Long-Horizon Associative Learning Explains Human Sensitivity to Statistical and Network Structures in Auditory Sequences.

Networks are a useful mathematical tool for capturing the complexity of the world. In a previous behavioral study, we showed that human adults were sensitive to the high-level network structure underlying auditory sequences, even when presented with incomplete information. Their performance was best explained by a mathematical model compatible with associative learning principles, based on the integration of the transition probabilities between adjacent and nonadjacent elements with a memory decay. In the present study, we explored the neural correlates of this hypothesis via magnetoencephalography (MEG). Participants (N = 23, 16 females) passively listened to sequences of tones organized in a sparse community network structure comprising two communities. An early difference (∼150 ms) was observed in the brain responses to tone transitions with similar transition probability but occurring either within or between communities. This result implies a rapid and automatic encoding of the sequence structure. Using time-resolved decoding, we estimated the duration and overlap of the representation of each tone. The decoding performance exhibited exponential decay, resulting in a significant overlap between the representations of successive tones. Based on this extended decay profile, we estimated a long-horizon associative learning novelty index for each transition and found a correlation of this measure with the MEG signal. Overall, our study sheds light on the neural mechanisms underlying human sensitivity to network structures and highlights the potential role of Hebbian-like mechanisms in supporting learning at various temporal scales.

[Brain abscess as a complication of pulmonary manifestation of HHT]. / Hirnabszess als Komplikation bei pulmonaler Manifestation einer HHT.

A 43-year-old female patient with a brain abscess and a complicated clinical course was diagnosed with hereditary haemorrhagic telangiectasia (HHT) at the Martin Zeitz Centre for Rare Diseases in Hamburg, Germany. The brain abscess was caused by pulmonary arteriovenous malformations (AVM), a typical finding in HHT. Patients with cryptogenic brain abscess should be screened for pulmonary AVM and HHT. This case report illustrates the importance of patient history and interdisciplinary exchange in patients with a broad clinical spectrum as well as interdisciplinary treatment in the case of complications of rare diseases.

Differentiation of acute non-ST elevation myocardial infarction and acute infarct-like myocarditis by visual pattern analysis: a head-to-head comparison of different cardiac MR techniques.

OBJECTIVES: Parametric cardiac magnetic resonance (CMR) techniques have improved the diagnosis of pathologies. However, the primary tool for differentiating non-ST elevation myocardial infarction (NSTEMI) from myocarditis is still a visual assessment of conventional signal-intensity-based images. This study aimed at analyzing the ability of parametric compared to conventional techniques to visually differentiate ischemic from non-ischemic myocardial injury patterns. METHODS: Twenty NSTEMI patients, twenty infarct-like myocarditis patients, and twenty controls were examined using cine, T2-weighted CMR (T2w) and late gadolinium enhancement (LGE) imaging and T1/T2 mapping on a 1.5 T scanner. CMR images were presented in random order to two experienced fully blinded observers, who had to assign them to three categories by a visual analysis: NSTEMI, myocarditis, or healthy. RESULTS: The conventional approach (cine, T2w and LGE combined) had the best diagnostic accuracy with 92% (95%CI: 81-97) for NSTEMI and 86% (95%CI: 71-94) for myocarditis. The diagnostic accuracies using T1 maps were 88% (95%CI: 74-95) and 80% (95%CI: 62-91), 84% (95%CI: 67-93) and 74% (95%CI: 54-87) for LGE, and 83% (95%CI: 66-92) and 73% (95%CI: 53-87) for T2w. The accuracies for cine (72% (95%CI: 52-86) and 60% (95%CI: 38-78)) and T2 maps (62% (95%CI: 40-79) and 47% (95%CI: 28-68)) were significantly lower compared to the conventional approach (p < 0.001 and p < 0.0001). CONCLUSIONS: The conventional approach provided a reliable visual discrimination between NSTEMI, myocarditis, and controls. The diagnostic accuracy of a visual pattern analysis of T1 maps was not significantly inferior, whereas the diagnostic accuracy of T2 maps was not sufficient in this context. CLINICAL RELEVANCE STATEMENT: The ability of parametric compared to conventional CMR techniques to visually differentiate ischemic from non-ischemic myocardial injury patterns can avoid potentially unnecessary invasive coronary angiography and help to shorten CMR protocols and to reduce the need of gadolinium contrast agents. KEY POINTS: • A visual differentiation of ischemic from non-ischemic patterns of myocardial injury is reliably achieved by a combination of conventional CMR techniques (cine, T2-weighted and LGE imaging). • There is no significant difference in accuracies between visual pattern analysis on native T1 maps without providing quantitative values and a conventional combined approach for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls. • T2 maps do not provide a sufficient diagnostic accuracy for visual pattern analysis for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls.

