Quantitative Histogram Analysis Research Articles

Heterogeneity Analysis of Chest CT Predict Individual Prognosis of COVID-19 Patients.

Ground-glass Opacity (GGO) and Consolidation Opacity (CLO) are the common CT lung opacities, and their heterogeneity may have potential for prognosis ofcoronavirus disease-19 (COVID-19) patients. This study aimed to estimate clinical outcomes in individual COVID-19 patients using histogram heterogeneity analysis based on CT opacities. 71 COVID-19 cases' medical records were retrospectively reviewed from a designated hospital in Wuhan, China, from January 24th to February 28th at the early stage of the pandemic. Two characteristic lung abnormity opacities, GGO and CLO, were drawn on CT images to identify the heterogeneity using quantitative histogram analysis. The parameters (mean, mode, kurtosis, and skewness) were derived from histograms to evaluate the accuracy of clinical classification and outcome prediction. Nomograms were built to predict the risk of death and median length of hospital stays (LOS), respectively. A total of 57 COVID-19 cases were eligible for the study cohort after excluding 14 cases. The highest lung abnormalities were GGO mixed with CLO in both the survival populations (26 in 42, 61.9%) and died population (10 in 15, 66.7%). The best performance heterogeneity parameters to discriminate severe type from mild/moderate counterparts were as follows: GGO_skewness: specificity= 66.67%, sensitivity=78.12%, AUC=0.706; CLO_mean: specificity=70.00%, sensitivity= 76.92%, and AUC=0.746. Nomogram based on histogram parameters can predict the individual risk of death and the prolonged median LOS of COVID-19 patients. C-indexes were 0.763 and 0.888 for risk of death and prolonged median LOS, respectively. Histogram analysis method based on GGO and CLO has the ability for individual risk prediction in COVID-19 patients.

Correlation between molecular prognostic factors and magnetic resonance imaging intravoxel incoherent motion histogram parameters in breast cancer

ObjectiveTo explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer. Materials and methodsA total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images. Whole-tumor histogram parameters were obtained with Firevoxel's software by accumulating all ROIs. Next, Kolmogorov-Smirnov test, Student's t-test, Mann-Whitney U test, receiver operating characteristic curve analysis and spearman rank correlation analysis were used to assess the relationship between histogram parameters and molecular prognostic factors of breast cancer. ResultsAmong estrogen receptor (ER)-negative ROCs, the apparent diffusion coefficient (ADC) 10th percentile had the highest ROC of 0.792, with a cut-off value of 0.788 × 10−3 mm2/s, and sensitivity and specificity of 0.714 and 0.867, respectively. The negative correlation between lymph node metastasis status and ADC standard deviation was significant (ρ = −0.44, the correlation coefficients was represented by ρ). Positive correlations were observed between hormonal expression of ER and progesterone receptor (PR) with heterogeneity metrics of ADC or perfusion fraction (f), such as ADC inhomogeneity (ρ = 0.37, ρ = 0.29) and f skewness (ρ = 0.32, ρ = 0.28). Negative correlations were observed with numerical metrics, such as the ADC median (ρ = −0.31, ρ = −0.34) and f 45th percentile (ρ = −0.35, ρ = −0.28). The positive correlations between human epidermal receptor factor-2 (HER2) and pseudo-diffusivity (Dp) numerical metrics, Ki-67 expression, and heterogeneity metrics of Dp were high. ConclusionsThe ADC 10th percentile had the largest area under the curve in the ER-negative ROC analysis, and the ADC standard deviation was the most valuable in the correlation analysis of lymph node metastasis. Whole-lesion quantitative histogram parameters of IVIM could, therefore, provide a scientific basis for radiomics to further guide clinical practice in the prognosis of breast cancer.

Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses.

