Prospective multicenter study on personalized and optimized MDCT contrast protocols: results on liver enhancement.

OBJECTIVE: To determine a personalized and optimized contrast injection protocol for a uniform and optimal diagnostic level of liver parenchymal enhancement, in a large patient population enrolled in a multicenter study. METHODS: Six hundred ninety-two patients who underwent a standardized multi-phase liver CT examination were prospectively assigned to one contrast media (CM) protocol group: G1 (100 mL fixed volume, 37 gI); G2 (600 mgI/kg of total body weight (TBW)); G3 (750 mgI/kg of fat-free mass (FFM)), and G4 (600 mgI/kg of FFM). Change in liver parenchyma CT number between unenhanced and contrast-enhanced images was measured by two radiologists, on 3-mm pre-contrast and portal phase axial reconstructions. The enhancement histograms were compared across CM protocols, specifically according to a target diagnostic value of 50 HU. The total amount of iodine dose was also compared among protocols by median and interquartile range (IQR). The Kruskal-Wallis and Mann-Whitney U tests were used to assess significant differences (p < 0.005), as appropriate. RESULTS: A significant difference (p < 0.001) was found across the groups with liver enhancement decreasing from median over-enhanced values of 77.0 (G1), 71.3 (G2), and 65.1 (G3) to a target enhancement of 53.2 HU for G4. Enhancement IQR was progressively reduced from 26.5 HU (G1), 26.0 HU (G2), and 17.8 HU (G3) to 14.5 HU (G4). G4 showed a median iodine dose of 26.0 gI, significantly lower (p < 0.001) than G3 (33.9 gI), G2 (38.8 gI), and G1 (37 gI). CONCLUSIONS: The 600 mgI/kg FFM-based protocol enabled a diagnostically optimized liver enhancement and improved patient-to-patient enhancement uniformity, while significantly reducing iodine load. KEY POINTS: • Consistent and clinically adequate liver enhancement is observed with personalized and optimized contrast injection protocol. • Fat-free mass is an appropriate body size parameter for correlation with liver parenchymal enhancement. • Diagnostic oncology follow-up liver CT examinations may be obtained using 600 mgI/kg of FFM.

Iterative reconstructions in multiphasic CT imaging of the liver: qualitative and task-based analyses of image quality.

AIM: To evaluate the clinical benefits on image quality (IQ) of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in multiphasic liver CT compared to filtered back-projection (FBP), in patients and on phantoms using a novel task-based metric. MATERIALS AND METHODS: Image data of 65 patients who underwent a routine multiphasic liver CT during a 1-month period were reconstructed with FBP, ASIR50, ASIR80, and MBIR. IQ was assessed qualitatively by ranking the most distal hepatic artery (HA) and portal vein (PV) visible; and quantitatively by measuring contrast-to-noise ratio (CNR) of the liver parenchyma, HA and PV. IQ was compared between each reconstruction and correlated to CNR and detectability index (d') measurements computed on phantoms scanned with the same CT protocol as for patients. RESULTS: HA and PV were seen more distally on MBIR and ASIR80 compared to FBP (p≤0.001). The CNR correlated weakly between patient and phantom (r=0.76 and 0.80 for HA and PV, respectively), whereas d' correlated strongly with the division order of HA and PV (r=0.96 and 0.95, respectively). CONCLUSION: MBIR and ASIR significantly improve the IQ of multiphasic liver CT, especially through better distal detection of HA and PV, in agreement with the adapted task-based metric d' estimated on phantoms.

Comparing different methods for estimating radiation dose to the conceptus.