DreamCoder: growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning.

Expert problem-solving is driven by powerful languages for thinking about problems and their solutions. Acquiring expertise means learning these languages-systems of concepts, alongside the skills to use them. We present DreamCoder, a system that learns to solve problems by writing programs. It builds expertise by creating domain-specific programming languages for expressing domain concepts, together with neural networks to guide the search for programs within these languages. A 'wake-sleep' learning algorithm alternately extends the language with new symbolic abstractions and trains the neural network on imagined and replayed problems. DreamCoder solves both classic inductive programming tasks and creative tasks such as drawing pictures and building scenes. It rediscovers the basics of modern functional programming, vector algebra and classical physics, including Newton's and Coulomb's laws. Concepts are built compositionally from those learned earlier, yielding multilayered symbolic representations that are interpretable and transferrable to new tasks, while still growing scalably and flexibly with experience. This article is part of a discussion meeting issue 'Cognitive artificial intelligence'.

Trend judgment as a perceptual building block of graphicacy and mathematics, across age, education, and culture.

Data plots are widely used in science, journalism and politics, since they efficiently allow to depict a large amount of information. Graphicacy, the ability to understand graphs, has thus become a fundamental cultural skill comparable to literacy or numeracy. Here, we introduce a measure of intuitive graphicacy that assesses the perceptual ability to detect a trend in noisy scatterplots ("does this graph go up or down?"). In 3943 educated participants, responses vary as a sigmoid function of the t-value that a statistician would compute to detect a significant trend. We find a minimum level of core intuitive graphicacy even in unschooled participants living in remote Namibian villages (N = 87) and 6-year-old 1st-graders who never read a graph (N = 27). The sigmoid slope that we propose as a proxy of intuitive graphicacy increases with education and tightly correlates with statistical and mathematical knowledge, showing that experience contributes to refining graphical intuitions. Our tool, publicly available online, allows to quickly evaluate and formally quantify a perceptual building block of graphicacy.

Spectral CT in Oncology. / Onkologische Bildgebung mittels Spektral-CT.

BACKGROUND: Spectral CT is gaining increasing clinical importance with multiple potential applications, including oncological imaging. Spectral CT-specific image data offers multiple advantages over conventional CT image data through various post-processing algorithms, which will be highlighted in the following review. METHODOLOGY: The purpose of this review article is to provide an overview of potential useful oncologic applications of spectral CT and to highlight specific spectral CT pitfalls. The technical background, clinical advantages of primary and follow-up spectral CT exams in oncology, and the application of appropriate spectral tools will be highlighted. RESULTS/CONCLUSIONS: Spectral CT imaging offers multiple advantages over conventional CT imaging, particularly in the field of oncology. The combination of virtual native and low monoenergetic images leads to improved detection and characterization of oncologic lesions. Iodine-map images may provide a potential imaging biomarker for assessing treatment response. KEY POINTS: · The most important spectral CT reconstructions for oncology imaging are virtual unenhanced, iodine map, and virtual monochromatic reconstructions.. · The combination of virtual unenhanced and low monoenergetic reconstructions leads to better detection and characterization of the vascularization of solid tumors.. · Iodine maps can be a surrogate parameter for tumor perfusion and potentially used as a therapy monitoring parameter.. · For radiotherapy planning, the relative electron density and the effective atomic number of a tissue can be calculated.. CITATION FORMAT: · Sauerbeck J, Adam G, Meyer M. Onkologische Bildgebung mittels Spektral-CT. Fortschr Röntgenstr 2023; 195: 21 - 29.

Cardiac magnetic resonance feature tracking global and segmental strain in acute and chronic ST-elevation myocardial infarction.

