Programmable CSF shunt valves: radiographic identification and interpretation.
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ABSTRACT:
SUBMITTER: Lollis SS
PROVIDER: S-EPMC7965480 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:(1) Background: pediatric hydrocephalus is a challenging condition. Programmable shunt valves (PSV) have been increasingly used. This study is undertaken to firstly, to objectively evaluate the efficacy of PSV as a treatment modality for pediatric hydrocephalus; and next, review its associated patient outcomes at our institution. Secondary objectives include the assessment of our indications for PSV, and corroboration of our results with published literature. (2) Methods: this is an ethics-approved, retrospective study. Variables of interest include age, gender, hydrocephalus etiology, shunt failure rates and incidence of adjustments made per PSV. Data including shunt failure, implant survival, and utility comparisons between PSV types are subjected to statistical analyses. (3) Results: in this case, 51 patients with PSV are identified for this study, with 32 index and 19 revision shunts. There are 3 cases of shunt failure (6%). The mean number of adjustments per PSV is 1.82 times and the mean number of adjustments made per PSV is significantly lower for MEDTRONIC™ Strata PSVs compared with others (p = 0.031). Next, PSV patients that are adjusted more frequently include cases of shunt revisions, PSVs inserted due to CSF over-drainage and tumor-related hydrocephalus. (4) Conclusion: we describe our institutional experience of PSV use in pediatric hydrocephalus and its advantages in a subset of patients whose opening pressures are uncertain and evolving.
| S-EPMC8615584 | biostudies-literature
Project description:The objective of this study was to use high-resolution cone-beam computed images (hr- CBCT) to diagnose degenerative joint disease in asymptomatic and symptomatic subjects using the Diagnostic Criteria for Temporomandibular Disorders DC/TMD imaging criteria. This observational study comprised of 92 subjects age-sex matched and divided into two groups: clinical degenerative joint disease (c-DJD, n = 46) and asymptomatic control group (n = 46). Clinical assessment of the DJD and high-resolution CBCT images (isotropic voxel size of 0.08mm) of the temporomandibular joints were performed for each participant. An American Board of Oral and Maxillofacial Radiology certified radiologist and a maxillofacial radiologist used the DC/TMD imaging criteria to evaluate the radiographic findings, followed by a consensus of the radiographic evaluation. The two radiologists presented a high agreement (Cohen's Kappa ranging from 0.80 to 0.87) for all radiographic findings (osteophyte, erosion, cysts, flattening, and sclerosis). Five patients from the c- DJD group did not present radiographic findings, being then classified as arthralgia. In the asymptomatic control group, 82.6% of the patients presented radiographic findings determinant of DJD and were then classified as osteoarthrosis or overdiagnosis. In conclusion, our results showed a high number of radiographic findings in the asymptomatic control group, and for this reason, we suggest that there is a need for additional imaging criteria to classify DJD properly in hr-CBCT images.
| S-EPMC8354480 | biostudies-literature
Project description:BackgroundTo determine the agreement rate between histopathologic diagnosis and radiographic interpretation of jaw lesions.MethodsCases with jaw pathologies that have diagnostically adequate histopathologic samples and radiographic examinations were reviewed retrospectively. Two board-certified oral and maxillofacial pathologists (OMFP) independently determined the histopathologic diagnosis, while two board-certified oral and maxillofacial radiologists (OMFR) determined the radiographic interpretations independently. Then the histopathologic diagnosis and the radiographic interpretation were compared for agreement.ResultsA total of 104 cases (53% females) were included with a mean age of 31 years. The agreement rate between histopathologic diagnosis and radiographic interpretation was 49%. OMFP required OMFR consultations to reach a diagnosis in 16% of cases. The most commonly encountered lesions were by far odontogenic cysts of inflammatory origin and the agreement for this disease category was 49.1%. However, agreement rates were highest for the disease category of tumors (62.5%).ConclusionThe agreement rate between OMFP and OMFR was higher for tumors than cysts. Agreement rates between OMFP and OMFR improved with efficient consultation between the two disciplines.