BackgroundThe incidence of chronic kidney disease (CKD) is high, and is easy to develop into end-stage renal disease (ESRD), which requires kidney dialysis or kidney transplantation. Therefore, we want to explore the clinical value of magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses (SLEEK) in assessing renal function in the early stage.MethodsOne hundred and twenty-nine patients underwent abdominal MRI examination, including a coronal SLEEK sequence. The patients were divided into the control group [CG, 47 cases, estimated glomerular filtration rate (eGFR) >90], the mild renal function impairment (mRI) group (48 cases, eGFR =60–90), and the moderate to severe renal function impairment (m-sRI) group (34 cases, eGFR <60). Two experienced radiologists delineated cortex and medulla regions of interest (ROIs) on SLEEK images to obtain cortex and medulla quantitative histogram parameters [Mean, Median, Percentiles (5th, 10th, 25th, 75th, and 90th), Skewness, Kurtosis, and Entropy] using FireVoxel. These histogram parameters were compared by proper statistical methods such as one-way analysis of variance, the χ2 test, and receiver operating characteristic (ROC) curve analysis.ResultsFour histogram parameters (Inhomogeneitycortex, Skewnesscortex, Kurtosismedulla, and Entropymedulla) differed significantly between the CG and the mRI group. One medulla (Entropymedulla) and nine cortex (Meancortex, Mediancortex, Kurtosiscortex, Entropycortex, and 5th, 10th, 25th, 75th, and 90th Percentilecortex) histogram parameters were significantly different between the m-RI and m-sRI groups. The most relevant parameter to eGFR was Inhomogenitycortex (r=−0.450, P<0.001). Inhomogeneitycortex had the largest area under the curve (AUC) for differentiating the mRI group from the CG (AUC =0.718; 95% CI: 0.616–0.806), while 25th Percentilecortex generated the largest AUC (AUC =0.786; 95% CI: 0.681–0.869) for differentiating the mRI and m-sRI groups.ConclusionsQuantitative histogram parameters based on a SLEEK sequence can be used to supplement renal dysfunction assessment. Cortex histogram parameters are more valuable for evaluating renal function than medulla histogram parameters.

Improved value of whole-lesion histogram analysis on DCE parametric maps for diagnosing small breast cancer (≤ 1cm).

To determine if whole-lesion histogram analysis on dynamic contrast-enhanced (DCE) parametric maps help to improve the diagnostic accuracy of small suspicious breast lesions (≤ 1cm). This retrospective study included 99 female patients with 114 lesions (40 malignant and 74 benign lesions) suspicious on magnetic resonance imaging (MRI).Two radiologists reviewed all lesions and descripted the morphologic and kinetic characteristics according to BI-RADS by consensus. Whole lesions were segmented on DCE parametric maps (washin and washout), and quantitative histogram features were extracted. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. Diagnostic performance was assessed and compared with that of qualitative BI-RADS assessment and quantitative histogram analysis by ROC analysis. For malignancy defined as a washout or plateau pattern, the qualitative kinetic pattern showed a significant difference between the two groups (p = 0.023), yielding an AUC of 0.603 (95% confidence interval [CI]: 0.507, 0.694). The mean and median of washout were independent quantitative predictors of malignancy (p = 0.002, 0.010), achieving an AUC of 0.796 (95% CI: 0. 709, 0.865). The AUC of the quantitative model was better than that of the qualitative model (p < 0.001). Compared with the qualitative BI-RADS assessment, quantitative whole-lesion histogram analysis on DCE parametric maps was better to discriminate between small benign and malignant breast lesions (≤ 1cm) initially defined as suspicious on DCE-MRI. • For malignancy defined as a washout or plateau, the kinetic pattern may provide information to diagnose small breast cancer. • The mean and median of washout map were significantly lower for small malignant breast lesions than for benign lesions. • Quantitative histogram analysis on MRI parametric maps improves diagnostic accuracy for small breast cancer, which may obviate unnecessary biopsy.

Brain Magnetic Resonance Imaging Reveals Different Courses of Disease in Pediatric and Adult Cerebral Malaria.