PURPOSE: To compare different methods available in the literature for estimating radiation dose to the conceptus (Dconceptus) against a patient-specific Monte Carlo (MC) simulation and a commercial software package (CSP). METHOD: Eight voxel models from abdominopelvic CT exams of pregnant patients were generated. Dconceptus was calculated with an MC framework including patient-specific longitudinal tube current modulation (TCM). For the same patients, dose to the uterus, Duterus, was calculated as an alternative for Dconceptus, with a CSP that uses a standard-size, non-pregnant phantom and a generic TCM curve. The percentage error between Duterus and Dconceptus was studied. Dose to the conceptus and percent error with respect to Dconceptus was also estimated for three methods in the literature. RESULTS: The percentage error ranged from -15.9% to 40.0% when comparing MC to CSP. When comparing the TCM profiles with the generic TCM profile from the CSP, differences were observed due to patient habitus and conceptus position. For the other methods, the percentage error ranged from -30.1% to 13.5% but applicability was limited. CONCLUSIONS: Estimating an accurate Dconceptus requires a patient-specific approach that the CSP investigated cannot provide. Available methods in the literature can provide a better estimation if applicable to patient-specific cases. KEY POINTS: • A patient's internal anatomy affects the dose to the conceptus. • Conceptus position has an influence on its dose estimation. • Patient anatomy and specific TCM must be considered for accurate conceptus dosimetry. • D uterus to a standard-size phantom should not be used as D conceptus .

Clinical indications and radiation doses to the conceptus associated with CT imaging in pregnancy: a retrospective study.

OBJECTIVE: To perform an internal audit at a university hospital with the aim of evaluating the number, clinical indication and operating procedure of computed tomography (CT) performed on pregnant patients and of estimating the radiation doses to the conceptus. METHODS: A retrospective review was conducted of all CT examinations performed in a single centre on pregnant patients between January 2008 and July 2013. The radiation doses to the conceptus were estimated. The results were compared with published data. RESULTS: The number of CT examinations during pregnancy increased from 3-4 per year in 2008-2011 to 11 per year in 2012. The mean estimated conceptus radiation dose was considered negligible for CT of the head and cervical spine, being less than 0.01 mGy, and for CT of the chest, less than 0.1 mGy. The estimated conceptus radiation dose from abdominopelvic CT was on average 28.7 mGy (range 6.7-60.5 mGy). CONCLUSIONS: The number of CT scans of pregnant patients increased threefold during the last few years. Most clinical indications and doses were in line with good clinical practice and literature; only in two cases the dose to the conceptus was higher than 50 mGy. KEY POINTS: • An increase in CT imaging of pregnant patients is of concern. • Clinical indications were in line with good practice. • Estimated conceptus doses were lower or similar to published data. • Internal guidelines for appropriate use of imaging during pregnancy should be established.

Effective dose and organ doses estimation taking tube current modulation into account with a commercial software package.

PURPOSE: To evaluate the effect of including tube current modulation (TCM) versus using the average mAs in estimating organ and effective dose (E) using commercial software. METHOD: Forty adult patients (24 females, 16 males) with normal BMI underwent chest/abdomen computed tomography (CT) performed with TCM at 120 kVp, reference mAs of 110 (chest) and 200 (abdomen). Doses to fully irradiated organs (breasts, lungs, stomach, liver and ovaries) and E were calculated using two versions of a dosimetry software: v.2.0, which uses the average mAs, and v.2.2, which accounts for TCM by implementing a gender-specific mAs profile. Student's t-test was used to assess statistically significant differences between organ doses calculated with the two versions. RESULTS: A statistically significant difference (p < 0.001) was found for E on chest and abdomen CT, with E being lower by 4.2% when TCM is considered. Similarly, organ doses were also significantly lower (p < 0.001): 13.7% for breasts, 7.3% for lungs, 9.1% for the liver and 8.5% for the stomach. Only the dose to the ovaries was higher with TCM (11.5%). CONCLUSION: When TCM is used, for the stylized phantom, the doses to lungs, breasts, stomach and liver decreased while the dose to the ovaries increased. KEY POINTS: • Estimated dose to the ovaries increased with TCM. • Estimated dose to lungs, breasts, stomach and liver decreased with TCM. • A unique but gender-specific mAs profile resulted in a radiation dose shift. • Even for normal size patients there is a variety in mAs profiles.

