Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition. The approach presented here is based on the analysis of brightness distribution patterns present in rectangular segments (here called "characteristic vectors") from the ultrasound digital images. In a first step we identified and eliminated the skin and subcutaneous tissue (fat and muscle) in lung ultrasound frames, and the "characteristic vectors"were analyzed using standard neural networks using artificial intelligence methods. We analyzed 60 lung ultrasound frames corresponding to 21 children under age 5 years (15 children with confirmed pneumonia by clinical examination and X-rays, and 6 children with no pulmonary disease) from a hospital based population in Lima, Peru. Lung ultrasound images were obtained using an Ultrasonix ultrasound device. A total of 1450 positive (pneumonia) and 1605 negative (normal lung) vectors were analyzed with standard neural networks, and used to create an algorithm to differentiate lung infiltrates from healthy lung. A neural network was trained using the algorithm and it was able to correctly identify pneumonia infiltrates, with 90.9% sensitivity and 100% specificity. This approach may be used to develop operator-independent computer algorithms for pneumonia diagnosis using ultrasound in young children.

Automatic pneumonia detection based on ultrasound video analysis.

Pneumonia is a disease which causes high mortality in children under five years old, particularly in developing countries. This paper proposes a novel application of ultrasound video analysis for the detection of pneumonia. This application is based on the processing of small video chunks, in which an image processing algorithm analyzes each frame to get some overall video statistics. Then, based on these quantities, the likeness of presence of pneumonia in the video is determined. The algorithm exploits different geometrical properties of typical anatomical and pathological features that commonly appear in lung sonography and which are already clinically typified in the literature. Our technique has been tested on different transverse thoracic scanning protocols and probe's maneuvers, thus, under a variety of clinical and usage protocols. Then, it can be targeted towards screening applications. We present encouraging results (AUC measure between 0.7851 and 0.9177) based on the analysis of 346 videos with an average duration of eight seconds. The analyzed videos were taken from children who were between three and five years old. Finally, our algorithm can be used directly as a classifier, but we detail how its performance may be enhanced if used as a first stage of a larger pipeline of other complementary pneumonia detection processes.

Developing a reference of normal lung sounds in healthy Peruvian children.

PURPOSE: Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. METHODS: 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81%) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. RESULTS: Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47% were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. CONCLUSIONS: Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments.

Computerised lung sound analysis to improve the specificity of paediatric pneumonia diagnosis in resource-poor settings: protocol and methods for an observational study.

INTRODUCTION: WHO case management algorithm for paediatric pneumonia relies solely on symptoms of shortness of breath or cough and tachypnoea for treatment and has poor diagnostic specificity, tends to increase antibiotic resistance. Alternatives, including oxygen saturation measurement, chest ultrasound and chest auscultation, exist but with potential disadvantages. Electronic auscultation has potential for improved detection of paediatric pneumonia but has yet to be standardised. The authors aim to investigate the use of electronic auscultation to improve the specificity of the current WHO algorithm in developing countries. METHODS: This study is designed to test the hypothesis that pulmonary pathology can be differentiated from normal using computerised lung sound analysis (CLSA). The authors will record lung sounds from 600 children aged ≤5 years, 100 each with consolidative pneumonia, diffuse interstitial pneumonia, asthma, bronchiolitis, upper respiratory infections and normal lungs at a children's hospital in Lima, Peru. The authors will compare CLSA with the WHO algorithm and other detection approaches, including physical exam findings, chest ultrasound and microbiologic testing to construct an improved algorithm for pneumonia diagnosis. DISCUSSION: This study will develop standardised methods for electronic auscultation and chest ultrasound and compare their utility for detection of pneumonia to standard approaches. Utilising signal processing techniques, the authors aim to characterise lung sounds and through machine learning, develop a classification system to distinguish pathologic sounds. Data will allow a better understanding of the benefits and limitations of novel diagnostic techniques in paediatric pneumonia.

Manual de tratamiento de la diarrea en niños

La reducción de la mortalidad en menores de cinco años en la Región de las Américas es fundamental para disminuir las grandes brechas entre países, áreas y grupos humanos, y lograr la equidad en el acceso a estrategias disponibles para la prevención y el tratamiento de las enfermedades, así como la promoción del crecimiento y el desarrollo saludable de la niñez. El Objetivo de Desarrollo del Milenio número 4 está relacionado con reducir la mortalidad en menores de cinco años en dos terceras partes entre 1990 y 2015... El componente comunitario de la Estrategia AIEPI contiene orientaciones preventivas de salud para que las familias las incorporen en sus hábitos y se constituya así en practices de buena salud para un desarrollo saludable de los niños, orientaciones sobre cuidados adecuados en el hogar en caso de enfermedad y, lo más importante, orientaciones para detectar oportunamente los signos cuando se requiera traslado urgente a un servicio de salud. Este material realizado por el Área de Salud Familiar y Comunitaria/Unidad de Salud del Niño y del Adolescente de la Organización Panamericana de la Salud, fue elaborado como parte de un esfuerzo para mejorar la detección de signos de peligro durante la enfermedad diarreica y contribuir de esta manera a la reducción de la morbilidad y mortalidad en niños y niñas menores de cinco años en la Región de las Américas.

Efficacy of rice-based oral rehydration solution containing recombinant human lactoferrin and lysozyme in Peruvian children with acute diarrhea.

OBJECTIVE: To compare glucose and rice-based oral rehydration solution with rice-based oral rehydration solution containing recombinant human lactoferrin and recombinant human lysozyme in diarrhea outcomes. PATIENTS AND METHODS: We conducted a randomized, double-blind controlled trial in children with acute diarrhea and dehydration. One hundred and forty children 5 to 33 months old were block randomized to receive low osmolarity WHO-ORS (G-ORS), rice-based ORS (R-ORS), or rice-based ORS plus lactoferrin and lysozyme (Lf/Lz-R-ORS). Intake and output were monitored for 48 h in the ORU, with continued monitoring through home and clinic follow-up for 14 d. RESULTS: The G-ORS and R-ORS groups did not show any differences in diarrhea outcomes and were therefore combined as the control group. Intent-to-treat analysis showed a significant decrease in duration of diarrhea (3.67 d vs 5.21 d, P = 0.05) in the Lf/Lz-R-ORS group as compared with the control group and a significant increase in the number of children who achieved 48 h with solid stool, 85% vs 69% (P < 0.05). There were no significant differences [corrected] in volume of diarrhea or [corrected] the percentage of children who had a new diarrhea episode after achieving the endpoint. CONCLUSIONS: Addition of recombinant human lactoferrin and lysozyme to a rice-based oral rehydration solution had beneficial effects on children with acute diarrhea.

Human caliciviruses as a cause of severe gastroenteritis in Peruvian children.

To define the role of human caliciviruses (HuCVs) in severe childhood gastroenteritis, fecal and paired serum samples from 233 Peruvian children hospitalized with gastroenteritis (case patients) and fecal samples from 248 control subjects were evaluated. Overall, 128 case patients (55%) demonstrated HuCV infection by either fecal (n=81 [35%]) or serological (n=96 [41%]) testing. HuCVs were more prevalent in fecal samples from case patients than those from control subjects (35% vs. 13%; P<.001). HuCV infection was more prevalent among case patients without another pathogen than in those who had a coinfecting pathogen (77% [40/52] vs. 49% [88/181]; P<.001). HuCVs appear to be an important cause of gastroenteritis in Peruvian children.