| S-EPMC6425351 | biostudies-literature
Project description:Introduction:We developed and validated a clinically applicable decision tree for the use of cerebrospinal fluid biomarkers in the diagnosis of Alzheimer's disease (AD). Methods:Subjects with probable AD (n = 1004) and controls (n = 442) were included. A decision tree was modeled using Classification And Regression Tree analysis in a training cohort (AD n = 221; controls n = 221) and validated in an independent cohort (AD n = 783; controls n = 221). Diagnostic performance was compared to previously defined cutoffs (amyloid β 1-42 < 813 pg/ml; tau>375 pg/ml). Results:Two cerebrospinal fluid AD biomarker profiles were revealed: the "classical" AD biomarker profile (amyloid β 1-42: 647-803 pg/ml; tau >374 pg/ml) and an "atypical" AD biomarker profile with strongly decreased amyloid β 1-42 (<647 pg/ml) and normal tau concentrations (<374 pg/ml). Compared to previous cutoffs, the decision tree performed better on diagnostic accuracy (86% [84-88] vs 80% [78-83]). Discussion:Two cerebrospinal fluid AD biomarker profiles were identified and incorporated in a readily applicable decision tree, which improved diagnostic accuracy.
| S-EPMC6287084 | biostudies-other
Project description:Microfluidics are essential for many lab-on-a-chip applications, but it is still challenging to implement a portable and programmable device that can perform an assay protocol autonomously when used by a person with minimal training. Here, we present a versatile concept toward this goal by realizing programmable liquid circuits where liquids in capillary-driven microfluidic channels can be controlled and monitored from a smartphone to perform various advanced tasks of liquid manipulation. We achieve this by combining electro-actuated valves (e-gates) with passive capillary valves and self-vented channels. We demonstrate the concept by implementing a 5-mm-diameter microfluidic clock, a chip to control four liquids using 100 e-gates with electronic feedback, and designs to deliver and merge multiple liquids sequentially or in parallel in any order and combination. This concept is scalable, compatible with high-throughput manufacturing, and can be adopted in many microfluidics-based assays that would benefit from precise and easy handling of liquids.
| S-EPMC7250678 | biostudies-literature
Project description:BackgroundNearly 20% of patients with cerebrospinal fluid (CSF) shunt infection develop reinfection. It is unclear whether reinfections are caused by an organism previously present or are independent infection events.ObjectiveWe used bacterial culture and high throughput sequencing (HTS) of 16S ribosomal RNA (rRNA) genes to identify bacteria present in serial CSF samples obtained from children who failed CSF shunt infection treatment. We hypothesized that organisms that persist in CSF despite treatment would be detected upon reinfection.Design/methodsSerial CSF samples were obtained from 6 patients, 5 with 2 infections and 1 with 3 infections; the study was limited to those for which CSF samples were available from the end of infection and beginning of reinfection. Amplicons of the 16S rRNA gene V4 region were sequenced. Taxonomic assignments of V4 sequences were compared with bacterial species identified in culture.ResultsSeven infection dyads averaging 13.5 samples per infection were analyzed. A median of 8 taxa [interquartile range (IQR) 5-10] were observed in the first samples from reinfection using HTS. Conventional culture correlated with high abundance of an organism by HTS in all but 1 infection. In 6 of 7 infection dyads, organisms identified by culture at reinfection were detected by HTS of culture-negative samples at the end of the previous infection. The median Chao-Jaccard abundance-based similarity index for matched infection pairs at end of infection and beginning of reinfection was 0.57 (IQR 0.07-0.87) compared to that for unmatched pairs of 0.40 (IQR 0.10-0.60) [p = 0.46].Conclusion(s)HTS results were generally consistent with culture-based methods in CSF shunt infection and reinfection, and may detect organisms missed by culture at the end of infection treatment but detected by culture at reinfection. However, the CSF microbiota did not correlate more closely within patients at the end of infection and beginning of reinfection than between any two unrelated infections. We cannot reject the hypothesis that sequential infections were independent.
