scholarly journals Combined 18F-FET PET and diffusion kurtosis MRI in post-treatment glioblastoma: differentiation of true progression from treatment related changes

2021 ◽  
Author(s):  
Francesco D’Amore ◽  
Farida Grinberg ◽  
Jörg Mauler ◽  
Norbert Galldiks ◽  
Ganna Blazhenets ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Diagnostic Accuracy ◽  
Diffusion Mri ◽  
Tumour Progression ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Regions Of Interest ◽  
Fet Pet ◽  
Diffusion Kurtosis ◽  
And Diffusion

Abstract Background Radiological differentiation of tumour progression (TPR) from treatment-related changes (TRC) in pre-treated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O-(2-[ 18F]-fluoroethyl)-L-tyrosine ( 18F-FET) PET for the differentiation of TPR from TRC in patients with pre-treated glioblastoma. Methods Thirty-two patients with histomolecularly defined and pre-treated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. 3D regions-of-interest were generated based on increased 18F-FET uptake using a brain-to-tumour ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions-of-interests using co-registered 18F-FET PET images, and an advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions-of-interest. Diagnostic accuracy was analysed by receiver-operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression. Results Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumour-to-brain ratio of 18F-FET uptake and diffusion MRI kurtosis metrics. Conclusions The combined use of 18F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pre-treated glioblastoma and warrants further investigation.

Value of Fibrinogen to Discriminate Appendicitis from Nonspecific Abdominal Pain in Preschool Children

2019 ◽  
Vol 30 (04) ◽  
pp. 357-363
Author(s):  
Javier Gómez-Veiras ◽  
Ángel Salgado-Barreira ◽  
José Luis Vázquez ◽  
Margarita Montero-Sánchez ◽  
José Ramón Fernández-Lorenzo ◽  
...  
Keyword(s):  
Abdominal Pain ◽  
Preschool Children ◽  
Diagnostic Accuracy ◽  
Prothrombin Time ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Suspected Appendicitis ◽  
Uncomplicated Appendicitis ◽  
Good Diagnostic Accuracy

Introduction The aim of this study was to assess the diagnostic value of the biomarker fibrinogen (FB), along with the markers white blood cell (WBC) count, absolute neutrophil count (ANC), and C-reactive protein (CRP), to discriminate appendicitis from nonspecific abdominal pain (NSAP) in preschool children. Materials and Methods We prospectively evaluated all children aged <5 years admitted for suspected appendicitis at an academic pediatric emergency department during 5 years. Diagnostic accuracy of FB (prothrombin time–derived method), WBC, ANC, and CRP were assessed by the area under the curve (AUC) of the receiver-operating characteristic curve. Results A total of 82 patients were enrolled in the study (27 NSAP, 17 uncomplicated, and 38 complicated appendicitides). WBC and ANC had moderate diagnostic accuracy for appendicitis versus NSAP (WBC: AUC 0.66, ANC: AUC 0.67). CRP and FB had good diagnostic accuracy for appendicitis versus NSAP (CRP: AUC 0.78, FB: AUC 0.77). WBC and ANC are not useful to discriminate complicated versus uncomplicated appendicitis (WBC: AUC 0.43, ANC: AUC 0.45). CPR and FB had good diagnostic accuracy for complicated versus uncomplicated appendicitis (CRP: AUC 0.80, FB: AUC 0.73). Conclusion CRP and FB are more useful than WBC and ANC to discriminate appendicitis from NSAP in preschool children. CRP and FB are especially useful to discriminate complicated from uncomplicated appendicitis and NSAP. In a child with suspected appendicitis, a plasma FB level (prothrombin time–derived method) >540 mg/dL is associated with an increased likelihood of complicated appendicitis.

Diagnostic accuracy of IGF-1 for screening growth hormone deficiency: a prospective, single-center, diagnostic accuracy study

2021 ◽  
Author(s):  
Hideyuki Iwayama ◽  
Sachiko Kitagawa ◽  
Jyun Sada ◽  
Ryosuke Miyamoto ◽  
Tomohito Hayakawa ◽  
...  
Keyword(s):  
Growth Hormone ◽  
Diagnostic Accuracy ◽  
Growth Hormone Deficiency ◽  
Predictive Value ◽  
Screening Test ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Rank Correlation ◽  
Hormone Deficiency ◽  
Height Velocity

