of the lung is a feasible approach in this clinical scenario.