Manual Quantification Methods Research Articles

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease.

Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

Clinical validation of an AI-based automatic quantification tool for lung lobes in SPECT/CT

BackgroundLung lobar ventilation and perfusion (V/Q) quantification is generally obtained by generating planar scintigraphy images and then imposing three equally sized regions of interest on the data of each lung. This method is fast but not as accurate as SPECT/CT imaging, which provides three-dimensional data and therefore allows more precise lobar quantification. However, the manual delineation of each lobe is time-consuming, which makes SPECT/CT incompatible with the clinical workflow for V/Q estimation. An alternative may be to use artificial intelligence-based auto-segmentation tools such as AutoLung3D (Siemens Healthineers, Knoxville, USA), which automatically delineate the lung lobes on the CT data acquired with the SPECT data. The present study assessed the clinical validity of this approach relative to planar scintigraphy and manual quantification in SPECT/CT.MethodsThe Autolung3D software was tested on the retrospective SPECT/CT data of 43 patients who underwent V/Q scintigraphy with 99mTc-macroaggregated albumin and 99mTc-labeled aerosol. It was compared to planar scintigraphy and SPECT/CT using the manual quantification method in terms of relative lobar V/Q quantification values and interobserver variability.ResultsThe three methods provided similar V/Q estimates for the left lung lobes and total lungs. However, compared to the manual SPECT/CT method, planar scintigraphy yielded significantly higher estimates for the middle right lobe and significantly lower estimates for the superior and inferior right lobes. The estimates of the manual and automated SPECT/CT methods were similar. However, the post-processing time in the automated method was approximately 5 min compared to 2 h for the manual method. Moreover, the automated method associated with a drastic reduction in interobserver variability: Its maximal relative standard deviation was only 5%, compared to 23% for planar scintigraphy and 19% for the manual SPECT/CT method.ConclusionsThis study validated the AutoLung3D software for general clinical use since it rapidly provides accurate lobar quantification in V/Q scans with markedly less interobserver variability than planar scintigraphy or the manual SPECT/CT method.

Decarbonisation of the urban built environment through vegetation-based carbon sequestration

The impacts of climate change require a strategic improvement in design decision-making. Leading professionals are aiming for carbon-positive buildings that can achieve carbon sequestration by adding vegetation to buildings. Multiple references and case studies explored in this paper suggest that there is theoretical potential for cities to become carbon sinks by constructing carbon-positive buildings. However, determining effective strategies, and quantifying and monitoring carbon sequestration in buildings, requires a standardised approach so that this carbon sequestration potential can be measurably established. This paper provides two key outputs: firstly, the paper identifies strategies that could shift buildings towards being capable of active carbon sequestration. Secondly, the paper provides a methodological framework with four key considerations that building professionals can use to design for carbon sequestration. These are: understanding the site’s ecological, climatic, cultural and legal context; identifying response, pressure, state and benefits indicators to set carbon sequestration targets; considering site ecosystem functioning and carbon dynamics to strategise carbon sequestration through design; and preparing long-term monitoring, evaluation and management plans. This paper identifies two areas for further investigation: linking manual quantification methods with computer-aided methods; and utilising biomass data and growth models at the landscape, regional, and global levels for carbon sequestration assessment.

Quantification of hematoma and perihematomal edema volumes in intracerebral hemorrhage study: Design considerations in an artificial intelligence validation (QUANTUM) study.