Abstract Purpose We evaluated the diagnostic accuracy of insulin-like growth factor-1 (IGF-1) for screening growth hormone deficiency (GHD) to determine the usefulness of IGF-1 as a screening test. Methods On 298 consecutive children who had short stature or decreased height velocity, we measured IGF-1 levels and performed growth hormone (GH) secretion test using clonidine, arginine, and, in cases with different results of the two tests, L-dopa. Patients with congenital abnormalities were excluded. GHD was defined as peak GH ≤ 6.0 ng/mL in the two tests. Results We identified 60 and 238 patients with and without GHD, respectively. The mean IGF-1 (SD) was not significantly different between the GHD and non-GHD groups (p = 0.23). Receiver operating characteristic curve analysis demonstrated the best diagnostic accuracy at an IGF-1 cutoff of −1.493 SD, with sensitivity of 0.685, specificity of 0.417, positive predictive value of 0.25, negative predictive value of 0.823, and area under the curve of 0.517. Spearman’s rank correlation coefficient showed that IGF-1 (SD) was weakly correlated with age, bone age, height velocity before examination, weight (SD), and BMI (SD) and very weakly correlated with height (SD), target height (SD), and maximum GH peak. Conclusion IGF-1 level had poor diagnostic accuracy as a screening test for GHD. Correlation analysis revealed that none of the items increased the diagnostic power of IGF-1. Therefore, IGF-1 should not be used alone in the screening of GHD. A predictive biomarker for GHD should be developed in the future.

scholarly journals Accuracy of apparent diffusion coefficients and enhancement ratios on magnetic resonance imaging in differentiating primary cerebral lymphomas from glioblastoma

2019 ◽  
Vol 32 (5) ◽  
pp. 328-334 ◽  
Author(s):  
Shayan Sirat Maheen Anwar ◽  
Mirza Zain Baig ◽  
Altaf Ali Laghari ◽  
Fatima Mubarak ◽  
Muhammad Shahzad Shamim ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Regions Of Interest ◽  
Post Contrast ◽  
Apparent Diffusion Coefficients ◽  
Normal Appearing White Matter ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Patient Subgroups

Background and purposeThis study aimed to determine the accuracy of apparent diffusion coefficient (ADC) and enhancement ratio (ER) in discriminating primary cerebral lymphomas (PCL) and glioblastomas.Materials and methodsCircular regions of interest were randomly placed centrally within the largest solid-enhancing area of all lymphomas and glioblastomas on both post-contrast T1-weighted images and corresponding ADC maps. Regions of interest were also drawn in the contralateral hemisphere to obtain enhancement and ADC values of normal-appearing white matter. This helped us to calculate the ER and ADC ratio.ResultsMean enhancement and ADC (mm2/s) values for PCL were 2220.56 ± 2948.30 and 712.00 ± 137.87, respectively. Mean enhancement and ADC values for glioblastoma were 1537.07 ± 1668.33 and 1037.93 ± 280.52, respectively. Differences in ADC values, ratios and ERs were all statistically significant between the two groups ( p < 0.05). ADC values correctly predicted 71.4% of the lesions as glioblastoma and 83.3% as PCL (area under the curve (AUC) = 0.86 on receiver operating characteristic curve analysis). ADC ratios correctly predicted 85.7% of the lesions as glioblastoma and 100% as PCL (AUC = 0.93). ERs correctly predicted 71.4% of the lesions as glioblastoma and 88.9% as PCL (AUC = 0.92). The combination of ADC ratio and ER correctly predicted 100% tumour type in both patient subgroups.ConclusionsADC values, ADC ratios and ERs may serve as useful variables to distinguish PCL from glioblastoma. The combination of ADC ratio and ER yielded the best results in identification of both patient subgroups.

scholarly journals Sinkhole Detection and Characterization Using LiDAR-Derived DEM with Logistic Regression

2019 ◽  
Vol 11 (13) ◽  
pp. 1592 ◽  
Author(s):  
Yong Je Kim ◽  
Boo Hyun Nam ◽  
Heejung Youn
Keyword(s):  
Logistic Regression ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Susceptibility Map ◽  
Cutoff Value ◽  
Geometric Characteristics ◽  
Probabilistic Detection ◽  
Remote Sensing Techniques ◽  
Karst Landscapes ◽  
Elevation Model

Depressions due to sinkhole formation cause significant structural damages to buildings and civil infrastructure. Traditionally, visual inspection has been used to detect sinkholes, which is a subjective way and time- and labor-consuming. Remote sensing techniques have been introduced for morphometric studies of karst landscapes. This study presents a methodology for the probabilistic detection of sinkholes using LiDAR-derived digital elevation model (DEM) data. The proposed study provides benefits associated with: (1) Detection of unreported sinkholes in rural and/or inaccessible areas, (2) automatic delineation of sinkhole boundaries, and (3) quantification of the geometric characteristics of those identified sinkholes. Among sixteen morphometric parameters, nine parameters were chosen for logistic regression, which was then employed to compute the probability of sinkhole detection; a cutoff value was back-calculated such that the sinkhole susceptibility map well predicted the reported sinkhole boundaries. According to the results of the LR model, the optimal cutoff value was calculated to be 0.13, and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.90, indicating the model is reliable for the study area. For those identified sinkholes, the geometric characteristics (e.g., depth, length, area, and volume) were computed.