BackgroundCerebral malaria is a common presentation of severe Plasmodium falciparum infection and remains an important cause of death in the tropics. Key aspects of its pathogenesis are still incompletely understood, but severe brain swelling identified by magnetic resonance imaging (MRI) was associated with a fatal outcome in African children. In contrast, neuroimaging investigations failed to identify cerebral features associated with fatality in Asian adults. MethodsQuantitative MRI with brain volume assessment and apparent diffusion coefficient (ADC) histogram analyses were performed for the first time in 65 patients with cerebral malaria to compare disease signatures between children and adults from the same cohort, as well as between fatal and nonfatal cases. ResultsWe found an age-dependent decrease in brain swelling during acute cerebral malaria, and brain volumes did not differ between fatal and nonfatal cases across both age groups. In nonfatal disease, reversible, hypoxia-induced cytotoxic edema occurred predominantly in the white matter in children, and in the basal ganglia in adults. In fatal cases, quantitative ADC histogram analyses also demonstrated different end-stage patterns between adults and children: Severe hypoxia, evidenced by global ADC decrease and elevated plasma levels of lipocalin-2 and microRNA-150, was associated with a fatal outcome in adults. In fatal pediatric disease, our results corroborate an increase in brain volume, leading to augmented cerebral pressure, brainstem herniation, and death. ConclusionsOur findings suggest distinct pathogenic patterns in pediatric and adult cerebral malaria with a stronger cytotoxic component in adults, supporting the development of age-specific adjunct therapies.

Evaluation of hepatic steatosis before liver transplantation in ex vivo by volumetric quantitative PDFF-MRI.

Over the last two decades, extended criteria have promoted an increased number of donor livers available for liver transplantation. But posttransplant graft loss is still a major concern. Macrovesicular hepatic steatosis (MHS) is recognized as the most significant prognostic histologic parameter in predicting posttransplant graft loss. We aimed to evaluate the utility of ex vivo volumetric quantitative MRI for quantifying MHS before liver transplantation using proton density fat-fraction (PDFF-MRI) histogram analysis. PDFF-MRI was performed at 3.0T in 40 livers. We obtained histogram parameters of whole-liver volume of interest, including the mean, median, 5th, 10th, 25th, 75th, 90th, and 95th percentile PDFF; skewness; kurtosis; entropy; and volume. Livers from 40 cadaveric donors were included, and histologic ex vivo fat quantification was available for 33 livers. Ten livers had MHS and 23 had normal fat content. The MHS group had higher mean, median, 5th, 10th, 25th, 75th, 90th, and 95th percentile PDFF, and entropy than the group with normal fat content (P < .05). Median PDFF had greater area under the curve value than other parameters. Mean PDFF showed an excellent correlation with entropy and a moderate correlation with MHS quantification on histology. Ex vivo volumetric quantitative PDFF-MRI histogram analysis is a very useful and noninvasive method to detect MHS before liver transplantation. Median PDFF was the best predictor of the presence of MHS. Entropy is a very promising parameter.

The value of 3.0T magnetic resonance -diffusion kurtosis imaging in the differential diagnosis of rectal mucinous adenocarcinoma and common adenocarcinoma

