Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

OBJECTIVE: The purpose of this article is to highlight best practices for writing and reviewing articles on artificial intelligence for medical image analysis. CONCLUSION: Artificial intelligence is in the early phases of application to medical imaging, and patient safety demands a commitment to sound methods and avoidance of rhetorical and overly optimistic claims. Adherence to best practices should elevate the quality of articles submitted to and published by clinical journals.

Quantitative assessment of solid renal masses by contrast-enhanced ultrasound with time-intensity curves: how we do it.

PURPOSE: To discuss the evaluation of the enhancement curve over time of the major renal cell carcinoma (RCC) subtypes, oncocytoma, and lipid-poor angiomyolipoma, to aid in the preoperative differentiation of these entities. Differentiation of these lesions is important, given the different prognoses of the subtypes, as well as the desire to avoid resecting benign lesions. METHODS: We discuss findings from CT, MR, and US, but with a special emphasis on contrast-enhanced ultrasound (CEUS). CEUS technique is described, as well as time-intensity curve analysis. RESULTS: Examples of each of the major RCC subtypes (clear cell, papillary, and chromophobe) are shown, as well as examples of oncocytoma and lipid-poor angiomyolipoma. For each lesion, the time-intensity curve of enhancement on CEUS is reviewed, and correlated with the enhancement curve over time reported for multiphase CT and MR. CONCLUSIONS: Preoperative differentiation of the most common solid renal masses is important, and the time-intensity curves of these lesions show some distinguishing features that can aid in this differentiation. The use of CEUS is increasing, and as a modality it is especially well suited to the evaluation of the time-intensity curve.

Automated pediatric abdominal effective diameter measurements versus age-predicted body size for normalization of CT dose.

There has been increasing interest in adjusting CT radiation dose data for patient body size. A method for automated computation of the abdominal effective diameter of a patient from a CT image has previously only been tested in adult patients. In this work, we tested the method on a set of 128 pediatric patients aged 0.8 to 12.9 years (average 8.0 years, SD = 3.7 years) who had CT abdomen/pelvis exams performed on a Toshiba Aquilion 64 scanner. For this set of patients, age-predicted abdominal effective diameter extrapolated based on data from the International Commission on Radiation Units and Measurements was a relatively poor predictor of measured effective diameter. The mean absolute percentage error between the CTDI normalization coefficient calculated from a manually measured effective diameter and the coefficient determined by age-predicted effective diameter was 12.3 % with respect to a 32 cm phantom (range 0.0-52.8 %, SD 8.7 %) and 12.9 % with respect to a 16 cm phantom (range 0.0-56.4 %, SD 9.2 %). In contrast, there is a close correspondence between the automated and manually measured patient effective diameters, with a mean absolute error of 0.6 cm (error range 0.2-1.3 cm). This correspondence translates into a high degree of correspondence between normalization coefficients determined by automated and manual measurements; the mean absolute percentage error was 2.1 % with respect to a 32 cm phantom (range 0.0-8.1 %, SD = 1.4 %) and 2.3 % with respect to a 16 cm phantom (range 0.0-9.3 %, SD = 1.6 %).

What the radiologist needs to know about urolithiasis: part 1--pathogenesis, types, assessment, and variant anatomy.

OBJECTIVE: This article reviews types of urinary calculi and their imaging appearances, presents direct and secondary imaging findings of urolithiasis, and provides an overview of treatment methods. Pertinent imaging findings that impact clinical management are highlighted. The implications of complex or variant genitourinary anatomy are reviewed. We outline a standard format for the reporting of urolithiasis to facilitate informed clinical management decisions. CONCLUSION: Unenhanced CT is the preferred examination for evaluation of urolithiasis because of its availability, ease of performance, and high sensitivity. An awareness of the important imaging findings to report allows appropriate and efficient therapy.