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OBJECTIVES: To assess the influence of peak tube voltage peak setting on adrenal adenomas (AA) attenuation on unenhanced abdominal CT. MATERIALS AND METHODS: IRB-approved retrospective observational cohort study. We included 89 patients with imaging-defined AAs with shortest diameter > 6 mm who underwent two or more unenhanced abdominal CTs using at least two different peak tube voltage settings. Two readers independently measured adenoma attenuation on different CT acquisitions by drawing a round ROI on 3 mm thick axial MPR reconstructions encompassing at least 2/3 of the lesion's surface. The mean of the values measured by the two readers was used for further analysis. Interobserver variability was assessed (Intraclass Correlation Coefficient). Attenuation values measured on 100, 110 and 140 kVp acquisitions were compared with standard 120 kVp ones (Bland-Altman analysis). RESULTS: We included 275 unenhanced abdominal CTs (3.1 ± 0.9/patient) in image analysis; 131 acquired at 120 kVp, 65 at 100 kVp, 59 at 110 kVp, and 20 at 140 kVp. 107 lesions were detected in 89 patients (1-4/patient), with a mean maximum diameter of 17 ± 6 mm. Interobserver agreement in attenuation measurement was excellent (ICC: 0.95, CI (92-97)). Median adenoma attenuation was significantly lower on 100 kVp images than on 120 kVp ones (-1 HU, IQR (-5 to 3.6), vs, 2.5 HU, IQR (-1.5 to 8.5); p < 0.001) whereas we didn't find statistically significant differences in adenoma attenuation between 110 kVp or 140 kVp and 120 kVp ones. CONCLUSION: AA attenuation is significantly lower on unenhanced CT scans acquired at 100 kVp than on those acquired at "standard" 120 kVp. CLINICAL RELEVANCE STATEMENT: AA attenuation is significantly lower at 100 kVp in comparison to 120 kVp. This might be exploited to increase unenhanced CT sensitivity in adenoma characterisation, but further studies including non-adenoma lesions are mandatory to confirm this hypothesis. KEY POINTS: CT scans are often acquired using peak tube voltage settings different from the "standard" 120 kVp. AA attenuation varies if CT scans are acquired using different tube peak voltage settings. At 100 kVp AAs show a significantly lower attenuation than at 120 kVp.

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PURPOSE: The assessment of low-contrast-details is a part of the quality control (QC) program in digital radiology. It generally consists of evaluating the threshold contrast (Cth) detectability details for different-sized inserts, appropriately located in dedicated QC test tools. This work aims to propose a simplified method, based on a statistical model approach for threshold contrast estimation, suitable for different modalities in digital radiology. METHODS: A home-madelow-contrast phantom, made of a central aluminium insert with a step-wedge, was assembled and tested. The reliability and robustness of the method were investigated for Mammography, Digital Radiography, Fluoroscopy and Angiography. Imageswere analysed using our dedicated software developed on Matlab®. TheCth is expressed in the same unit (mmAl) for all studied modalities. RESULTS: This method allows the collection of Cthinformation from different modalities and equipment by different vendors, and it could be used to define typical values. Results are summarized in detail. For 0.5 diameter detail, Cthresults are in the range of: 0.018-0.023 mmAl for 2D mammography and 0.26-0.34 mmAl DR images. For angiographic images, for 2.5 mm diameter detail, the Cths median values are 0.55, 0.4, 0.06, 0.12 mmAl for low dose fluoroscopy, coronary fluorography, cerebral and abdominal DSA, respectively. CONCLUSIONS: The statistical method proposed in this study gives a simple approach for Low-Contrast-Details assessment, and the typical values proposed can be implemented in a QA program for digital radiology modalities.

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PURPOSE: The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation. METHODS: Water phantom acquisitions were carried out on 39 scanners. DWI acquisitions (b-value = 0-200-400-600-800-1000 s/mm2) with different acquisition plans (axial, coronal, sagittal) and phase encoding directions (anterior/posterior and right/left, for the axial acquisition plan), for 3 orthogonal diffusion weighting gradient directions, were performed. For each acquisition setup, ADC values were measured in-center and off-center (6 different positions), resulting in an entire dataset of 84 × 39 = 3276 ADC values. Spatial uniformity of ADC maps was assessed by means of the percentage difference between off-center and in-center ADC values (Δ). RESULTS: No significant dependence of in-center ADC values on acquisition plan/phase encoding direction was found. Ward unsupervised clustering analysis showed 3 distinct clusters of scanners and an association between Δ-values and manufacturer/model, whereas no association between Δ-values and maximum gradient strength, slew rate or static magnetic field strength was revealed. Several acquisition setups showed significant differences among groups, indicating the introduction of different biases in ADC estimation. CONCLUSIONS: Unsupervised clustering analysis of DWI data, obtained from several scanners using an extensive acquisition protocol, allows to reveal an association between measured ADC values and manufacturer/model of scanner, as well as to identify suboptimal DWI acquisition setups for accurate ADC estimation.