Objective: To investigate the value of 3.0T MRI diffusion kurtosis imaging (DKI) quantitative histogram parameters in the differential diagnosis of rectal mucinous adenocarcinoma (MC) and common adenocarcinoma (AC). Methods: One hundred and ten patients from Department of Radiology, the Second Affiliated Hospital of Soochow University between September 2015 and September 2019 with complete magnetic resonance imaging (MRI) and DKI results confirmed by surgery and pathology were retrospectively analyzed, including 16 patients in MC group and 94 patients in AC group. Two physicians outlined the region of interest (ROI) on the DKI image with b=1 000 s/mm(2), and obtained quantitative DKI parameters, including the diffusion coefficient (D value) and kurtosis coefficient (K value) corrected for non-Gaussian distribution. The apparent diffusion coefficient (ADC) values of quantitative parameters of diffusion-weighted imaging (DWI) were obtained through image registration, and histogram analysis was performed to obtain the mean value, 25th percentile, 50th percentile, 75th percentile, skewness and kurtosis of the above parameters, respectively. The difference between the quantitative histogram parameter analysis results of the rectal MC group and the AC group was evaluated, and the main indicators and multivariate comprehensive analysis indicators was screened, and the effectiveness of quantitative histogram parameters related to histopathological classification in the differential diagnosis of rectal MC and AC was evaluated. Results: There was no significant differences in gender, age, lesion location, T stage or N stage between MC group and AC group (all P>0.05). The multivariate binary logistic stepwise regression screening showed that D50th percentile and K25th percentile are statistically significant indicators (B values were 2 966.166 and -4.550, respectively; Wals values were 9.000 and 15.720, respectively; and P values were 0.003 and <0.001, respectively). The combined area under the curve of the two indictors was 0.85, but there was no statistically significant difference in pairwise comparison using DeLong method (P>0.05). The results of histogram analysis of quantitative parameters measured by the two physicians were consistent, and the inter-group correlation coefficient ranged from 0.880 to 0.981. Conclusions: The quantitative parameter histogram analysis of the DKI double-index model is helpful for the differentiation of rectal MC and AC, in which the D50th percentile and K25th percentile have differential diagnosis significance, and are superior to the ADC value of the single-index model.

Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers.

Objective To investigate if histogram analysis and visually assessed heterogeneity of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping can predict molecular subtypes of invasive breast cancers. Materials and Methods In this retrospective study, 91 patients with invasive breast carcinoma who underwent preoperative magnetic resonance imaging (MRI) with DWI at our institution were included. Two radiologists delineated a 2-D region of interest (ROI) on ADC maps in consensus. Tumors were also independently classified into low and high heterogeneity based on visual assessment of DWI. First-order statistics extracted through histogram analysis within the ROI of the ADC maps (mean, 10th percentile, 50th percentile, 90th percentile, standard deviation, kurtosis, and skewness) and visually assessed heterogeneity were evaluated for associations with tumor receptor status (ER, PR, and HER2 status) as well as molecular subtype. Results HER2-positive lesions demonstrated significantly higher mean (p=0.034), Perc50 (p=0.046), and Perc90 (p=0.040), with AUCs of 0.605, 0.592, and 0.652, respectively, than HER2-negative lesions. No significant differences were found in the histogram values for ER and PR statuses. Neither quantitative histogram analysis based on ADC maps nor qualitative visual heterogeneity assessment of DWI images was able to significantly differentiate between molecular subtypes, i.e., luminal A versus all other subtypes (luminal B, HER2-enriched, and triple negative) combined, luminal A and B combined versus HER2-enriched and triple negative combined, and triple negative versus all other types combined. Conclusion Histogram analysis and visual heterogeneity assessment cannot be used to differentiate molecular subtypes of invasive breast cancer.

Whole Tumor Histogram Analysis Using DW MRI in Primary Central Nervous System Lymphoma Correlates with Tumor Biomarkers and Outcome.

The ability to non-invasively predict outcomes and monitor treatment response in primary central nervous system lymphoma (PCNSL) is important as treatment regimens are constantly being trialed. The aim of this study was to assess the validity of using apparent diffusion coefficient (ADC) histogram values to predict Ki-67 expression, a tumor proliferation marker, and patient outcomes in PCNSL in both immunocompetent patients and patients living with HIV (PLWH). Qualitative PCNSL magnetic resonance imaging (MRI) characteristics from 93 patients (23 PLWH and 70 immunocompetent) were analyzed, and whole tumor segmentation was performed on the ADC maps. Quantitative histogram analyses of the segmentations were calculated. These measures were compared to PCNSL Ki-67 expression. Progression-free survival (PFS) and overall survival (OS) were analyzed via comparison to the International Primary Central Nervous System Lymphoma Collaboration Group Response Criteria. Associations between ADC measures and clinical outcomes were assessed using univariate and multivariate Cox proportional hazards models. Normalized ADC (nADC)Min, nADCMean, nADC1, nADC5, and nADC15 values were significantly associated with a poorer OS. nADCMax, nADCMean, nADC5, nADC15, nADC75, nADC95, nADC99 inversely correlated with Ki-67 expression. OS was also significantly associated with lesion hemorrhage. PFS was not significantly associated with ADC values but with lesion hemorrhage. ADC histogram values and related parameters can predict the degree of tumor proliferation and patient outcomes for primary central nervous system lymphoma patients and in both immunocompetent patients and patients living with HIV.