Detection of antineutrophil cytoplasmic antibodies (ANCAs): a multicentre European Vasculitis Study Group (EUVAS) evaluation of the value of indirect immunofluorescence (IIF) versus antigen-specific immunoassays

2016 ◽  
Vol 76 (4) ◽  
pp. 647-653 ◽  
Author(s):  
Jan Damoiseaux ◽  
Elena Csernok ◽  
Niels Rasmussen ◽  
Frank Moosig ◽  
Pieter van Paassen ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Indirect Immunofluorescence ◽  
Wide Spectrum ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Detection Methods ◽  
Antineutrophil Cytoplasmic Antibodies ◽  
International Consensus ◽  
Large Variability ◽  
Novel Technologies

ObjectiveThis multicentre study was performed to evaluate the diagnostic accuracy of a wide spectrum of novel technologies nowadays available for detection of myeloperoxidase (MPO) and proteinase 3 (PR3)-antineutrophil cytoplasmic antibodies (ANCAs).MethodsSera (obtained at the time of diagnosis) from 251 patients with ANCA-associated vasculitis (AAV), including granulomatosis with polyangiitis and microscopic polyangiitis, and from 924 disease controls were tested for the presence of cytoplasmic pattern/perinuclear pattern and atypical ANCA (A-ANCA) by indirect immunofluorescence (IIF) (at two sites) and for the presence of PR3-ANCA and MPO-ANCA by eight different immunoassays.ResultsThe area under the curve (AUC) of the receiver operating characteristic curve to discriminate AAV from controls was 0.923 (95% CI 0.902 to 0.944) and 0.843 (95% CI 0.814 to 0.871) for the two IIF methods. For the antigen-specific immunoassays, the AUC varied between 0.936 (95% CI 0.912 to 0.960) and 0.959 (95% CI 0.941 to 0.976), except for one immunoassay for which the AUC was 0.919 (95% CI 0.892 to 0.945).ConclusionsOur comparison of various ANCA detection methods showed (i) large variability between the two IIF methods tested and (ii) a high diagnostic performance of PR3-ANCA and MPO-ANCA by immunoassay to discriminate AAV from disease controls. Consequently, dual IIF/antigen-specific immunoassay testing of each sample is not necessary for maximal diagnostic accuracy. These results indicate that the current international consensus on ANCA testing for AAV needs revision.

scholarly journals Diffusion Kurtosis MR Imaging versus Conventional Diffusion-Weighted Imaging for Distinguishing Hepatocellular Carcinoma from Benign Hepatic Nodules

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yingmei Jia ◽  
Huasong Cai ◽  
Meng Wang ◽  
Yanji Luo ◽  
Ling Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Diffusion Weighted Imaging ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Hepatocellular Adenoma ◽  
Diffusion Kurtosis Imaging ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Benign Nodules ◽  
Diffusion Kurtosis

Objectives. To assess the efficacy of diffusion kurtosis imaging (DKI) and compare DKI-derived parameters with conventional diffusion-weighted imaging (DWI) for distinguishing hepatocellular carcinoma (HCC) from benign hepatic nodules including focal nodular hyperplasia (FNH), hemangioma, and hepatocellular adenoma (HCA). Materials and Methods. 151 patients with 182 hepatic nodules (114 HCCs and 68 benign nodules including 33 FNHs, 29 hemangiomas, and 6 HCAs) were analyzed. Preoperative MRI examinations including DKI (b values: 0, 200, 500, 800, 1500, and 2000 sec/mm2) were performed, and kurtosis (K), diffusivity (D), and apparent diffusion coefficient (ADC) were calculated. The efficacy of DKI-derived parameters K, D, and ADC for distinguishing HCC from these benign nodules was analyzed. Results. ROC (receiver operating characteristic curve) analysis showed the optimal cutoff values of ADC, D, and K for identification of these benign nodules, and HCCs were 1.295 (area under the curve (AUC): 0.826; sensitivity 80.6%; specificity 70.8%), 1.787 (AUC: 0.770; sensitivity 83.6%; specificity 59.6%), and 1.002 (AUC: 0.761; sensitivity 65.5%; specificity 79.0%), respectively. Statistically significant differences were found in ADC, D, and K values between groups of HCC-FNH and HCC-hemangioma (P<0.05). There were significant differences in K and ADC values between groups of FNH-hemangioma and HCA-hemangioma (P<0.05), respectively. Using logistic regression analysis, a regression equation was obtained: LogitP=−1.982X1+1.385X3+1.948(X1: ADC; X3: K), and odds ratios (OR) were 0.138 (95% confidence interval (CI): 0.052, 0.367), and 8.996 (95% CI: 0.970, 16.460), respectively. Conclusion. Both ADC value and DKI-derived parameters K and D values have demonstrated a higher preoperative efficacy in distinguishing HCC from FNH, hemangioma, and HCA. No evidence was shown to suggest D or K value was superior to the ADC value.