Hematoma and perihematomal edema volumes are important radiographic markers in spontaneous intracerebral hemorrhage. Accurate, reliable, and efficient quantification of these volumes will be paramount to their utility as measures of treatment effect in future clinical studies. Both manual and semi-automated quantification methods of hematoma and perihematomal edema volumetry are time-consuming and susceptible to inter-rater variability. Efforts are now underway to develop a fully automated algorithm that can replace them. A (QUANTUM) study to establish inter-quantification method measurement equivalency, which deviates from the traditional use of measures of agreement and a comparison hypothesis testing paradigm to indirectly infer quantification method measurement equivalence, is described in this article. The Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study aims to determine whether a fully automated quantification method and a semi-automated quantification method for quantification of hematoma and perihematomal edema volumes are equivalent to the hematoma and perihematomal edema volumes of the manual quantification method. Hematoma and perihematomal edema volumes of supratentorial intracerebral hemorrhage on 252 computed tomography scans will be prospectively quantified in random order by six raters using the fully automated, semi-automated, and manual quantification methods. Primary outcome measures for hematoma and perihematomal edema volumes will be quantified via computed tomography scan on admission (<24 h from symptom onset) and on day 3 (72 ± 12 h from symptom onset), respectively. Equivalence hypothesis testing will be conducted to determine if the hematoma and perihematomal edema volume measurements of the fully automated and semi-automated quantification methods are within 7.5% of the hematoma and perihematomal edema volume measurements of the manual quantification reference method. By allowing direct equivalence hypothesis testing, the Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study offers advantages over radiology validation studies which utilize measures of agreement to indirectly infer measurement equivalence and studies which mistakenly try to infer measurement equivalence based on the failure of a comparison two-sided null hypothesis test to reach the significance level for rejection. The equivalence hypothesis testing paradigm applied to artificial intelligence application validation is relatively uncharted and warrants further investigation. The challenges encountered in the design of this study may influence future studies seeking to translate artificial intelligence medical technology into clinical practice.

A digital method to interpret the C-MYC stain in diffuse large B cell lymphoma

Diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS) is a heterogenous group of aggressive lymphomas. C-MYC expression by immunohistochemical stain (IHC) is shown to be an independent prognostic factor in DLBCL. In the clinical setting, MYC stain is currently evaluated by manual quantification with a minimum positivity cut-off 40%. Manual quantification methods can be subjective and may show intra- and interobserver variability and variability between centers. Thus, stains which require definitive quantification such as MYC needs better standardized and precise methods. Here we present a simple digital algorithm for quantitative evaluation of MYC stain in DLBCL, NOS. For this, slides immunostained for C-MYC were scanned at 40X with a high-resolution, Philips Ultra Fast scanner (Koninklijke Philips N.V. Cambridge, MA). The images were manually assessed and appropriate areas with neoplastic cells were selected. For quantification, positive and negative C-MYC staining nuclei were scored using a modified Visiopharm APP Nuclei Detection, AI (Brightfield) using Visiopharm Image Analysis software (Visiopharm, Hørsholm, Denmark version 2018.09). The percentage positivity resulted by the digital method was concordant with the pathologist’s interpretation with statistical significance (rs: 0.85968; p (2-tailed) = 0). Minor disadvantages were observed including failure to detect very weak staining and inability to separate neoplastic and non-neoplastic nuclei when admixed in the same area. If combined with a quick manual evaluation, a digital method like this with precision and reproducibility will be of great use in quantitative evaluation of MYC and other similar stains in clinical setting and will reduce intra- and interobserver variability.

Quantification and Analysis of Laryngeal Closure From Endoscopic Videos.

At present, there are no objective techniques to quantify and describe laryngeal obstruction, and the reproducibility of subjective manual quantification methods is insufficient, resulting in diagnostic inaccuracy and a poor signal-to-noise ratio in medical research. In this work, a workflow is proposed to quantify laryngeal movements from laryngoscopic videos, to facilitate the diagnosis procedure. The proposed method analyses laryngoscopic videos, and delineates glottic opening, vocal folds, and supraglottic structures, using a convolutional neural networks (CNNs) based algorithm. The segmentation is divided into two steps: A bounding box which indicates the region of interest (RoI) is found, followed by segmentation using fully convolutional networks (FCNs). The segmentation results are statistically quantified along the temporal dimension and processed using singular spectrum analysis (SSA), to extract clear objective information that can be used by the clinicians in diagnosis. The segmentation was validated on 400 images from 20 videos acquired using different endoscopic systems from different patients. The results indicated significant improvements over using FCN only in terms of both processing speed (16 FPS vs. 8 FPS) and segmentation result statistics. Five clinical cases on patients have also been provided to showcase the quantitative analysis results using the proposed method. The proposed method guarantees a robust and fast processing of laryngoscopic videos. Measurements of glottic angles and supraglottic index showed distinctive patterns in the provided clinical cases. The proposed automated and objective method extracts important temporal laryngeal movement information, which can be used to aid laryngeal closure diagnosis.