Strain is an important imaging parameter to determine myocardial deformation. This study sought to 1) assess changes in left ventricular strain and ejection fraction (LVEF) from acute to chronic ST-elevation myocardial infarction (STEMI) and 2) analyze strain as a predictor of late gadolinium enhancement (LGE). 32 patients with STEMI and 18 controls prospectively underwent cardiac magnetic resonance imaging. Patients were scanned 8 [Formula: see text] 5 days and six months after infarction (± 1.4 months). Feature tracking was performed and LVEF was calculated. LGE was determined visually and quantitatively on short-axis images and myocardial segments were grouped according to the LGE pattern (negative, non-transmural and transmural). Global strain was impaired in patients compared to controls, but improved within six months after STEMI (longitudinal strain from -14 ± 4 to -16 ± 4%, p < 0.001; radial strain from 38 ± 11 to 42 ± 13%, p = 0.006; circumferential strain from -15 ± 4 to -16 ± 4%, p = 0.023). Patients with microvascular obstruction showed especially attenuated strain results. Regional strain persisted impaired in LGE-positive segments. Circumferential strain could best distinguish between LGE-negative and -positive segments (AUC 0.73- 0.77). Strain improves within six months after STEMI, but remains impaired in LGE-positive segments. Strain may serve as an imaging biomarker to analyze myocardial viability. Especially circumferential strain could predict LGE.

A language of thought for the mental representation of geometric shapes.

In various cultures and at all spatial scales, humans produce a rich complexity of geometric shapes such as lines, circles or spirals. Here, we propose that humans possess a language of thought for geometric shapes that can produce line drawings as recursive combinations of a minimal set of geometric primitives. We present a programming language, similar to Logo, that combines discrete numbers and continuous integration to form higher-level structures based on repetition, concatenation and embedding, and we show that the simplest programs in this language generate the fundamental geometric shapes observed in human cultures. On the perceptual side, we propose that shape perception in humans involves searching for the shortest program that correctly draws the image (program induction). A consequence of this framework is that the mental difficulty of remembering a shape should depend on its minimum description length (MDL) in the proposed language. In two experiments, we show that encoding and processing of geometric shapes is well predicted by MDL. Furthermore, our hypotheses predict additive laws for the psychological complexity of repeated, concatenated or embedded shapes, which we confirm experimentally.

Symbols and mental programs: a hypothesis about human singularity.

Natural language is often seen as the single factor that explains the cognitive singularity of the human species. Instead, we propose that humans possess multiple internal languages of thought, akin to computer languages, which encode and compress structures in various domains (mathematics, music, shape…). These languages rely on cortical circuits distinct from classical language areas. Each is characterized by: (i) the discretization of a domain using a small set of symbols, and (ii) their recursive composition into mental programs that encode nested repetitions with variations. In various tasks of elementary shape or sequence perception, minimum description length in the proposed languages captures human behavior and brain activity, whereas non-human primate data are captured by simpler nonsymbolic models. Our research argues in favor of discrete symbolic models of human thought.

Analyzing the misperception of exponential growth in graphs.

Exponential growth is frequently underestimated, an error that can have a heavy social cost in the context of epidemics. To clarify its origins, we measured the human capacity (N = 521) to extrapolate linear and exponential trends in scatterplots. Four factors were manipulated: the function underlying the data (linear or exponential), the response modality (pointing or venturing a number), the scale on the y axis (linear or logarithmic), and the amount of noise in the data. While linear extrapolation was precise and largely unbiased, we observed a consistent underestimation of noisy exponential growth, present for both pointing and numerical responses. A biased ideal-observer model could explain these data as an occasional misperception of noisy exponential graphs as quadratic curves. Importantly, this underestimation bias was mitigated by participants' math knowledge, by using a logarithmic scale, and by presenting a noiseless exponential curve rather than a noisy data plot, thus suggesting concrete avenues for interventions.

Dual-Energy CT Vital Iodine Tumor Burden for Response Assessment in Patients With Metastatic GIST Undergoing TKI Therapy: Comparison With Standard CT and FDG PET/CT Criteria.

