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Society for Pediatric Radiology – Poster Archive

Showing 6 Abstracts.

Jen Aaron,  Iskander Paul,  Ghahremani Shahnaz

Final Pr. ID: Poster #: CR-079

Case Report:
A 14 year-old previously healthy male presented to the emergency department with weakness, fever, diarrhea, lateral right eye deviation and transient vision loss, following a week of headaches and dizziness. The symptoms began following a recent camping trip to Yosemite National Park with friends, where distant contact with squirrels and several bug bites were noted. The initial physical examination revealed additional photophobia, limited neck flexion secondary to pain, and a raised, non-tender soft tissue mass over the anterior right shin. Soon after admission, the patient developed pain in the right hip and left leg and significant lower extremity weakness. A chest X-ray demonstrated left lower lobe consolidation, a left upper lobe lung nodule, and a right upper lobe lung nodule. MRI showed multifocal osteomyelitis and multiple intraosseous, intramuscular and soft tissue abscesses. Contrast-enhanced CT angiogram demonstrated septic emboli, scarring, and atelectasis within the left lower lung with a small hydropneumothorax. Lucent lesions were also noticed in the T3-T6 vertebral bodies with increased prominence of the paravertebral soft tissue.

A lumbar puncture was found consistent with bacterial meningitis. A blood culture, CSF culture, and culture of abscess fluid from the right hip were all found to be PCR positive for Yersinia pestis, and the patient was placed on a treatment regimen of ciprofloxacin, gentamicin, and tetracycline.

Plague, colloquial known as the Black Death, is a zoonosis caused by the gram-negative bacterium Yersinia pestis and endemic to the Western United States and developing countries. In the modern day, plague is typically found in infected rodents and spread to humans through fleas. Three forms of plague are reported in humans: bubonic, septicemic, and pneumonic. Our patient’s presented primary septicemic plague complicated by secondary pneumonia, meningitis, and osteomyelitis. Notably, Yersinia osteomyelitis has been reported only once in the historical literature, and was likely underappreciated before the advent of MRI. This case presentation will highlight the unique imaging manifestations of the patient’s disseminated disease.
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Authors:  Jen Aaron , Iskander Paul , Ghahremani Shahnaz

Keywords:  plague, osteomyelitis, pneumonia, meningitis, sepsis

Hoeksema Peter,  Betz Lisa,  Ledbetter Karyn

Final Pr. ID: Paper #: 038

Small airways disease (SAD) is a common pathology seen in pediatric patients. In suspected cases of SAD/RSV/bronchiolitis, chest radiographs are often ordered to diagnose disease and to rule out other conditions, such as bacterial pneumonia. While SAD and pneumonia have unique radiographic features, the threshold to diagnose such findings may depend on radiologist experience and training background. The purpose of this study is to investigate intra-radiologist precision and accuracy in diagnosing normal, SAD, and bacterial pneumonia on pediatric chest radiography. Read More

Authors:  Hoeksema Peter , Betz Lisa , Ledbetter Karyn

Keywords:  Pneumonia

Li Jason,  Betke Margaret,  Gill Christopher,  Thompson Russell,  Wang Kaihong,  Etter Lauren,  Camelo Ingrid,  Chang Hailey,  Setty Bindu,  Castro Ilse,  Pieciak Rachel

Final Pr. ID: Poster #: SCI-015

Point of Care Lung ultrasound has proven in multiple studies to be superior to CXR to diagnose pneumonia in children especially in limited resource settings. This non-radiating, portable and adaptable technique, brings an opportunity to detect pneumonia with higher accuracy than CXR. Ultrasound imaging interpretation is challenging. To deal with this complexity, we created a "brightness profiles" data reduction technique to identify specific anatomical structures identified by lung ultrasound using artificial intelligence. We use this technique to demonstrate how data reduction can help identify common anatomical landmarks and abnormal findings, and aid in the interpretation of ultrasound diagnosed pediatric pneumonia. Read More

Authors:  Li Jason , Betke Margaret , Gill Christopher , Thompson Russell , Wang Kaihong , Etter Lauren , Camelo Ingrid , Chang Hailey , Setty Bindu , Castro Ilse , Pieciak Rachel