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable. MATERIALS AND METHODS: A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc., Kyoto, Japan) containing a set of 3D-printed lung nodules including six diameters (4 to 9 mm) and three morphology classes (lobular, spiculated, smooth), with an established ground truth. Images were acquired at varying radiation doses (6.04, 3.03, 1.54, 0.77, 0.41 and 0.20 mGy) and reconstructed with combinations of reconstruction kernels (soft and hard kernel) and reconstruction algorithms (ASIR-V and DLIR at low, medium and high strength). Semi-automatic volumetry measurements and subjective image quality scores recorded by five radiologists were analyzed with multiple linear regression and mixed-effect ordinal logistic regression models. RESULTS: Volumetric errors of nodules imaged with DLIR are up to 50% lower compared to ASIR-V, especially at radiation doses below 1 mGy and when reconstructed with a hard kernel. Also, across all nodule diameters and morphologies, volumetric errors are commonly lower with DLIR. Furthermore, DLIR renders higher subjective IQ, especially at the sub-mGy doses. Radiologists were up to nine times more likely to score the highest IQ-score to these images compared to those reconstructed with ASIR-V. Lung nodules with irregular margins and small diameters also had an increased likelihood (up to five times more likely) to be ascribed the best IQ scores when reconstructed with DLIR. CONCLUSION: We observed that DLIR performs as good as or even outperforms conventionally used reconstruction algorithms in terms of volumetric accuracy and subjective IQ of nodules in an anthropomorphic chest phantom. As such, DLIR potentially allows to lower the radiation dose to participants of lung cancer screening without compromising accurate measurement and characterization of lung nodules.

Sexual size dimorphism, sex ratio and the relationship between seasonality and water quality in four species of Gordiida (Nematomorpha) from Catamarca, Argentina.

A total of 687 adult nematomorphs of four species of Gordiida: Chordodes brasiliensis (393 specimens), Noteochorododes cymatium (47 specimens), N. talensis (162 specimens) and Pseudochordodes dugesi (85 specimens) were collected during a period of 1 year from El Simbolar stream, Argentina. Free-living worms were abundant during autumn and spring, but their number decreased during winter and summer. Males were shorter and significantly more abundant than females. The presence of N. cymatium, N. talensis and P. dugesi was correlated with water temperature and these species were most abundant in winter and spring. The presence of C. brasiliensis was correlated with flow rate and pH; this species was more abundant in autumn and winter. These four species are sympatric.

The EU medical device regulation: Implications for artificial intelligence-based medical device software in medical physics.

Medical device manufacturers are increasingly applying artificial intelligence (AI) to innovate their products and to improve patient outcomes. Health institutions are also developing their own algorithms, to address specific needs for which no commercial product exists. Although AI-based algorithms offer good prospects for improving patient outcomes, their wide adoption in clinical practice is still limited. The most significant barriers to the trust required for wider implementation are safety and clinical performance assurance . Qualified medical physicist experts (MPEs) play a key role in safety and performance assessment of such tools, before and during integration in clinical practice. As AI methods drive clinical decision-making, their quality should be assured and tested. Occasionally, an MPE may be also involved in the in-house development of such an AI algorithm. It is therefore important for MPEs to be well informed about the current regulatory framework for Medical Devices. The new European Medical Device Regulation (EU MDR), with date of application set for 26 of May 2021, imposes stringent requirements that need to be met before such tools can be applied in clinical practice. The objective of this paper is to give MPEs perspective on how the EU MDR affects the development of AI-based medical device software. We present our perspective regarding how to implement a regulatory roadmap, from early-stage consideration through design and development, regulatory submission, and post-market surveillance. We have further included an explanation of how to set up a compliant quality management system to ensure reliable and consistent product quality, safety, and performance .

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction.

OBJECTIVES: To compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and potential dose reduction. METHODS: Anthropomorphic phantoms (mimicking non-overweight and overweight patient), containing lesions of 6 mm in diameter with 20HU contrast, were scanned at five different dose levels (2,6,10,15,20 mGy) on a CT system, using clinical routine protocols for liver lesion detection. Images were reconstructed using ASiR-V 0% (surrogate for FBP), 60 % and TF at low, medium and high strength. Noise texture was characterized by computing a normalized Noise Power Spectrum filtered by an eye filter. The similarity against FBP texture was evaluated using peak frequency difference (PFD) and root mean square deviation (RMSD). Low contrast detectability was assessed using a channelized Hotelling observer and the area under the ROC curve (AUC) was used as figure of merit. Potential dose reduction was calculated to obtain the same AUC for TF and ASiR-V. RESULTS: FBP-like noise texture was more preserved with TF (PFD from -0.043mm-1 to -0.09mm-1, RMSD from 0.12mm-1 to 0.21mm-1) than with ASiR-V (PFD equal to 0.12 mm-1, RMSD equal to 0.53mm-1), resulting in a sharper image. AUC was always higher with TF than ASIR-V. In average, TF compared to ASiR-V, enabled a radiation dose reduction potential of 7%, 25 % and 33 % for low, medium and high strength respectively. CONCLUSION: Compared to ASIR-V, TF at high strength does not impact noise texture and maintains low contrast liver lesions detectability at significant lower dose.