BACKGROUND. CT-based criteria for assessing the gastrointestinal stromal tumor (GIST) response to tyrosine kinase inhibitor (TKI) therapy are limited in part because tumor attenuation is influenced by treatment-related changes including hemorrhage and calcification. The iodine concentration may be less impacted by such changes. OBJECTIVE. The purpose of this study was to determine whether the dual-energy CT (DECT) vital iodine tumor burden (TB) allows improved differentiation between treatment responders and nonresponders among patients with metastatic GIST who are undergoing TKI therapy compared with established CT and PET/CT criteria. METHODS. An anthropomorphic phantom with spherical inserts mimicking GIST lesions of varying iodine concentrations and having nonenhancing central necrotic cores underwent DECT to determine a threshold iodine concentration. Forty patients (25 women and 15 men; median age, 57 years) who were treated with TKI for metastatic GIST were retrospectively evaluated. Patients underwent baseline and follow-up DECT and FDG PET/CT. Response assessment was performed using RECIST 1.1, modified Choi (mChoi) criteria, vascular tumor burden (VTB) criteria, DECT vital iodine TB criteria, and European Organization for Research and Treatment of Cancer (EORTC) PET criteria. DECT vital iodine TB criteria used the same percentage changes as RECIST 1.1 response categories. Progression-free survival was compared between responders and nonresponders for each response criterion by use of Cox proportional hazard ratios and Harrell C-indexes (i.e., concordance indexes). RESULTS. The phantom experiment identified a threshold of 0.5 mg/mL to differentiate vital from nonvital tissue. With use of the DECT vital iodine TB, median progression-free survival was significantly different between responders and nonresponders (623 vs 104 days; p < .001).. For nonresponders versus responders, the hazard ratio for disease progression for DECT vital iodine TB was 6.9 versus 7.6 for EORTC PET criteria, 3.3 for VTB criteria, 2.3 for RECIST 1.1, and 2.1 for mChoi criteria. The C-index was 0.74 for EORTC PET criteria, 0.73 for DECT vital iodine TB criteria, 0.67 for VTB criteria, 0.61 for RECIST 1.1, and 0.58 for mChoi criteria. The C-index was significantly greater for DECT vital iodine TB criteria than for RECIST 1.1 (p = .02) and mChoi criteria (p = .002), but it was not different from that for VTB and EORTC PET criteria (p > .05). CONCLUSION. DECT vital iodine TB criteria showed performance comparable to that of EORTC PET criteria and outperformed RECIST 1.1 and mChoi criteria for response assessment of metastatic GIST treated with TKI therapy. CLINICAL IMPACT. DECT vital iodine TB could help guide early management decisions in patients receiving TKI therapy.

Can radiomic analysis of a single-phase dual-energy CT improve the diagnostic accuracy of differentiating enhancing from non-enhancing small renal lesions?

BACKGROUND: The value of dual-energy computed tomography (DECT)-based radiomics in renal lesions is unknown. PURPOSE: To develop DECT-based radiomic models and assess their incremental values in comparison to conventional measurements for differentiating enhancing from non-enhancing small renal lesions. MATERIAL AND METHODS: A total of 349 patients with 519 small renal lesions (390 non-enhancing, 129 enhancing) who underwent contrast-enhanced nephrographic phase DECT examinations between June 2013 and January 2020 on multiple DECT platforms were retrospectively recruited. Cohort A included all lesions, while cohort B included Bosniak II-IV and solid enhancing renal lesions. Radiomic models were built with features selected by the least absolute shrinkage and selection operator regression (LASSO). ROC analyses were performed to compare the diagnostic accuracy among conventional and radiomic models for predicting enhancing renal lesions. RESULTS: The individual iodine concentration (IC), normalized IC, mean attenuation on 75-keV images, radiomic model of iodine images, 75-keV images and a combined model integrating all the above-mentioned features all demonstrated high AUCs for predicting renal lesion enhancement in cohort A (AUCs = 0.934-0.979) as well as in the test dataset (AUCs = 0.892-0.962) of cohort B (P values with Bonferroni correction >0.003). The AUC (0.864) of mean attenuation on 75-keV images was significantly lower than those of other models (all P values ≤0.001) except the radiomic model of 75-keV images (P = 0.038) in the training dataset of cohort B. CONCLUSION: No incremental value was found by adding radiomic and machine learning analyses to iodine images for differentiating enhancing from non-enhancing renal lesions.

CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study.

Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Do and Kambadakone in this issue.

Sensitivity to geometric shape regularity in humans and baboons: A putative signature of human singularity.