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PURPOSE: To propose an MRI quality assurance procedure that can be used for routine controls and multi-centre comparison of different MR-scanners for quantitative diffusion-weighted imaging (DWI). MATERIALS AND METHODS: 44 MR-scanners with different field strengths (1 T, 1.5 T and 3 T) were included in the study. DWI acquisitions (b-value range 0-1000 s/mm2), with three different orthogonal diffusion gradient directions, were performed for each MR-scanner. All DWI acquisitions were performed by using a standard spherical plastic doped water phantom. Phantom solution ADC value and its dependence with temperature was measured using a DOSY sequence on a 600 MHz NMR spectrometer. Apparent diffusion coefficient (ADC) along each diffusion gradient direction and mean ADC were estimated, both at magnet isocentre and in six different position 50 mm away from isocentre, along positive and negative AP, RL and HF directions. RESULTS: A good agreement was found between the nominal and measured mean ADC at isocentre: more than 90% of mean ADC measurements were within 5% from the nominal value, and the highest deviation was 11.3%. Away from isocentre, the effect of the diffusion gradient direction on ADC estimation was larger than 5% in 47% of included scanners and a spatial non uniformity larger than 5% was reported in 13% of centres. CONCLUSION: ADC accuracy and spatial uniformity can vary appreciably depending on MR scanner model, sequence implementation (i.e. gradient diffusion direction) and hardware characteristics. The DWI quality assurance protocol proposed in this study can be employed in order to assess the accuracy and spatial uniformity of estimated ADC values, in single- as well as multi-centre studies.

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PURPOSE: The aim of this study was to propose and validate across various clinical scanner systems a straightforward multiparametric quality assurance procedure for proton magnetic resonance spectroscopy (MRS). METHODS: Eighteen clinical 1.5 T and 3 T scanner systems for MRS, from 16 centres and 3 different manufacturers, were enrolled in the study. A standard spherical water phantom was employed by all centres. The acquisition protocol included 3 sets of single (isotropic) voxel (size 20 mm) PRESS acquisitions with unsuppressed water signal and acquisition voxel position at isocenter as well as off-center, repeated 4/5 times within approximately 2 months. Water peak linewidth (LW) and area under the water peak (AP) were estimated. RESULTS: LW values [mean (standard deviation)] were 1.4 (1.0) Hz and 0.8 (0.3) Hz for 3 T and 1.5 T scanners, respectively. The mean (standard deviation) (across all scanners) coefficient of variation of LW and AP for different spatial positions of acquisition voxel were 43% (20%) and 11% (11%), respectively. The mean (standard deviation) phantom T2values were 1145 (50) ms and 1010 (95) ms for 1.5 T and 3 T scanners, respectively. The mean (standard deviation) (across all scanners) coefficients of variation for repeated measurements of LW, AP and T2 were 25% (20%), 10% (14%) and 5% (2%), respectively. CONCLUSIONS: We proposed a straightforward multiparametric and not time consuming quality control protocol for MRS, which can be included in routine and periodic quality assurance procedures. The protocol has been validated and proven to be feasible in a multicentre comparison study of a fairly large number of clinical 1.5 T and 3 T scanner systems.

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PURPOSE: In medical imaging systems, proper rendition of anatomy is essential in discerning normal tissue from disease. Currently, digital breast tomosynthesis (DBT) systems are evaluated using subjective evaluation of lesion visibility in uniform phantoms. This study involved the development of a new methodology to objectively measure the rendition of a 3D breast model by an anthropomorphic breast phantom, and its implementation on five clinical DBT systems of different makes and models. METHODS: A 3D, patient-based breast phantom was fabricated based on XCAT breast models. This phantom was imaged on representative breast tomosynthesis systems. The ability of tomosynthesis systems to accurately reproduce the 3D structure of the breast was assessed by computational analysis of the resultant images in terms of three groups of indices: contrast index (CI), reflective of local difference between adipose and glandular material; adipose variability index (AVI), reflective of contributions of noise and artifacts within uniform adipose regions; and contrast detectability, which describes contrast against local background variability and is described by contrast variability index (CVI), coefficient of variation (COV), contrast to adipose variability index (CAVI), and contrast to noise ratio index (CNRI). The indices were obtained by comparing the image data to the gold standard 3D distribution of breast tissue in the model. Corresponding indices were measured within variable region of interest (ROI) sizes ranging from 10 to 37 mm. The characterization was performed on five tomosynthesis systems: Fuji Aspire Crystal, GE Essential, Hologic Dimension, IMS Giotto, and Siemens Inspiration, all evaluated at a fixed dose of 1.5 mGy average glandular dose, anonymized in random order from A to E. RESULTS: Results are provided as a function of ROI size. The systems ranked orders in terms of CI with values of 7.4%, 7.0%, 6.9%, 6.4%, and 5.2% for systems A-E, respectively. This system ranking was identical for CNRI. Both CI and CNRI were constant over ROI size. The ranking was similar for CVI. The COV also changed little with ROI size and was similar across systems. For 10 mm ROIs, the average system COV was 0.7, which reduced to 0.5 with 37 mm ROIs. Two systems (A and B) exhibited highest AVI values when measured in 10 mm ROIs. This, however, was ROI-size-dependent with the three other systems (C-E) yielding higher AVI values when measured with 37 mm ROIs. Two systems (B and E) showed inferior CAVI compared to others. CONCLUSIONS: The quality of rendition tracked with differences in image appearance across systems. The findings illustrate that the anthropomorphic phantom can be used as a basis to extract quantitative values of image attributes in DBT.