PULMONARY NODULE DETECTION IN CHEST CT USING A DEEP LEARNING-BASED RECONSTRUCTION ALGORITHM.

This study's aim was to assess whether deep learning image reconstruction (DLIR) techniques are non-inferior to ASIR-V for the clinical task of pulmonary nodule detection in chest computed tomography. Up to 6 (range 3-6, mean 4.2) artificial lung nodules (diameter: 3, 5, 8 mm; density: -800, -630, +100 HU) were inserted at different locations in the Kyoto Kagaku Lungman phantom. In total, 16 configurations (10 abnormal, 6 normal) were scanned at 7.6, 3, 1.6 and 0.38 mGy CTDIvol (respectively 0, 60, 80 and 95% dose reduction). Images were reconstructed using 50% ASIR-V and a deep learning-based algorithm with low (DL-L), medium (DL-M) and high (DL-H) strength. Four chest radiologists evaluated 256 series by locating and scoring nodules on a five-point scale. No statistically significant difference was found among the reconstruction algorithms (p = 0.987, average across readers AUC: 0.555, 0.561, 0.557, 0.558 for ASIR-V, DL-L, DL-M, DL-H).

Expanding the medical physicist curricular and professional programme to include Artificial Intelligence.

PURPOSE: To provide a guideline curriculum related to Artificial Intelligence (AI), for the education and training of European Medical Physicists (MPs). MATERIALS AND METHODS: The proposed curriculum consists of two levels: Basic (introducing MPs to the pillars of knowledge, development and applications of AI, in the context of medical imaging and radiation therapy) and Advanced. Both are common to the subspecialties (diagnostic and interventional radiology, nuclear medicine, and radiation oncology). The learning outcomes of the training are presented as knowledge, skills and competences (KSC approach). RESULTS: For the Basic section, KSCs were stratified in four subsections: (1) Medical imaging analysis and AI Basics; (2) Implementation of AI applications in clinical practice; (3) Big data and enterprise imaging, and (4) Quality, Regulatory and Ethical Issues of AI processes. For the Advanced section instead, a common block was proposed to be further elaborated by each subspecialty core curriculum. The learning outcomes were also translated into a syllabus of a more traditional format, including practical applications. CONCLUSIONS: This AI curriculum is the first attempt to create a guideline expanding the current educational framework for Medical Physicists in Europe. It should be considered as a document to top the sub-specialties' curriculums and adapted by national training and regulatory bodies. The proposed educational program can be implemented via the European School of Medical Physics Expert (ESMPE) course modules and - to some extent - also by the national competent EFOMP organizations, to reach widely the medical physicist community in Europe.

Peak skin and eye lens radiation dose from brain perfusion CT: CTDIvol and Monte Carlo based estimations.

PURPOSE: To quantify the eye lens, peak skin and brain doses associated with head CT perfusion exam by means of thermoluminescent dosimeters (TLDs) measurements in a cadaver and compare them to Monte Carlo (MC) dose estimations as well as to the CTDIvol. METHOD: 18 TLDs were inserted in the brain, skin, and eye lenses of a female cadaver head, who underwent a CT brain perfusion scan using a Siemens Definition Flash. The table-toggling protocol used 80 kVp, 200 mAs, 32 × 1.2 mm collimation and 30 sequences. From the CT images, a voxel model was created. Doses were calculated with a MC framework (EGSnrc) and compared to TLD measurements. TLD measurements were also compared to the displayed CTDIvol. RESULTS: The average measured doses were: 185 mGy for the eyes lenses, 107 mGy for the skin, 172 mGy for the brain and 273 mGy for the peak skin. The reported CTDIvol of 259 mGy overestimated the averaged organ doses but not the peak skin dose. MC estimated organ doses were 147 mGy for the eyes (average), 104 mGy for the skin and 178 mGy for the brain (-20 %, -3% and 4% difference respect to the TLDs measurements, respectively). CONCLUSIONS: CTDIvol remains a conservative metric for average brain, skin and eyes lenses doses. For accurate eye lens and skin dose estimates MC simulations can be used. CTDIvol should be used with caution as it was of the same order of magnitude as the peak skin dose for this protocol and this particular CT scanner.

