Nadja Kadom

Deep Learning in Radiology

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care.

Using the American College of Radiology Dose Index Registry to Evaluate Practice Patterns and Radiation Dose Estimates of Pediatric Body CT

OBJECTIVE Imaging registries afford opportunities to study large, heterogeneous populations. The purpose of this study was to examine the American College of Radiology CT Dose Index Registry (DIR) for dose-related demographics and metrics of common pediatric body CT examinations. MATERIALS AND METHODS Single-phase CT examinations of the abdomen and pelvis and chest submitted to the DIR over a 5-year period (July 2011-June 2016) were evaluated (head CT frequency was also collected). CT examinations were stratified into five age groups, and examination frequency was determined across age and sex. Standard dose indexes (volume CT dose index, dose-length product, and size-specific dose estimate) were categorized by body part and age. Contributions to the DIR were also categorized by region and practice type. RESULTS Over the study period 411,655 single-phase pediatric examinations of the abdomen and pelvis, chest, and head, constituting 5.7% of the total (adult and pediatric) examinations, were submitted to the DIR. Head CT was the most common examination across all age groups. The majority of all scan types were performed for patients in the second decade of life. Dose increased for all scan types as age increased; the dose for abdominopelvic CT was the highest in each age group. Even though the DIR was queried for single-phase examinations only, as many as 32.4% of studies contained multiple irradiation events. When these additional scans were included, the volume CT dose index for each scan type increased. Among the studies in the DIR, 99.8% came from institutions within the United States. Community practices and those that specialize in pediatrics were nearly equally represented. CONCLUSION The DIR provides valuable information about practice patterns and dose trends for pediatric CT and may assist in establishing diagnostic reference levels in the pediatric population.

Radiology Research in Quality and Safety: Current Trends and Future Needs

Promoting quality and safety research is now essential for radiology as reimbursement is increasingly tied to measures of quality, patient safety, efficiency, and appropriateness of imaging. This article provides an overview of key features necessary to promote successful quality improvement efforts in radiology. Emphasis is given to current trends and future opportunities for directing research. Establishing and maintaining a culture of safety is paramount to organizations wishing to improve patient care. The correct culture must be in place to support quality initiatives and create accountability for patient care. Focused educational curricula are necessary to teach quality and safety-related skills and behaviors to trainees, staff members, and physicians. The increasingly complex healthcare landscape requires that organizations build effective data infrastructures to support quality and safety research. Incident reporting systems designed specifically for medical imaging will benefit quality improvement initiatives by identifying and learning from system errors, enhancing knowledge about safety, and creating safer systems through the implementation of standardized practices and standards. Finally, validated performance measures must be developed to accurately reflect the value of the care we provide for our patients and referring providers. Common metrics used in radiology are reviewed with focus on current and future opportunities for investigation.

Pediatric Accidental Traumatic Brain Injury: Evidence-Based Emergency Imaging

There are opportunities for avoiding unnecessary imaging in children who experienced accidental head trauma. This chapter reviews clinical decision rules that can inform when imaging should be performed or can be avoided. Advanced imaging techniques and their current role in the evaluation of pediatric brain injury are also reviewed.

Content-oriented sparse representation (COSR) for CT denoising with preservation of texture and edge

PURPOSE Denoising has been a challenging research subject in medical imaging, since the suppression of noise conflicts with the preservation of texture and edges. To address this challenge, we develop a content-oriented sparse representation (COSR) method for denoising in computed tomography (CT). METHODS An image is segmented into a number of content areas and each of them consists of similar material. Having been ex-painted, each content area is sparsely coded using the dictionary learnt from patches extracted from the corresponding content area. By constraining sparsity, noise is suppressed and the final image is formed by aggregating all denoised content areas. The performance of COSR method is examined with images simulated by computer and generated by multidetector row CT (MDCT), cone beam CT (CBCT), and micro-CT, in which water phantom, anthropomorphic phantom, a human subject, and a small animal are engaged, using the figures of merit, such as standard division (SD), contrast to noise ratio (CNR), and thresholded edge keeping index (EKIth ) and structural similarity index (SSIM). In addition, the optimization of performance by parameter tuning is also investigated. RESULTS Quantitatively gauged by metrics of noise, EKIth and SSIM, the performance evaluation shows that the proposed COSR method is effective in denoising (>50% reduction in noise) while it outperforms the conventional sparse representation method in preservation of texture and edge by ~20% (gauged by SSIM). It has also been shown that the COSR method is tolerable to inaccuracy in content area segmentation and variation in dictionary learning. Moreover, the computational efficiency of COSR can be substantially improved using prelearnt dictionaries. CONCLUSIONS The COSR method would find its utility in clinical and preclinical applications, such as low-dose CT, image segmentation, registration, and computer-aided diagnosis. The proposal of COSR denoising is of innovation and significance in the theory and practice of denoising in medical imaging. A demonstration code package is available at https://github.com/xiehq/COSR.

