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The study aims to reveal the composition of subgingival bacteria in monozygotic twins with discordant in severity and progression risk of periodontitis. Microbiome analysis indicated that most bacteria were heritable but differed in their abundance and immune response. The dysbiotic bacteria can be considered as risk markers for periodontitis progression.
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PURPOSE: Increased use of deep learning (DL) in medical imaging diagnoses has led to more frequent use of 10-fold cross-validation (10-CV) for the evaluation of the performance of DL. To eliminate some of the (10-fold) repetitive processing in 10-CV, we proposed a "generalized fitting method in conjunction with every possible coalition of N-combinations (G-EPOC)", to estimate the range of the mean accuracy of 10-CV using less than 10 results of 10-CV. MATERIAL AND METHODS: G-EPOC was executed as follows. We first provided (2N-1) coalition subsets using a specified N, which was 9 or less, out of 10 result datasets of 10-CV. We then obtained the estimation range of the accuracy by applying those subsets to the distribution fitting twice using a combination of normal, binominal, or Poisson distributions. Using datasets of 10-CVs acquired from the practical detection task of the appendicitis on CT by DL, we scored the estimation success rates if the range provided by G-EPOC included the true accuracy. RESULTS: G-EPOC successfully estimated the range of the mean accuracy by 10-CV at over 95% rates for datasets with N assigned as 2 to 9. CONCLUSIONS: G-EPOC will help lessen the consumption of time and computer resources in the development of computerbased diagnoses in medical imaging and could become an option for the selection of a reasonable K value in K-CV.
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The original article can be found online.
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PURPOSE: To reveal that a computed tomography surveillance program (CT-surveillance) could demonstrate the epidemiologic features of COVID-19 infection and simultaneously investigate the type and frequency of CT findings using clinical CT data. MATERIALS AND METHODS: We targeted individuals with possible CT findings of viral pneumonia. Using an online questionnaire, we asked Japanese board-certified radiologists to register their patients' information including patient age and sex, the CT examination date, the results of PCR test for COVID-19 infection, CT findings, and the postal code of the medical institution that performed the CT. We compared the diurnal patient number and the cumulative regional distribution map of registrations in CT-surveillance to those of the PCR-positive patient surveillance (PCR-surveillance). RESULTS: A total of 637 patients was registered from January 1 to April 17, 2020 for CT-surveillance. Their PCR test results were positive (n = 62.5-398%), negative (n = 8.9-57%), unknown (n = 26.2-167%), and other disease (n = 2.4-15%). An age peak at 60-69 years and male dominance were observed in CT-surveillance. The most common CT finding was bilaterally distributed ground-glass opacities. The diurnal number and the cumulative regional distribution map by CT-surveillance showed tendencies that were similar to those revealed by PCR-surveillance. CONCLUSION: Using clinical CT data, CT-surveillance program delineated the epidemiologic features of COVID-19 infection.
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COVID-19/diagnóstico por imagem , COVID-19/epidemiologia , Tomografia Computadorizada por Raios X/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Monitoramento Epidemiológico , Feminino , Humanos , Lactente , Japão/epidemiologia , Pulmão/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Pandemias , SARS-CoV-2 , Inquéritos e Questionários , Adulto JovemRESUMO
The prevention of nosocomial infections is an imperative task. The dental chair unit (DCU) is an indispensable device used in dental treatment. However, it is known that the dental unit water line (DUWL) can become contaminated with biofilm, consisting mainly of heterotrophic bacteria (HB). Recently, the International Organization for Standardization specified the methods for testing DUWL contamination management. On these grounds, a simulator reproducing DUWL was prepared to standardize the examination method of the DUWL contamination. OBJECTIVES: To evaluate the reproducibility of the DUWL simulator, monitor the DUWL contamination states, and test the efficacy of a commercial decontaminant for DUWL. METHODS: The DUWL simulator was assembled by a DCU manufacturing company. The simulator's DUWL was filled with tap water (TW), and left for approximately one year. Neutral electrolyzed water (NEW) was used as a decontaminant for DUWL. Both TW and NEW were passed through DUWL in a timely manner simulating daily dental treatment. Water was sampled from the air turbine hand piece weekly for 4 weeks and used for HB culture. Contamination status was evaluated by measuring bacterial adenosine triphosphate release and by culturing on Reasoner's 2A medium. RESULTS: The DUWL released contaminated water had a bacterial count of over 6 × 104 cfu/mL. After passing NEW through DUWL for 1 week, the count drastically decreased to its basal level and remained steady for 4 weeks. However, TW showed no effect on DUWL decontamination throughout the examination periods. CONCLUSIONS: The DUWL simulator could be useful to examine the efficacy of the decontaminant for DUWL and development of new methods in DUWL contamination management.