Implementation of patient-tailored contrast volumes based on body surface area and heart rate harmonizes contrast enhancement and reduces contrast load in small patients in portal venous phase abdominal CT.

PURPOSE: The aim of this study was to evaluate the impact of a patient-tailored contrast volume protocol on portal venous phase abdominal CT-images compared to a fixed volume protocol in daily radiological practice. METHOD: Data of 77 patients who underwent two contrast-enhanced CT-examinations were collected. The first examination was performed with a fixed contrast volume (95 ml), the follow-up examination was performed with a patient-tailored contrast volume based on patient's BSA and heart rate. The patient-tailored volume was calculated by a software application integrated in the interface of the injection pump. Two independent radiologists assessed subjective and objective image quality. Differences in enhancement and contrast volumes between both protocols were analysed. RESULTS: Despite a significant contrast volume reduction in women and in patients with low to normal BMI, enhancement was more consistent over different BMI-categories in the patient-tailored contrast volume protocol and there was no significant difference in subjective image quality between both injection protocols. CONCLUSIONS: A patient-tailored contrast volume protocol based on BSA and heart rate can be considered in daily radiological practice to decrease contrast volumes in women and in low to normal BMI patients and to achieve more consistent contrast enhancement across different BMI-categories in venous phase abdominal CT.

A quantitative method for evaluating the detectability of lesions in digital mammography.

This study presents a quantitative method for evaluating the detectability of microcalcifications in digital mammography. Four hundred and twenty microcalcifications (with various morphology, size and contrast), simulated with a previously validated method, were used for the creation of image datasets. Lesions were inserted into 163 regions of interests of 59 selected raw digital mammograms with various anatomical backgrounds and acquired with a Siemens Novation DR. After processing, these composite images were scored by experienced radiologists, who located multiple simulated lesions and rated them under conditions of free-search. For statistical analysis, free-response receiver-operating characteristic curves are plotted; the use of jackknife free-response receiver-operating characteristic method has also been investigated. The main advantage of this methodology is that the exact number of inserted microcalcifications is well known and that the lesions are fully characterised in terms of pathology, size, morphology and peak contrast. A first application has been the evaluation of the effect of anatomical background on microcalcifications detection. Preliminary findings in this study indicate that this method may be a promising tool to evaluate factors that have an influence on the detectability of lesions, such as the clinical processing or the viewing conditions.

Image quality measurements and metrics in full field digital mammography: an overview.

This paper gives an overview of test procedures developed to assess the performance of full field digital mammography systems. We make a distinction between tests of the individual components of the imaging chain and global system tests. Most tests are not yet fully standardised. Where possible, we illustrate the test methodologies on a selenium flat-panel system.

Scanning electron microscopy of Spinochordodes tellinii (Camerano, 1888), (Gordiacea, Nematomorpha).

There are many species of Nematomorpha which are deficiently described and therefore pose doubts about their actual taxonomic position. This is the case with Spinochordodes tellinii (Comerano, 1888), which was transferred to four different genera and has been recently considered as species incertae sedis. A female of Spinochordodes tellinii is redescribed in this work under light microscopy and Scanning Electron Microscopy. Cuticle details, shapes and areolar distribution and the features as well as the location of spiniform structures are analysed. The systematic position is discussed.

Comparison of measured and estimated maximum skin doses during CT fluoroscopy lung biopsies.