The influence of trimming of the hoof wall on the damage of laminar tissue after loading: An in vitro study

Laminitis is associated with failure of the suspensory apparatus of the distal phalanx (SADP) connecting the distal phalanx to the hoof wall. The specific aim of this study was to examine in vitro whether thinning of the hoof wall leading to increased deformability influences the damage of the laminar tissue created by loading of the hoof. Paired cadaver forelimbs from twelve horses were used. For each pair, the hoof wall from one hoof was thinned by 25%; this was ascertained by radiography. The contralateral hooves were used as controls. In a material testing machine, hooves were loaded in a proximodistal direction at 0.5mm/s until a cut-off value of 8kN or 14mm was reached. Afterwards, samples of the SADP were taken for histology. Image-based evaluation of the destruction of the SADP was performed using quantitative histogram analysis. Additionally, three examiners masked to treatment (trimmed/untrimmed) qualitatively evaluated SADP destruction.During hoof loading with forces from 0.5 to 1.8 times the body mass of the donor horses, hooves with thinned hoof wall underwent significantly more deformation (P<0.05). Quantitative histogram analysis detected a shift to higher brightness values and a higher pixel intensity in control hooves, representing disruption in the histologic analysis. Qualitative evaluation of histology sections showed significantly more disruption of the SADP in untrimmed hooves (P=0.03). These results confirm the hypothesis that reduced hoof wall thickness can decrease disruption of laminar tissue in vitro, thus supporting the evaluation of hoof wall reduction as a prophylactic measure in horses at imminent risk of SADP failure.

Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping

Background and purposeThe ability to predict high-grade meningioma preoperatively is important for clinical surgical planning. The purpose of this study is to evaluate the performance of comprehensive multiparametric MRI, including susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) in predicting high-grade meningioma both qualitatively and quantitatively. MethodsNinety-two low-grade and 37 higher grade meningiomas in 129 patients were included in this study. Morphological characteristics, quantitative histogram analysis of QSM and ADC images, and tumor size were evaluated to predict high-grade meningioma using univariate and multivariate analyses. Receiver operating characteristic (ROC) analyses were performed on the morphological characteristics. Associations between Ki-67 proliferative index (PI) and quantitative parameters were calculated using Pearson correlation analyses. ResultsFor predicting high-grade meningiomas, the best predictive model in multivariate logistic regression analyses included calcification (β=0.874, P=0.110), peritumoral edema (β=0.554, P=0.042), tumor border (β=0.862, P=0.024), tumor location (β=0.545, P=0.039) for morphological characteristics, and tumor size (β=4×10−5, P=0.004), QSM kurtosis (β=−5×10−3, P=0.058), QSM entropy (β=−0.067, P=0.054), maximum ADC (β=−1.6×10−3, P=0.003), ADC kurtosis (β=−0.013, P=0.014) for quantitative characteristics. ROC analyses on morphological characteristics resulted in an area under the curve (AUC) of 0.71 (0.61–0.81) for a combination of them. There were significant correlations between Ki-67 PI and mean ADC (r=−0.277, P=0.031), 25th percentile of ADC (r=−0.275, P=0.032), and 50th percentile of ADC (r=−0.268, P=0.037). ConclusionsAlthough SWI and QSM did not improve differentiation between low and high-grade meningiomas, combining morphological characteristics and quantitative metrics can help predict high-grade meningioma.