Myocardial Fibrosis in Hypertrophic Cardiomyopathy: Volumetric Assessment of Late Enhancement Provided by Cardiac Computed Tomography.

With subgroups of patients with hypertrophic cardiomyopathy (HCM) confers a 4% to 5% risk for adverse prognosis. Besides left-ventricular muscle mass (LV-MM) myocardial fibrosis (MF) assessable by late gadolinium enhancement in cardiovascular magnetic resonance (LGE-CMR) has been related to that. Myocardial fibrosis can also be demonstrated by late enhancement (LE) in late-enhanced multislice computed tomography (leMDCT). This analysis investigates leMDCT whether to enable quantification of LE load in terms of LE mass by percent LV-MM in HCM. In a prospective validation study, we included 30 consecutive patients with HCM who underwent leMDCT (64 slice) and LGE-CMR (1.5 T). The leMDCT scan was performed 7 minutes after injection of iodine contrast (Iopromid). Endocardial and epicardial planimetry served for the assessment of LV-MM. Visually detectable LE was quantified using the manual quantification method resulting in LE by percent LV-MM (%LE). The LGE-CMR data served for validation. Mean (SD) age was 64.1 (13.9) years. Myocardial fibrosis prevalence was 63.3% (19/30 patients indentified by both leMDCT and LGE-CMR). In leMDCT, tissue density in LE areas compared with normal myocardium was higher (138.2 [23.9] HU vs 98.4 [16.5] HU, P < 0.001) but lower than in the LV cavity (138.2 [23.9] HU vs 169.2 [35.9] HU, P < 0.001). Late enhancement mass in leMDCT seemed to be 7.9 (8.5) g LE versus 8.6 [11] g LGE in CMR (P = 0.497, r = 0.95) resulting in a leMDCT/LGE-CMR relation of 1.2. Referring LE mass to LV-MM gave an LE proportion measured by leMDCT of 4 (3.9) %LE versus 3.9 (4.1) %LGE in LGE-CMR (r = 0.88, P = 0.75). Intraobserver/interobserver reliability of LE mass assessment showed an intraclass correlation coefficient of 0.99 and 0.97. In patients with HCM, leMDCT provides volumetric assessment of LE mass-absolutely and by percent LV-MM.

Hypertrophic cardiomyopathy in cardiac CT: a validation study on the detection of intramyocardial fibrosis in consecutive patients

Hypertrophic Cardiomyopathy (HCM) confers a 4-5 %/year-risk for sudden cardiac death. Intramyocardial fibrosis (IF) is associated with this risk. The gold standard of IF visualization is cardiovascular magnetic resonance (CMR) with late gadolinium enhancement (LGE-CMR). In view of a number of CMR-limitations the hypothesis of this study was that late enhanced multi-slice computed tomography (leMDCT) enables demonstration of late enhancement (LE) indicating IF. In a prospective single-center validation study leMDCT research-scans were exclusively performed for IF-imaging in HCM-patients not including non-invasive coronary angiography during first-pass (64-slice; 80 kV; Iopromide, 150 mL, injected 7 min before scanning). Applying a 17-segment-polar-map short cardiac axis views (multiplanar reformations; 5 mm slice thickness) were analysed in order to exclude/detect, localize and measure LE practicing the manual quantification method if present. Finally, leMDCT and LGE-CMR data were unblinded for intermodal correlation. We included n = 24 patients consecutively (64.0 ± 14.5 years of age). LE was demonstrated by LGE-CMR in n = 14/24 patients (prevalence 58 %). Patient- and segment-based sensitivity in leMDCT was 100 and 68 %, respectively. In leMDCT tissue density of LE was 142 ± 51 versus 89.9 ± 19.3 HU in remote myocardium (p < 0.001). Signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) appeared to be 7.3 ± 3.3 and 2.3 ± 1, respectively. Sizing of LE-area gave 2.2 ± 1.4 cm(2) in leMDCT versus 2.9 ± 2.4 cm(2) in LGE-CMR (r = 0.93). Intra-/interobserver variability was assessed with an accuracy of 0.36 cm(2) (r = 0.91) and 0.47 cm(2) (r = 0.82), respectively. In consecutive HCM patients leMDCT can reliably detect intramyocardial fibrosis marked by LE. In view of a comparatively low SNR and CNR leMDCT may alternatively be applied in case of CMR contraindications.