PURPOSE: To measure patient-specific maximum skin dose (MSD) associated with CT fluoroscopy (CTF) lung biopsies and to compare measured MSD with the MSD estimated from phantom measurements, as well as with the CTDIvol of patient examinations. METHODS: Data from 50 patients with lung lesions who underwent a CT fluoroscopy-guided biopsy were collected. The CT protocol consisted of a low-kilovoltage (80 kV) protocol used in combination with an algorithm for dose reduction to the radiology staff during the interventional procedure, HandCare (HC). MSD was assessed during each intervention using EBT2 gafchromic films positioned on patient skin. Lesion size, position, total fluoroscopy time, and patient-effective diameter were registered for each patient. Dose rates were also estimated at the surface of a normal-size anthropomorphic thorax phantom using a 10 cm pencil ionization chamber placed at every 30°, for a full rotation, with and without HC. Measured MSD was compared with MSD values estimated from the phantom measurements and with the cumulative CTDIvol of the procedure. RESULTS: The median measured MSD was 141 mGy (range 38-410 mGy) while the median cumulative CTDIvol was 72 mGy (range 24-262 mGy). The ratio between the MSD estimated from phantom measurements and the measured MSD was 0.87 (range 0.12-4.1) on average. In 72% of cases the estimated MSD underestimated the measured MSD, while in 28% of the cases it overestimated it. The same trend was observed for the ratio of cumulative CTDIvol and measured MSD. No trend was observed as a function of patient size. CONCLUSIONS: On average, estimated MSD from dose rate measurements on phantom as well as from CTDIvol of patient examinations underestimates the measured value of MSD. This can be attributed to deviations of the patient's body habitus from the standard phantom size and to patient positioning in the gantry during the procedure.

Comparison of visual grading and free-response ROC analyses for assessment of image-processing algorithms in digital mammography.

OBJECTIVE: To compare two methods for assessment of image-processing algorithms in digital mammography: free-response receiver operating characteristic (FROC) for the specific task of microcalcification detection and visual grading analysis (VGA). METHODS: The FROC study was conducted prior to the VGA study reported here. 200 raw data files of low breast density (Breast Imaging-Reporting and Data System I-II) mammograms (Novation DR, Siemens, Germany)-100 of which abnormal-were processed by four image-processing algorithms: Raffaello (IMS, Bologna, Italy), Sigmoid (Sectra, Linköping, Sweden), and OpView v. 2 and v. 1 (Siemens, Erlangen, Germany). Four radiologists assessed the mammograms for the detection of microcalcifications. 8 months after the FROC study, a subset (200) of the 800 images was reinterpreted by the same radiologists, using the VGA methodology in a side-by-side approach. The VGA grading was based on noise, saturation, contrast, sharpness and confidence with the image in terms of normal structures. Ordinal logistic regression was applied; OpView v. 1 was the reference processing algorithm. RESULTS: In the FROC study all algorithms performed better than OpView v. 1. From the current VGA study and for confidence with the image, Sigmoid and Raffaello were significantly worse (p<0.001) than OpView v. 1; OpView v. 2 was significantly better (p=0.01). For the image quality criteria, results were mixed; Raffaello and Sigmoid for example were better than OpView v. 1 for sharpness and contrast (although not always significantly). CONCLUSION: VGA and FROC discordant results should be attributed to the different clinical task addressed. ADVANCES IN KNOWLEDGE: The method to use for image-processing assessment depends on the clinical task tested.

Consistency of methods for analysing location-specific data.

Although the receiver operating characteristic (ROC) method is the acknowledged gold-standard for imaging system assessment, it ignores localisation information and differentiation between multiple abnormalities per case. As the free-response ROC (FROC) method uses localisation information and more closely resembles the clinical reporting process, it is being increasingly used. A number of methods have been proposed to analyse the data that result from an FROC study: jackknife alternative FROC (JAFROC) and a variant termed JAFROC1, initial detection and candidate analysis (IDCA) and ROC analysis via the reduction of the multiple ratings on a case to a single rating. The focus of this paper was to compare JAFROC1, IDCA and the ROC analysis methods using a clinical FROC human data set. All methods agreed on the ordering of the modalities and all yielded statistically significant differences of the figures-of-merit, i.e. p < 0.05. Both IDCA and JAFROC1 yielded much smaller p-values than ROC. The results are consistent with a recent simulation-based validation study comparing these and other methods. In conclusion, IDCA or JAFROC1 analysis of FROC human data may be superior at detecting modality differences than ROC analysis.