Content-oriented sparse representation (COSR) denoising in CT images

Denoising has been a challenging research subject in medical imaging in general and in CT imaging in particular, because the suppression of noise conflicts with the preservation of texture and edges. The purpose of this paper is to develop and evaluate a content-oriented sparse representation (COSR) denoising method in CT to effectively address this challenge. A CT image is firstly segmented by thresholding into several content-areas with similar materials, such as the air, soft tissues and bones. After being ex-painted smoothly outside it boundary, each content-area is sparsely coded by an atom from the dictionary that learnt from the image patches extracted from the corresponding content-area. The regenerated content-areas are finally aggregated to form the denoised CT image. The efficiency of image denoising and the ability of preserving texture and edges are demonstrated with a cylinder water phantom generated by simulation. The denoising performance of the proposed method is further tested with images of a pediatric head phantom and an anonymous pediatric patient that scanned by a state-of-the-art CT scanner, which shows that the proposed COSR denoising method can effectively preserve texture and edges while reducing noise. It is believed that this method would find its utility in extensive clinical and pre-clinical applications, such as dedicated and low dose CT, image segmentation and registration, and computer aided diagnosis (CAD) etc.

ACR Appropriateness Criteria® Headache–Child

Headaches in children are not uncommon and have various causes. Proper neuroimaging of these children is very specific to the headache type. Care must be taken to choose and perform the most appropriate initial imaging examination in order to maximize the ability to properly determine the cause with minimum risk to the child. This evidence-based report discusses the different headache types in children and provides appropriate guidelines for imaging these children. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Think A-Head Campaign of Image Gently: Shared Decision-Making in Pediatric Head Trauma

When children present with head trauma, as with any imaging examination, it is necessary to consider the risks, costs, and benefits of testing. In many instances of pediatric head trauma, imaging studies are used for “confirming” or “excluding” certain diagnoses.[1][1] However, imaging tests

Noncontrast Head CT in Children: National Variation in Radiation Dose Indices in the United States

BACKGROUND AND PURPOSE: Radiologists should manage the radiation dose for pediatric patients to maintain reasonable diagnostic confidence. We assessed the variation in estimated radiation dose indices for pediatric noncontrast head CT in the United States. MATERIALS AND METHODS: Radiation dose indices for single-phase noncontrast head CT examinations in patients 18 years of age and younger were retrospectively reviewed between July 2011 and June 2016 using the American College of Radiology CT Dose Index Registry. We used the reported volume CT dose index stratified by patient demographics and imaging facility characteristics. RESULTS: The registry included 295,296 single-phase pediatric noncontrast head CT studies from 1571 facilities (56% in male patients and 53% in children older than 10 years of age). The median volume CT dose index was 33 mGy (interquartile range = 22–47 mGy). The volume CT dose index increased as age increased. The volume CT dose index was lower in childrens hospitals (median, 26 mGy) versus academic hospitals (median, 32 mGy) and community hospitals (median, 40 mGy). There was a lower volume CT dose index in level I and II trauma centers (median, 27 and 32 mGy, respectively) versus nontrauma centers (median, 40 mGy) and facilities in metropolitan locations (median, 30 mGy) versus those in suburban and rural locations (median, 41 mGy). CONCLUSIONS: Considerable variation in the radiation dose index for pediatric head CT exists. Median dose indices and practice variations at pediatric facilities were both lower compared with other practice settings. Decreasing dose variability through proper management of CT parameters in pediatric populations using benchmarks generated by data from registries can potentially decrease population exposure to ionizing radiation.

Occipital intraosseous dermoid cyst with restricted diffusion on magnetic resonance imaging in a child

A 4-year-old girl presented repeatedly with a complicated occipital mass, which was erroneously treated as a pyogenic granuloma. Imaging performed before a planned surgical resection detected an underlying intraoccipital dermoid with a sinus tract to the skin surface and extension into the posterior fossa. This case highlights the value of high-resolution computed tomography imaging for depiction of anatomic details and the value of magnetic resonance imaging for differential diagnosis and surgical management. A comprehensive literature review of intraosseous dermoid cyst and detailed discussion of the differential diagnoses are provided.