Among primates, humans are special in their ability to create and manipulate highly elaborate structures of language, mathematics, and music. Here we show that this sensitivity to abstract structure is already present in a much simpler domain: the visual perception of regular geometric shapes such as squares, rectangles, and parallelograms. We asked human subjects to detect an intruder shape among six quadrilaterals. Although the intruder was always defined by an identical amount of displacement of a single vertex, the results revealed a geometric regularity effect: detection was considerably easier when either the base shape or the intruder was a regular figure comprising right angles, parallelism, or symmetry rather than a more irregular shape. This effect was replicated in several tasks and in all human populations tested, including uneducated Himba adults and French kindergartners. Baboons, however, showed no such geometric regularity effect, even after extensive training. Baboon behavior was captured by convolutional neural networks (CNNs), but neither CNNs nor a variational autoencoder captured the human geometric regularity effect. However, a symbolic model, based on exact properties of Euclidean geometry, closely fitted human behavior. Our results indicate that the human propensity for symbolic abstraction permeates even elementary shape perception. They suggest a putative signature of human singularity and provide a challenge for nonsymbolic models of human shape perception.

Teaching a large-scale crystallography school with Zoom Webinar.

In order to address the loss of crystallographic training opportunities resulting from the cancelation of conventional schools around the world due to the COVID-19 pandemic, we have started an online crystallography school with live lectures and live Q&A using Zoom Webinar. Since we were trying to reach a large audience in a relatively short period, we have limited the school to ten 1 h lectures covering practical aspects of small molecule crystallography including data collection, data processing, and structure solution. In the school, we also covered some advanced topics that students commonly see in their work: absolute structure determination, twinning, and disorder. To round out the education, we provided lectures on macromolecular crystallography and powder diffraction. For students to practice on their own, we used freely available data reduction and structure solution software, as well as datasets with which to practice. To give students credit for course completion, we provided an online exam and an electronic certificate of completion. In this editorial, we will provide some insight into the issues of holding lectures with up to 750 students of very diverse backgrounds and review the efficacy of the school in teaching crystallography for the two cohorts of students.

"Bull's eye" appearance of hepatocellular adenomas in patients with glycogen storage disease type I - atypical magnetic resonance imaging findings: Two case reports.

BACKGROUND: Hepatocellular adenomas are rare tumors that can occur in patients with glycogen storage disease type I. CASE SUMMARY: We herein report two cases of histologically proven hepatocellular adenomas in patients with glycogen storage disease type I. Magnetic resonance imaging (MRI) was performed after bolus injection of gadoxetate disodium, a liver-specific gadolinium-based MRI contrast agent. In the present cases, some of the hepatocellular adenomas showed unexpectedly a "bull's eye" appearance on T2-weighted and post-contrast images, which was not previously described as imaging findings of hepatocellular adenomas in glycogen storage disease. A bull's eye appearance on T2-weighted images can be encountered in both benign (i.e., abscess) or malignant (i.e., epithelioid hemangioendothelioma, cholangio-carcinoma, and metastases) hepatic lesions. CONCLUSION: We present two cases of hepatocellular adenomas in patients with glycogen storage disease type 1, in which gadoxetate disodium-MRI showed atypical imaging findings for hepatocellular adenomas. At present there is no systematic study evaluating MRI findings of hepatocellular adenomas in patients with glycogen storage disease, further studies are needed to specifically investigate this issue.

Variability of quantitative measurements of metastatic liver lesions: a multi-radiation-dose-level and multi-reader comparison.

PURPOSE: To evaluate the variability of quantitative measurements of metastatic liver lesions by using a multi-radiation-dose-level and multi-reader comparison. METHODS: Twenty-three study subjects (mean age, 60 years) with 39 liver lesions who underwent a single-energy dual-source contrast-enhanced staging CT between June 2015 and December 2015 were included. CT data were reconstructed with seven different radiation dose levels (ranging from 25 to 100%) on the basis of a single CT acquisition. Four radiologists independently performed manual tumor measurements and two radiologists performed semi-automated tumor measurements. Interobserver, intraobserver, and interdose sources of variability for longest diameter and volumetric measurements were estimated and compared using Wilcoxon rank-sum tests and intraclass correlation coefficients. RESULTS: Inter- and intraobserver variabilities for manual measurements of the longest diameter were higher compared to semi-automated measurements (p < 0.001 for overall). Inter- and intraobserver variabilities of volume measurements were higher compared to the longest diameter measurement (p < 0.001 for overall). Quantitative measurements were statistically different at < 50% radiation dose levels for semi-automated measurements of the longest diameter, and at 25% radiation dose level for volumetric measurements. The variability related to radiation dose was not significantly different from the inter- and intraobserver variability for the measurements of the longest diameter. CONCLUSION: The variability related to radiation dose is comparable to the inter- and intraobserver variability for measurements of the longest diameter. Caution should be warranted in reducing radiation dose level below 50% of a conventional CT protocol due to the potentially detrimental impact on the assessment of lesion response in the liver.