| S-EPMC7787469 | biostudies-literature
Project description:PurposeTo study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on opacity visibility on chest radiographs.Materials and methodsThis retrospective study included 20 pairs of CT scans and same-day chest radiographs from 17 patients with COVID-19, along with 20 chest radiographs of controls. All pulmonary opacities were semiautomatically segmented on CT images, producing an anteroposterior projection image to match the corresponding frontal chest radiograph. The quantitative CT lung opacification mass (QCTmass) was defined as (opacity attenuation value + 1000 HU)/1000 × 1.065 (g/mL) × combined volume (cm3) of the individual opacities. Eight thoracic radiologists reviewed the 40 radiographs, and a receiver operating characteristic curve analysis was performed for the detection of lung opacities. Logistic regression analysis was performed to identify factors affecting opacity visibility on chest radiographs.ResultsThe mean QCTmass per patient was 72.4 g ± 120.8 (range, 0.7-420.7 g), and opacities occupied 3.2% ± 5.8 (range, 0.1%-19.8%) and 13.9% ± 18.0 (range, 0.5%-57.8%) of the lung area on the CT images and projected images, respectively. The radiographs had a median sensitivity of 25% and specificity of 90% among radiologists. Nineteen of 186 opacities were visible on chest radiographs, and a median area of 55.8% of the projected images was identifiable on radiographs. Logistic regression analysis showed that QCTmass (P < .001) and combined opacity volume (P < .001) significantly affected opacity visibility on radiographs.ConclusionQCTmass varied among patients with COVID-19. Chest radiographs had high specificity for detecting lung opacities in COVID-19 but a low sensitivity. QCTmass and combined opacity volume were significant determinants of opacity visibility on radiographs.Earlier incorrect version appeared online. This article was corrected on April 6, 2020 and December 14, 2020.Supplemental material is available for this article.© RSNA, 2020.
| S-EPMC7233433 | biostudies-literature
Project description:To explore the feasibility of an automatic machine-learning algorithm-based quality control system for the practice of diagnostic radiography, performance of a convolutional neural networks (CNN)-based algorithm for identifying radiographic (X-ray) views at different levels was examined with a retrospective, HIPAA-compliant, and IRB-approved study performed on 15,046 radiographic images acquired between 2013 and 2018 from nine clinical sites affiliated with our institution. Images were labeled according to four classification levels: level 1 (anatomy level, 25 classes), level 2 (laterality level, 41 classes), level 3 (projection level, 108 classes), and level 4 (detailed level, 143 classes). An Inception V3 model pre-trained with ImageNet dataset was trained with transfer learning to classify the image at all levels. Sensitivity and positive predictive value were reported for each class, and overall accuracy was reported for each level. Accuracy was also reported when we allowed for "reasonable errors". The overall accuracy was 0.96, 0.93, 0.90, and 0.86 at levels 1, 2, 3, and 4, respectively. Overall accuracy increased to 0.99, 0.97, 0.94, and 0.88 when "reasonable errors" were allowed. Machine learning algorithms resulted in reasonable model performance for identifying radiographic views with acceptable accuracy when "reasonable errors" were allowed. Our findings demonstrate the feasibility of building a quality-control program based on machine-learning algorithms to identify radiographic views with acceptable accuracy at lower levels, which could be applied in a clinical setting.