Keywords:  Artificial intelligence, pneumonia, ultrasound

Hook Marcus,  Barrera Ambika,  Biko David,  Dennis Rebecca,  Rapp Jordan

Final Pr. ID: Paper #: 029

Vaping associated pulmonary injury (VAPI) has recently received national attention as an epidemic resulting in cases of significant morbidity and mortality from electronic cigarette use. The purpose is to present the clinical and imaging findings in adolescents with pulmonary symptoms from suspected VAPI. Read More

Authors:  Hook Marcus , Barrera Ambika , Biko David , Dennis Rebecca , Rapp Jordan

Keywords:  Vaping, Lung injury, Pneumonia

Chang Hailey,  Gill Christopher,  Setty Bindu,  Castro-aragon Ilse,  Camelo Ingrid,  Etter Lauren,  Pieciak Rachel,  Thompson Russell,  Wang Kaihong,  Li Jason

Final Pr. ID: Poster #: EDU-060

Pneumonia is a leading cause of pediatric morbidity and mortality worldwide. In 2017, 15% of under-5 mortalities were due to pneumonia. Children in sub-Saharan Africa are disproportionately affected. Chest radiography (CXR) is currently the reference standard for imaging diagnosis of pediatric lung diseases. However, radiographic equipment is not available in many clinical settings, particularly in low and middle-income countries. In these scenarios, point-of-care lung ultrasound (LUS) is much more readily accessible. Thus, it is important to understand the US appearance of both interstitial and bacterial pneumonias and how they correlate with CXR findings.

In this pictorial essay, we will discuss the US appearance of common lower respiratory tract infections such as RSV, COVID-19, and bacterial pneumonia using images obtained from patients ages 1 month to 5 years with symptomatic respiratory illness in Lusaka, Zambia. All images were obtained by a technologist with a Butterfly portable ultrasound probe connected to an iPad. Images were obtained in the anterior, lateral, and posterior lung fields bilaterally. US images will be correlated with CXR findings.

The following examples of LUS findings will be discussed: 1) Normal LUS: The pleural line is thin and smooth with normal lung sliding. A-lines are present, and B-lines are limited to less than three in each field of view. 2) Abnormal B-lines: When three or more B-lines are seen in a single field of view, there is an abnormal increase in interstitial fluid. A focal B line is an abnormally thickened B-line and likely represents a confluence of multiple B-lines. 3) White lung: Confluent echogenicity involving two or more rib interspaces. 4) Pleural irregularity: The pleural line is jagged or fragmented and may also appear thickened with small sub-centimeter subpleural consolidations. 5) Pleural effusion: Well-defined fluid above the diaphragm. In a simple transudative effusion, the fluid appears anechoic. In a complex exudative effusion, the fluid may have loculations, septations, and/or internal echogenic floating debris. 6) Consolidation: Poorly defined, tissue-like region within the lung, usually seen adjacent to the pleural line. 7) Lung necrosis or abscess: Well-defined, hypoechoic region within an area of consolidation. By understanding the US appearance of lung pathologies, LUS can be used to diagnose pediatric lung diseases in areas where CXRs are currently unavailable.
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Authors:  Chang Hailey , Gill Christopher , Setty Bindu , Castro-aragon Ilse , Camelo Ingrid , Etter Lauren , Pieciak Rachel , Thompson Russell , Wang Kaihong , Li Jason

Keywords:  Lung Ultrasound, RSV, Pneumonia

Thompson Russell,  Pieciak Rachel,  Gill Christopher,  Li Jason,  Wang Kaihong,  Etter Lauren,  Camelo Ingrid,  Castro-aragon Ilse,  Setty Bindu,  Chang Hailey,  Betke Margaret

Final Pr. ID: Poster #: SCI-008

CXR is the most common imaging method to diagnose pneumonia in children in limited-resource settings. There is a need to simplify and expedite its interpretation. By using a machine learning model to first classify and interpret the pneumonia images and then incorporate those characteristic imaging findings patterns into a simulated mobile app, health care workers can use their mobile devices to interpret those findings based on preloaded images built into their mobile devices corresponding to pneumonia. Read More

Authors:  Thompson Russell , Pieciak Rachel , Gill Christopher , Li Jason , Wang Kaihong , Etter Lauren , Camelo Ingrid , Castro-aragon Ilse , Setty Bindu , Chang Hailey , Betke Margaret

Keywords:  Artificial intelligence, pneumonia, CXR