Comparison of visceral adipose tissue quantification on water suppressed and nonwater‐suppressed MRI at 3.0 tesla

To systematically evaluate and compare the performance of water-saturated and nonwater-saturated T1-weighted 3.0 T magnetic resonance imaging (MRI) in the application of visceral adipose tissue (VAT) quantification. Forty-five patients underwent abdomen MRI using two different sequences at 3.0 T: 1) a traditional T1-weighted gradient echo sequence, and 2) the same sequence with water presaturation to enhance fat and nonfat contrast. VAT amounts from both water-saturated and nonwater-saturated images were quantified with a manual thresholding technique and an automated segmentation method to study quantification variability and consistency of the two imaging techniques. Nonwater-saturated MRI had significantly larger coefficient of variation than water-saturated MRI in the imaging reproducibility study based on 112 slices from seven subjects (11.4% vs. 2.5%, P < 0.0001). VAT volumes measured from the nonwater-saturation MRI sequence had significantly higher variability than those from water-saturation images even when using a manual quantification method based on images from 38 subjects (1.76% vs. 1.08%, P < 0.001). In addition, the VAT volume amounts from nonwater-saturation images and water-saturated images quantified with the automatic and manual quantification methods were statistically consistent. Water-saturated MRI sequences at 3.0 T for VAT quantification improve reproducibility and decrease variability compared with nonwater saturated sequences, especially with the use of automatic quantification methods.

Applications of Laser Scanning Cytometry in Immunohistochemistry and Routine Histopathology

Laser scanning cytometry (LSC) is a powerful tool for qualitative and quantitative analysis of tissue sections in preclinical drug development. LSC combines the strengths of flow cytometry with tissue architecture retention. This technology has been used predominantly with immunofluorescent techniques on cell culture and tissue sections, but recently LSC has shown promise in evaluating chromogenic immunohistochemistry (IHC) and histochemical products in paraffin-embedded and/or frozen tissue sections. Inverted light scatter measurements or a combination of inverted scatter and fluorescence allows automated determination of cell/nuclear counts (e.g., proliferation labeling indices), cell area (e.g., cellular hypertrophy), stromal elements, and labeling intensity (e.g., cytoplasmic/organellar proteins) in chromogen-labeled IHC or histochemical stained sections that correlates well with standard manual quantification methods. Segmentation with autofluorescence or dual immunolabeling facilitates capture of labeling data from specific cell populations. LSC evaluation of HE-stained sections is accomplished using autofluorescence/eosin fluorescence and inverse scatter. A standardized fluorescent approach with archivability, a lack of fluorescence quenching (photobleaching), and amenability to evaluation of multiple markers in a section has been demonstrated using Qdot nanocrystals. Examples of LSC use in chromogenic IHC, routine histopathology, and Qdot labeling will be reviewed, and advantages and disadvantages of this technology will be discussed.

Efficient Whole-body Transduction with Trans-splicing Adeno-associated Viral Vectors

Limited packaging capacity has hampered adeno-associated virus (AAV)-mediated gene therapy for many common genetic diseases such as cystic fibrosis (CF) and Duchenne muscular dystrophy (DMD). Trans-splicing AAV (tsAAV) vectors double AAV packaging capacity but their transduction efficiency has been too low to be useful. We have recently overcome this hurdle by rational vector design. We have shown that a pair of optimized mini-dystrophin tsAAV vectors can reach the same transduction efficiency as that of a single AAV vector after local injection in dystrophic muscle. However, global gene transfer is required to treat diseases like DMD. To test whether systemic delivery can be achieved with tsAAV vectors, we generated a set of optimized alkaline phosphatase (AP) tsAAV vectors. We delivered AAV serotype 9 pseudotyped AP tsAAV intravenously to newborn mice. Six weeks later, we observed high-level transduction in all body skeletal muscle and the heart, the tissues that are affected in DMD. We also detected efficient transduction in the lung, the primary organ affected in CF. Our results provide the first evidence of whole-body transduction with tsAAV vectors and further raise the hope of tsAAV gene therapy for DMD and CF.