| S-EPMC7887112 | biostudies-literature
Project description:ObjectivesIdiopathic normal pressure hydrocephalus (INPH) is a neurodegenerative disorder characterized by excess cerebrospinal fluid (CSF) in the ventricles, which can be diagnosed by invasive CSF drainage test and treated by shunt placement. Here, we aim to investigate the diagnostic and prognostic power of systematic volumetric analysis based on brain structural MRI for INPH.MethodsWe performed a retrospective study with a cohort of 104 probable INPH patients who underwent CSF drainage tests and another cohort of 41 INPH patients who had shunt placement. High-resolution T1-weighted images of the patients were segmented using an automated pipeline into 283 structures that are grouped into different granularity levels for volumetric analysis. Volumes at multi-granularity levels were used in a recursive feature elimination model to classify CSF drainage responders and non-responders. We then used pre-surgical brain volumes to predict Tinetti and MMSE scores after shunting, based on the least absolute shrinkage and selection operator.ResultsThe classification accuracy of differentiating the CSF drainage responders and non-responders increased as the granularity increased. The highest diagnostic accuracy was achieved at the finest segmentation with a sensitivity/specificity/precision/accuracy of 0.89/0.91/0.84/0.90 and an area under the curve of 0.94. The predicted post-surgical neurological scores showed high correlations with the ground truth, with r = 0.80 for Tinetti and r = 0.88 for MMSE. The anatomical features that played important roles in the diagnostic and prognostic tasks were also illustrated.ConclusionsWe demonstrated that volumetric analysis with fine segmentation could reliably differentiate CSF drainage responders from other INPH-like patients, and it could accurately predict the neurological outcomes after shunting.Key points• We performed a fully automated segmentation of brain MRI at multiple granularity levels for systematic volumetric analysis of idiopathic normal pressure hydrocephalus (INPH) patients. • We were able to differentiate patients that responded to CSF drainage test with an accuracy of 0.90 and area under the curve of 0.94 in a cohort of 104 probable INPH patients, as well as to predict the post-shunt gait and cognitive scores with a coefficient of 0.80 for Tinetti and 0.88 for MMSE. • Feature analysis showed the inferior lateral ventricle, bilateral hippocampus, and orbital cortex are positive indicators of CSF drainage responders, whereas the posterior deep white matter and parietal subcortical white matter were negative predictors.
| S-EPMC8213563 | biostudies-literature
Project description:ObjectiveThe objectives of the present study were to investigate (1) whether trinary visual interpretation of amyloid positron emission tomography (PET) imaging (negative/equivocal/positive) reflects quantitative amyloid measurements and the time course of 11C-Pittsburgh compound B (PiB) amyloid accumulation, and (2) whether visually equivocal scans represent an early stage of the Alzheimer's disease (AD) continuum in terms of an intermediate state of quantitative amyloid measurements and the changes in amyloid accumulation over time.MethodsFrom the National Bioscience Database Center Human Database of the Japanese Alzheimer's Disease Neuroimaging Initiative, we selected 133 individuals for this study including 33 with Alzheimer's disease dementia (ADD), 52 with late mild cognitive impairment (LMCI), and 48 cognitively normal (CN) subjects who underwent clinical assessment, PiB PET, and structural magnetic resonance imaging (MRI) with 2 or 3-years of follow-up. Sixty-eight of the 133 individuals underwent cerebrospinal fluid amyloid-?1-42 (CSF-Ab42) analysis at baseline. The standard uptake value ratio (SUVR) of PiB PET was calculated with a method using MRI at each visit. The cross-sectional values, longitudinal changes in SUVR, and baseline CSF-Ab42 were compared among groups, which were categorized based on trinary visual reads of amyloid PET (negative/equivocal/positive).ResultsFrom the trinary visual interpretation of the PiB PET images, 55 subjects were negative, 8 were equivocal, and 70 were positive. Negative interpretation was most frequent in the CN group (70.8/10.4/18.8%: negative/equivocal/positive), and positive was most frequent in the LMCI group (34.6/1.9/63.5%) and in the ADD group (9.1/6.1/84.8%). The baseline SUVRs were 1.08?±?0.06 in the negative group, 1.23?±?0.15 in the equivocal group, and 1.86?±?0.31 in the positive group (F?=?174.9, p?<?0.001). The baseline CSF-Ab42 level was 463?±?112 pg/mL in the negative group, 383?±?125 pg/mL in the equivocal group, and 264?±?69 pg/mL in the positive group (F?=?37, p?<?0.001). Over the 3-year follow-up, annual changes in SUVR were?-?0.00?±?0.02 in the negative group, 0.02?±?0.02 in the equivocal group, and 0.04?±?0.07 in the positive group (F?=?8.4, p?<?0.001).ConclusionsTrinary visual interpretation (negative/equivocal/positive) of amyloid PET imaging reflects quantitative amyloid measurements evaluated with PET and the CSF amyloid test as well as the amyloid accumulation over time evaluated with PET over 3 years. Subjects in the early stage of the AD continuum could be identified with an equivocal scan, because they showed intermediate quantitative amyloid PET, CSF measurements, and the amyloid accumulation over time.
| S-EPMC7026272 | biostudies-literature