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PURPOSE: Increased use of deep convolutional neural networks (DCNNs) in medical imaging diagnosis requires determinate evaluation of diagnostic performance. We performed the fundamental investigation of diagnostic performance of DCNNs using the detection task of brain metastasis. METHODS: We retrospectively investigated AlexNet and GoogLeNet using 3117 positive and 37961 negative MRI images with and without metastasis regarding (1) diagnostic biases, (2) the optimal K number of K-fold cross validations (K-CVs), (3) the optimal positive versus negative image ratio, (4) the accuracy improvement curves, (5) the accuracy range prediction by the bootstrap method, and (6) metastatic lesion detection by regions with CNNs (R-CNNs). RESULTS: Respectively, AlexNet and GoogLeNet had (1) 50 ± 4.6% and 50 ± 4.9% of the maximal mean ± 95% confidence intervals (95% CIs) measured with equal-sized negative versus negative image datasets and positive versus positive image datasets, (2) no less than 10 and 4 of K number in K-CVs fell within the respective maximum biases of 4.6% or 4.9%, (3) 74% of the highest accuracy with equal positive versus negative image ratio dataset and 91% of that with four times of negative-to-positive image ratio dataset, (4) the accuracy improvement curves increasing from 69% to 74% and 73% to 88% as positive versus negative pairs of the training images increased from 500 to 2495, (5) at least nine and six out of 10-CV result sets essential to predict the accuracy ranges by the bootstrap method, and (6) 50% and 45% of metastatic lesion detection accuracies by R-CNNs. CONCLUSIONS: Our research presented methodological fundamentals to evaluate diagnostic features in the visual recognition of DCNNs. Our series will help to conduct the accuracy investigation of computer diagnosis in medical imaging.
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Neoplasias Encefálicas/diagnóstico por imagem , Aprendizado Profundo , Interpretação de Imagem Assistida por Computador/métodos , Encéfalo/diagnóstico por imagem , Humanos , Imageamento por Ressonância Magnética , Estudos RetrospectivosRESUMO
Contamination of dental unit waterlines (DUWL) with heterotrophic bacteria can cause problems in immune compromised patients (aged, tumor and organ transplantation-patients). We focused on the use of low-concentrated ozonized water (OZW) as the biofilm formation restraint system for DUWL. Here, we examined the effects of low-concentrated OZW on the growth of bacteria and related biofilm formation and harmfulness to dental unit components (DUCs) in vitro. OBJECTIVES: To evaluate the bactericidal effects of OZW on biofilms in DUWL and DUC in vitro. METHODS: Low-concentrated OZW (0.4 mg/L) was generated using an OZS-PTDX generator. Heterotrophic bacterial biofilms in old DUWL tubes and Candia albicans solution (control microbe) were treated with OZW for 1 h with gentle agitation before static culturing for 96 h in Reasoner's 2A liquid media. The control solutions were 0.1% cetylpyridinium chloride (CPC), chlorinated tap water (TW), and phosphate-buffered saline (PBS). Adenosine triphosphate (ATP) amounts of the microbes were measured and the biofilms of these microbes were observed using scanning electron microscopy (SEM). Moreover, surfaces of DUC soaked in OZW and TW were observed by SEM. RESULTS: The OZW reduced ATP levels in microbes to 50% compared to TW and PBS treatment, although CPC reduced it below detection limits. SEM observation revealed deformation of microbes cultured with OZW, whereas no changes were seen on DUC surfaces. CONCLUSIONS: Low-concentrated OZW is bactericidal against heterotrophic bacteria biofilms and it is not harmful to DUC, suggesting that it might be useful in preventing DUWL contamination.
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PURPOSE: The confusion of MRI sequence names could be solved if MR images were automatically identified after image data acquisition. We revealed the ability of deep learning to classify head MRI sequences. MATERIALS AND METHODS: Seventy-eight patients with mild cognitive impairment (MCI) having apparently normal head MR images and 78 intracranial hemorrhage (ICH) patients with morphologically deformed head MR images were enrolled. Six imaging protocols were selected to be performed: T2-weighted imaging, fluid attenuated inversion recovery imaging, T2-star-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient mapping, and source images of time-of-flight magnetic resonance angiography. The proximal first image slices and middle image slices having ambiguous and distinctive contrast patterns, respectively, were classified by two deep learning imaging classifiers, AlexNet and GoogLeNet. RESULTS: AlexNet had accuracies of 73.3%, 73.6%, 73.1%, and 60.7% in the middle slices of MCI group, middle slices of ICH group, first slices of MCI group, and first slices of ICH group, while GoogLeNet had accuracies of 100%, 98.1%, 93.1%, and 94.8%, respectively. AlexNet significantly had lower classification ability than GoogLeNet for all datasets. CONCLUSIONS: GoogLeNet could judge the types of head MRI sequences with a small amount of training data, irrespective of morphological or contrast conditions.