Assessment of the blood flow in kidneys of growth-restricted fetuses using quantitative three-dimensional power Doppler ultrasound

ObjectiveFetuses with fetal growth restrictions have higher perinatal mortality rates than fetuses without fetal growth restrictions. Vascularization of the fetal kidney is crucial to fetal growth. Hence, we assessed blood flow and vascularization of fetal kidneys in non-growth-restricted as well as growth-restricted fetuses using quantitative three-dimensional power Doppler ultrasound. Materials and methodsWe undertook a prospective study to evaluate the vascular indices of fetal kidneys; i.e., the vascularization index, flow index and vascularization-flow index, in growth-restricted and non-growth-restricted fetuses using three-dimensional power Doppler ultrasound and quantitative three-dimensional histogram analysis. All fetuses from 20 to 40 weeks of gestation were singletons with a normal pregnancy and were followed up to delivery. ResultsIn total, 209 fetuses without fetal growth restriction and 50 fetuses with fetal growth restriction were included. Our results showed the fetal renal vascularization index, flow index, and vascularization-flow index evaluated by three-dimensional power Doppler ultrasound can differentiate fetuses with fetal growth restriction from fetuses without fetal growth restriction. ConclusionThe fetal renal vascularization index, flow index, and vascularization-flow index measured by three-dimensional power Doppler ultrasound can be applied to prenatally detect fetal growth restriction. Our data support assessment of the fetal renal vascularization index, flow index, and vascularization-flow index using three-dimensional power Doppler ultrasound as a useful test for detecting fetuses with fetal growth restriction.

Predicting tumor recurrence in patients with cervical carcinoma treated with definitive chemoradiotherapy: value of quantitative histogram analysis on diffusion-weighted MR images.

Background Further research is required for evaluating the use of ADC histogram analysis in more advanced stages of cervical cancer treated with definitive chemoradiotherapy (CRT). Purpose To investigate the utility of apparent diffusion coefficient (ADC) histogram derived from diffusion-weighted magnetic resonance images in cervical cancer patients treated with definitive CRT. Material and Methods The clinical and radiological data of 50 patients with histologically proven cervical squamous cell carcinoma treated with definitive CRT were retrospectively analyzed. The impact of clinicopathological factors and ADC histogram parameters on prognostic factors and treatment outcomes was assessed. Results The mean and median ADC values for the cohort were 1.043 ± 0.135 × 10-3 mm2/s and 1.018 × 10-3 mm2/s (range, 0.787-1.443 × 10-3 mm2/s). The mean ADC was significantly lower for patients with advanced stage (≥IIB) or lymph node metastasis compared with patients with stage <IIB or no lymph node metastasis. The mean ADC, 75th percentile ADC (ADC75), 90th percentile ADC (ADC90), and 95th percentile ADC (ADC95) were significantly lower in patients with tumor recurrence compared with patients without recurrence. In multivariate analysis, tumor size, ADC75 and ADC95 were independent prognostic factors for both overall survival and disease-free survival. Conclusion ADC histogram parameters could be markers for disease recurrence and for predicting survival outcomes. ADC75, ADC90, and ADC95 of the primary tumor were significant predictors of disease recurrence in cervical cancer patients treated with definitive CRT.

Single STE-MR Acquisition in MR-Based Attenuation Correction of Brain PET Imaging Employing a Fully Automated and Reproducible Level-Set Segmentation Approach.

The aim of this study is to introduce a fully automatic and reproducible short echo-time (STE) magnetic resonance imaging (MRI) segmentation approach for MR-based attenuation correction of positron emission tomography (PET) data in head region. Single STE-MR imaging was followed by generating attenuation correction maps (μ-maps) through exploiting an automated clustering-based level-set segmentation approach to classify head images into three regions of cortical bone, air, and soft tissue. Quantitative assessment was performed by comparing the STE-derived region classes with the corresponding regions extracted from X-ray computed tomography (CT) images. The proposed segmentation method returned accuracy and specificity values of over 90% for cortical bone, air, and soft tissue regions. The MR- and CT-derived μ-maps were compared by quantitative histogram analysis. The results suggest that the proposed automated segmentation approach can reliably discriminate bony structures from the proximal air and soft tissue in single STE-MR images, which is suitable for generating MR-based μ-maps for attenuation correction of PET data.