Diagnostic Accuracy of Noncontrast CT in Detecting Acute Appendicitis: A Meta-analysis of Prospective Studies

2015 ◽  
Vol 81 (6) ◽  
pp. 626-629 ◽  
Author(s):  
Bing Xiong ◽  
Baishu Zhong ◽  
Zhenwei Li ◽  
Feng Zhou ◽  
Ruying Hu ◽  
...  
Keyword(s):  
Acute Appendicitis ◽  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Noncontrast Ct

The aim of the study is to evaluate the diagnostic accuracy of noncontrast CT in detecting acute appendicitis. Prospective studies in which noncontrast CT was performed to evaluate acute appendicitis were found on PubMed, EMBASE, and Cochrane Library. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were assessed. The summary receiver-operating characteristic curve was conducted and the area under the curve was calculated. Seven original studies investigating a total of 845 patients were included in this meta-analysis. The pooled sensitivity and specificity were 0.90 (95% CI: 0.86–0.92) and 0.94 (95% CI: 0.92–0.97), respectively. The pooled positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio was 12.90 (95% CI: 4.80–34.67), 0.09 (95% CI: 0.04–0.20), and 162.76 (95% CI: 31.05–853.26), respectively. The summary receiver-operating characteristic curve was symmetrical and the area under the curve was 0.97 (95% CI: 0.95–0.99). In conclusion, noncontrast CT has high diagnostic accuracy in detecting acute appendicitis, which is adequate for clinical decision making.

scholarly journals Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study

2019 ◽  
Vol 22 (3) ◽  
pp. 412-422 ◽  
Author(s):  
Niels Verburg ◽  
Thomas Koopman ◽  
Maqsood M Yaqub ◽  
Otto S Hoekstra ◽  
Adriaan A Lammertsma ◽  
...  
Keyword(s):  
Amino Acid ◽  
Diagnostic Accuracy ◽  
Area Under The Curve ◽  
Local Therapy ◽  
Preoperative Imaging ◽  
Diffuse Glioma ◽  
Characteristic Analysis ◽  
Fet Pet ◽  
Amino Acid Pet ◽  
Better Than

Abstract Background Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration. Methods We included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis. Results A total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [18F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P &lt; 0.001) and [18F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [18F]FET PET. Conclusion Combining ADC and [18F]FET PET detects glioma infiltration better than standard MRI and [18F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

scholarly journals Microstructural characterization and validation of a 3D printed axon-mimetic phantom for diffusion MRI

2020 ◽  
Author(s):  
Farah N. Mushtaha ◽  
Tristan K. Kuehn ◽  
Omar El-Deeb ◽  
Seyed A. Rohani ◽  
Luke W. Helpard ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Microstructural Characterization ◽  
Diffusion Kurtosis Imaging ◽  
Micro Ct ◽  
Variable Effect ◽  
3D Printed ◽  
The Stability ◽  
Diffusion Kurtosis ◽  
And Diffusion ◽  
Microscopy Images

AbstractPurposeTo introduce and characterize inexpensive and easily produced 3D-printed axon-mimetic (3AM) diffusion MRI (dMRI) phantoms in terms of pore geometry and diffusion kurtosis imaging (DKI) metrics.MethodsPhantoms were 3D-printed with a composite printing material that, after dissolution of the PVA, exhibits microscopic fibrous pores. Confocal microscopy and synchrotron phase contrast micro-CT imaging were performed to visualize and assess the pore sizes. dMRI scans of four identical phantoms and phantoms with varying print parameters in water were performed at 9.4T. DKI was fit to both datasets and used to assess the reproducibility between phantoms and effects of print parameters on DKI metrics. Identical scans were performed 25 and 76 days later to test their stability.ResultsSegmentation of pores in three microscopy images yielded a mean, median, and standard deviation of equivalent pore diameters of 7.57 μm, 3.51 μm, and 12.13 μm, respectively. Phantoms with identical parameters showed a low coefficient of variation (∼10%) in DKI metrics (D=1.38 ×10−3 mm2/s and K=0.52, T1= 3960 ms and T2=119 ms). Printing temperature and speed had a small effect on DKI metrics (<16%) while infill density had a larger and more variable effect (>16%). The stability analysis showed small changes over 2.5 months (<7%).Conclusion3AM phantoms can mimic the fibrous structure of axon bundles on a microscopic scale, serving as complex, anisotropic dMRI phantoms.

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