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Inteligência Artificial , Encéfalo/diagnóstico por imagem , Encéfalo/fisiopatologia , Disfunção Cognitiva/fisiopatologia , Imageamento por Ressonância Magnética/métodos , Redes Neurais de Computação , Idoso , Idoso de 80 Anos ou mais , Imagem de Difusão por Ressonância Magnética , Feminino , Humanos , Angiografia por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Estudos RetrospectivosRESUMO
We previously reported a high incidence of kerato-conjunctivitis in patients receiving high-dose cytarabine following total body irradiation (TBI) as a conditioning for hematopoietic stem cell transplantation (HSCT) even on prophylaxis with topical corticosteroid. This study aimed to evaluate whether addition of eye rinse, which was designed to remove cytarabine from ocular surface, further reduces the incidence of kerato-conjunctivitis in the same setting. Seventy-six patients receiving cytarabine at a dose of 3 g/m(2) every 12 h for 4 days after receiving TBI (12 Gy) as conditioning for HSCT were evaluated. All patients received betamethasone sodium phosphate eye drops. Twenty-three patients were further instructed to rinse their eyes with sterile saline every 10-15 min during and for two additional hours after the completion of each cytarabine infusion. Among 23 patients with eye rinse, Grades 2-3 and 1-3 kerato-conjunctivitis were observed in 4 (17.4%) and 5 patients (21.7%), respectively. These incidences were significantly lower than those [35 (66.0%) and 41 (77.4%)] observed in 53 patients without eye rinse (P < 0.001 and P < 0.00001, respectively). These results strongly suggest that eye rinse effectively reduces the incidence and severity of cytarabine-induced kerato-conjunctivitis in HSCT recipients who receive high-dose cytarabine following TBI.
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Antimetabólitos Antineoplásicos/efeitos adversos , Citarabina/efeitos adversos , Transplante de Células-Tronco Hematopoéticas , Ceratoconjuntivite/induzido quimicamente , Ceratoconjuntivite/prevenção & controle , Condicionamento Pré-Transplante , Adolescente , Adulto , Antimetabólitos Antineoplásicos/administração & dosagem , Citarabina/administração & dosagem , Feminino , Humanos , Incidência , Ceratoconjuntivite/epidemiologia , Masculino , Pessoa de Meia-Idade , Índice de Gravidade de Doença , Transplante Homólogo , Irradiação Corporal Total , Adulto JovemRESUMO
High-dose cytarabine is one of the major components of the conditioning regimen for hematopoietic stem cell transplantation (HSCT), and frequently causes severe oral mucositis. We have recently demonstrated that cytarabine is excreted into the saliva in patients receiving high-dose cytarabine, and proposed that it might locally and directly contribute to the development of oral mucositis. Therefore, this study was performed to assess whether removing the excreted cytarabine in the saliva by intensive mouth rinse during high-dose cytarabine infusion could reduce the incidence of oral mucositis. Fifteen patients with hematologic malignancies undergoing allogeneic HSCT who received total body irradiation (12 Gy) and high-dose cytarabine at a dose of 3 g/m(2) every 12 h for 4 days as a conditioning were evaluated. Patients were instructed to rinse their mouths using ice-cold water every 10 min, starting simultaneously with the 2-h cytarabine infusion and continuing up to 1 h after completion of each infusion. Oral mucositis was graded on a daily basis according to the National Cancer Institute, Common Toxicity Criteria. Thirty-five patients who previously underwent the same conditioning without mouth rinse served as controls. The incidence of Grades 2-3 and Grade 3 oral mucositis was significantly reduced in patients who performed mouth rinse as compared with the controls (40 vs. 80%, P = 0.009; 0 vs. 25. 7%, P = 0.02). In conclusion, mouth rinse during and shortly after high-dose cytarabine infusion could be an effective and inexpensive measure in reducing the incidence of moderate to severe oral mucositis caused by high-dose cytarabine. This finding strongly suggests the role of cytarabine excretion in the saliva in the development of cytarabine-associated oral mucositis.