Age-related changes in pancreatic elasticity: When should we be concerned about their effect on strain elastography?

BackgroundUltrasound strain elastography is one of the useful methods for evaluating pancreatic lesions. During aging, several pancreatic parenchymal changes occur that may interfere with the interpretation of the ultrasound images. We studied age-related changes in pancreatic elasticity using transabdominal ultrasound strain elastography in subjects without known pancreatic disease. MethodsThis study was conducted at Nagoya University Hospital, which is an academic medical center, and included 102 subjects (66 women and 39 men) aged 20–85years (mean 58.6±17.5) who underwent transabdominal ultrasonography for screening and follow-up for non-pancreatic diseases. Strain elastography of the pancreas was performed, and the results were subjected to quantitative strain histogram analysis. The correlations of age with four elastographic parameters (Mean, Standard deviation, Skewness, and Kurtosis) and other findings, including hyperechoic pancreas, hyperechoic liver, and diabetes, were evaluated. ResultsThere was a significant correlation between increasing age and elastographic parameters such as the Mean (P=0.004), Skewness (P=0.007), and Kurtosis (P=0.03), and these differences became significant after the age of 40. The prevalence of hyperechoic pancreas increased with age (P<0.001), and the Means were lower in those with hyperechoic pancreas (P=0.004) and a higher body mass index (BMI, P=0.008). No significant correlations with diabetes, hyperechoic liver, or elastographic parameters were demonstrated. ConclusionStrain elastography demonstrated elastographic changes in the pancreas with aging that included a decreasing Mean and increasing Skewness and Kurtosis after the age of 40. The prevalence of pancreatic hyperechogenicity increased, and the pancreatic hyperechogenicity was significantly negatively correlated with the Mean.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis.

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health.

Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors.

Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas. Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p < .01. The study population included 17 children with pilocytic astrocytoma and 16 with medulloblastoma (mean age, 9.21 ± 5.18 years and 7.66 ± 4.97 years, respectively). Compared to children with medulloblastoma, children with pilocytic astrocytoma showed higher MD (P = .003 and P = .008), AD (P = .004 and P = .007), and RD (P = .003 and P = .009) values for the 25th and 75th percentile. In addition, histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008). The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology.

3D Power Doppler ultrasound and computerised placental assessment in normal pregnancy

BackgroundIn recent years there have been significant developments in the use of 3D Power Doppler (3DPD) imaging and quantitative 3DPD histogram analysis to estimate both placental volume and intra-placental vasculature. This study aims to determine if placental volume, vascularisation and blood flow are correlated with gestational age in normal pregnancy. It also examines whether or not a new software method for analysis of percentage calcification (the ‘placentometer’) correlates well with gestation. Material and methodThis was a prospective cohort study of 250 women with normal pregnancies (12 + 6 to 39 + 5 weeks gestation). 3DPD ultrasound was used to evaluate placental volume, vascularisation index (VI), flow index (FI) and vascularisation-flow index (VFI). Placental volume (calculated at 35–40 weeks gestation), was correlated with birth weight. Following each scan the percentage of calcification was also calculated using the placentometer. ResultsPlacental volume correlated significantly with gestational age: 66.676 + 0.623 × GA (P < 0.001). No significant change with gestation was noted in VI, FI and VFI (VI: P = 0.199, FI: P = 0.299, VFI: P = 0.557). Software analysis of the percentage of calcification, demonstrated the expected increase in calcification as gestation increased: −4.605 + 0.032 × GA (P < 0.001). From 35 to 40 weeks gestation volume was related to birth weight (P < 0.01). ConclusionThis study shows that in normal low-risk pregnancy placental volume increases with gestational age, whereas vascularisation and blood flow are independent of gestation. Placental volume in late pregnancy is related to birth weight. Software analysis of the percentage of calcification demonstrates an increase with advancing gestation.