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PURPOSE: To propose a magnetic resonance imaging (MRI) quality assurance procedure that can be used for multicenter comparison of different MR scanners for quantitative diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Twenty-six centers (35 MR scanners with field strengths: 1T, 1.5T, and 3T) were enrolled in the study. Two different DWI acquisition series (b-value ranges 0-1000 and 0-3000 s/mm(2) , respectively) were performed for each MR scanner. All DWI acquisitions were performed by using a cylindrical doped water phantom. Mean apparent diffusion coefficient (ADC) values as well as ADC values along each of the three main orthogonal directions of the diffusion gradients (x, y, and z) were calculated. Short-term repeatability of ADC measurement was evaluated for 26 MR scanners. RESULTS: A good agreement was found between the nominal and measured mean ADC over all the centers. More than 80% of mean ADC measurements were within 5% from the nominal value, and the highest deviation and overall standard deviation were 9.3% and 3.5%, respectively. Short-term repeatability of ADC measurement was found <2.5% for all MR scanners. CONCLUSION: A specific and widely accepted protocol for quality controls in DWI is still lacking. The DWI quality assurance protocol proposed in this study can be applied in order to assess the reliability of DWI-derived indices before tackling single- as well as multicenter studies.

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PURPOSE: To compare the diagnostic performance of T2-weighted images (T2-WI)+contrast-enhanced T1-weighted images (CE T1-WI) with the one of T2-WI+diffusion-weighted images (DWI) in the assessment of myometrial and cervical stromal infiltration by endometrial carcinoma (EC). MATERIALS AND METHODS: Institutional review board approved our retrospective study; requirement for informed consent was waived. 56 patients with histologically proven EC who underwent preoperative MRI and surgery at our Institution over a 34 months period were included. Two radiologists independently evaluated T2-WI+CE T1-WI and T2-WI+DWI of each patient. Confidence in imaging evaluation (0-3), depth of myometrial invasion (0.05) whereas both imaging sequences combinations showed the same diagnostic performance in recognizing cervical stromal infiltration (accuracy, sensitivity and specificity of 0.95, 0.98 and 0.80, p>0.05). CONCLUSION: T2-WI+DWI can reliably replace the "classical" combination T2-WI+CE T1-WI for local staging of endometrial carcinoma.

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PURPOSE: To analyse the prevalence of blunt cerebrovascular injuries (BCVIs) in multi-trauma patients by means of a post-contrast acquisition of neck vessels included into the whole-body multi-detector computed tomography (MDCT) protocol performed at admission and to correlate it with the presence of risk factors (Memphis approach). MATERIALS AND METHODS: A retrospective study was undertaken for the period January 2005 to November 2011, involving 976 multi-trauma patients. Post-contrast images of neck vessels in MDCT scan were evaluated by two experienced radiologists; carotid, vertebral and basilar arteries were rated according to the Biffl classification. The presence of clinical and/or CT risk factors for BCVI was assessed. RESULTS: BCVI were present in 32/976 (3.3 %) multi-trauma patients. Risk factors for BCVI were present in 247/976 (25.3 %) patients. The group of patients presenting risk factors showed a significantly higher prevalence of cerebrovascular injuries (8.1 %) compared with the group of patients without risk factors (1.6 %) (p = 0.009); however, 12/32 (37.5 %) patients presenting BCVI did not show any of the risk factors proposed by the Memphis group. CONCLUSION: An investigation for the presence of BCVI should be performed on all multi-trauma patients despite the absence of clinical-radiological risk factors. KEY POINTS: • BCVIs are present in 3.3 % of multi-trauma patients. • BCVIs are significantly associated to the Memphis risk factors. • Of the multi-trauma patients affected by BCVIs, 37.5 % do not show clinical-radiological risk factors. • A screening for BCVI should be performed on all multi-trauma patients.