Sensitivity of High-Pitch Dual-Source Computed Tomography for the Detection of Anomalous Pulmonary Venous Connection in Infants.

PURPOSE: To evaluate the sensitivity, specificity, and interobserver reliability of high-pitch dual-source computed tomography angiography (CTA) in the detection of anomalous pulmonary venous connection (APVC) in infants with congenital heart defects and to assess the associated radiation exposure. MATERIALS AND METHODS: 78 pulmonary veins in 17 consecutively enrolled patients with congenital heart defects (6 females; 11 males; median age: 6 days; range: 1-299 days) were retrospectively included in this study. All patients underwent high-pitch dual-source CTA of the chest at low tube voltages (70 kV). APVC was evaluated independently by two radiologists. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and interobserver agreement were determined. For standard of reference, one additional observer reviewed CT scans, echocardiography reports, clinical reports as well as surgical reports. In cases of disagreement the additional observer made the final decision based on all available information. RESULTS: Detection of APVC with high-pitch dual-source CTA revealed a good sensitivity (91 %) and specificity (99 %), with PPV and NPV of 98 % and 97 %. Interobserver agreement was almost perfect (Kappa = 0.84). The median DLP was 3.8 mGy*cm (IQR 3.3-4.7 mGy*cm) and the median radiation dose was 0.33 mSv (IQR 0.26-0.39 mSv). CONCLUSION: High-pitch dual-source CTA in infants with congenital heart defects allows for accurate and reliable assessment of APVC at a low radiation dose. KEY POINTS: · High-pitch dual-source CTA enables detection of anomalous pulmonary vein connection with high sensitivity in infants.. · Interrater reliability in the detection of anomalous pulmonary vein connection with high-pitch dual-source CTA is almost perfect.. · Radiation dose of high-pitch dual-source CTA in the cardiac examination of infants is low.. CITATION FORMAT: · Well L, Weinrich JM, Meyer M et al. Sensitivity of High-Pitch Dual-Source Computed Tomography for the Detection of Anomalous Pulmonary Venous Connection in Infants. Fortschr Röntgenstr 2021; 193: 551 - 558.

Hepatobiliary phase hypointensity predicts progression to hepatocellular carcinoma for intermediate-high risk observations, but not time to progression.

PURPOSE: To determine whether hepatobiliary phase hypointensity, enhancing "capsule" and size provide prognostic information regarding the risk of progression to hepatocellular carcinoma (HCC), as well as the time to progression, of intermediate to high risk observations ≥ 10 mm with arterial phase hyperenhancement (APHE). METHOD: This retrospective dual-institution study included 160 LR-3 and 26 LR-4 observations measuring more than 10 mm and having APHE in 136 patients (mean age [SD], 57 [11] years old). A composite reference standard of pathologic analysis and imaging follow-up was used. The prognostic performance of hepatobiliary phase hypointensity, enhancing "capsule" and size (cut-off: 20 mm) for the prediction of probability of progression to HCC and median time to progression to HCC was assessed and compared by means of Log-rank test, Cox-regression and Kaplan-Meier curves. RESULTS: 110 (59%) of 186 of observations progressed to HCC, 29.1% (32) progressed within 6 months, 60% (66) within 1 year and 84.5% (93) within 2 years. Hepatobiliary phase hypointensity was a significant predictor of progression to HCC (p < 0.0001, odds ratio: 20.62) but not of time to progression (p = 0.17). Median time to progression to HCC was 284 days [IQR: 266-363] and was shorter - though not significantly - for observations with enhancing "capsule" (118 days vs 301 days; p = 0.19). CONCLUSIONS: Hepatobiliary phase hypointensity is an independent predictor of progression to HCC in intermediate to high risk APHE observations ≥ 10 mm.