Histogram Analysis of Lipid-Core Plaques in Coronary Computed Tomographic Angiography

In coronary computed tomographic angiography (CTA), low attenuation of coronary atherosclerotic plaque is associated with lipid-rich plaques. However, an overlap in Hounsfield units (HU) between fibrous and lipid-rich plaque as well as an influence of luminal enhancement on plaque attenuation was observed and may limit accurate detection of lipid-rich plaques by CTA. We sought to determine whether the quantitative histogram analysis improves accuracy of the detection of lipid-core plaque (LCP) in ex vivo hearts by validation against histological analysis. Human donor hearts were imaged with a 64-slice computed tomographic scanner using a standard coronary CTA protocol, optical coherence tomography (OCT), a histological analysis. Lipid-core plaque was defined in the histological analysis as any fibroatheroma with a lipid/necrotic core diameter of greater than 200 μm and a circumference greater than 60 degrees as well as a cap thickness of less than 450 μm. In OCT, lipid-rich plaque was determined as a signal-poor region with diffuse borders in 2 quadrants or more. In CTA, the boundaries of the noncalcified plaque were manually traced. The absolute and relative areas of low attenuation plaque based on pixels with less than 30, less than 60, and less than 90 HU were calculated using quantitative histogram analysis. From 5 hearts, a total of 446 cross sections were coregistered between CTA and the histological analysis. Overall, 55 LCPs (12%) were identified by the histological analysis. In CTA, the absolute and relative areas of low attenuation plaque less than 30, less than 60, and less than 90 HU were 0.14 (0.31) mm2 (4.22% [9.02%]), 0.69 (0.95) mm2 (18.28% [21.22%]), and 1.35 (1.54) mm2 (35.65% [32.07%]), respectively. The low attenuation plaque area correlated significantly with histological lipid content (lipid/necrotic core size [in square millimeter] and a portion of lipid/necrotic core on the entire plaque) at all thresholds but was the strongest at less than 60 HU (r = 0.53 and r = 0.48 for the absolute and relative areas, respectively). Using a threshold of 1.0 mm2 or greater, the absolute plaque area of less than 60 HU in CTA yielded 69% sensitivity and 80% specificity to detect LCP, whereas sensitivity and specificity were 73% and 71% for using 25.0% or higher relative area less than 60 HU. The discriminatory ability of CTA for LCP was similar between the absolute and relative areas (the area under the curve, 0.744 versus 0.722; P = 0.37). Notably, the association of the low attenuation plaque area in CTA with LCP was not altered by the luminal enhancement for the relative (P = 0.48) but for the absolute measurement (P = 0.03). Similar results were achieved when validated against lipid-rich plaque by OCT in a subset of 285 cross sections. In ex vivo conditions, the relative area of coronary atherosclerotic plaque less than 60 HU in CTA as derived from quantitative histogram analysis has good accuracy to detect LCP as compared with a histological analysis independent of differences in luminal contrast enhancement.

Ultrasound for evaluation of adnexal malignancy: From 2D to 3D ultrasound

Conventional two-dimensional (2D) ultrasound has been widely used for the evaluation of adnexal malignancy in gynecologic fields. This 2D ultrasound evaluation includes a morphological assessment, color/power and pulsed Doppler sonographic assessment, scoring system, and contrast agent assessment of adnexal masses. The introduction of three-dimensional (3D) ultrasound would facilitate the novel assessment of adnexal masses. With the recent advance in 3D power Doppler (3DPD) ultrasound as well as quantitative 3DPD histogram analysis, quantitative and qualitative assessments of the vascularization and blood flow of adnexal masses have become feasible. These novel techniques may assist in the evaluation of adnexal malignancy, and offer potential advantages relative to conventional 2D sonographic assessments. 3D ultrasound may be an important modality in future gynecologic oncology research and in the evaluation of adnexal malignancy in clinical practice, although some limitations regarding the assessment of adnexal malignancy employing 3D ultrasound remain unresolved.