Effects of acute and chronic ethanol exposure on the behavior of adult zebrafish ( Danio rerio)

The zebrafish has been a popular subject of embryology and genetic research for the past three decades. Recently, however, the interest in its neurobiology and behavior has also increased. Nevertheless, compared to other model organisms, e.g., rodents, zebrafish behavior is understudied and very few behavioral paradigms exist for mutation or drug screening purposes. Alcoholism is one of the biggest and costliest diseases whose mechanisms are not well understood. Model organisms such as the zebrafish may be utilized in this line of research. Previously, we investigated the effects of acute ethanol exposure on adult zebrafish using four behavioral paradigms and employing manual quantification methods. Here, we study the effects of chronic ethanol exposure and analyze how it modifies the effects of acute ethanol treatment. We employ a videotracking-based automated quantification method in a predator model paradigm and show that this method is capable of detecting an avoidance reaction that is ameliorated by higher doses of ethanol, a potential anxiolytic effect. Importantly, we also demonstrate that chronic, two week long, exposure to ethanol results in significant adaptation to this substance in adult zebrafish. Overall, our results suggest that zebrafish will be an appropriate subject for high throughput screening applications aimed at the analysis of the mechanisms and pharmacology of acute and chronic ethanol induced changes in the vertebrate brain.

Diagnostic performance of a 3-D automated quantification method of dopamine D2 receptor SPECT studies in the differential diagnosis of parkinsonism

Assessment of post-synaptic D2 receptors with 123I-IBZM SPECT is helpful in distinguishing idiopathic (IPS) from other parkinsonian syndromes (non-IPS). To evaluate the diagnostic performance of a recently introduced three-dimensional automated quantification method in a large group of parkinsonian patients. IBZM SPECT was performed in 101 consecutive patients with IPS (n = 49) and non-IPS (n = 52). Striatal/frontal cortex binding ratios were assessed by a standard manual quantification method and by the automated method. For the latter patient studies were registered to a mean template of healthy controls (n = 13). IBZM binding was calculated from a 3-D volume-of-interest map established on the normal template. The diagnostic performance of the automated and manual approaches were assessed by receiver operating characteristic (ROC) analyses. Specific striatal binding ratios of both quantification methods showed a close linear relationship (y = 0.81x + 0.1188; R2 = 0.8062). At optimal decision thresholds sensitivity and specificity were 87% and 90% for the automated, and 85% and 90% for the manual method, respectively. The area under the ROC curve was 0.92 for the automated and 0.93 for the manual method, showing no statistical difference. The area under the ROC curve corresponding to a false positive fraction from 0% to 20% was 0.163 for the automated and 0.166 for the manual evaluation. The diagnostic performance of an automated 3-D quantification method for IBZM SPECT studies has been shown to be equal to, or even better than, a standard manual technique. Advantages of automated quantifications are observer independence and fast processing times. This method may be also used as a platform for processing large data sets/multicentre studies in order to objectively evaluate basal ganglia disorders.

Qualitative and Quantitative Measurement of Human Brain Activity Using Pixel Subtraction Algorithm

Purpose: To develop an automated quantification program, which is called FALBA (Functional & Anatomical Labeling of Brain Activation), and to provide information on the brain centers, brain activity (%) and hemispheric lateralization index on the basis of a brain activation map obtained from functional MR imaging. Materials and Methods: The 3-dimensional activation MR images were processed by a statistical parametric mapping program (SPM99, The Wellcome Department of Cognitive Neurology, University College London, UK) and MRIcro software (www.mricro.com). The 3-dimensional images were first converted into 2-dimensional sectional images, and then overlapped with the corresponding T1-weighted images. Then, the image dataset was extended to -59 mm to 83 mm with a 2 mm slice-gap, giving 73 axial images. By using a pixel subtraction method, the differences in the R, G, B values between the T1-weighted images and the activation images were extracted, in order to produce black & white (B/W) differentiation images, in which each pixel is represented by 24-bit R, G, B true colors. Subsequently, another pixel differentiation method was applied to two template images, namely one functional and one anatomical index image, in order to generate functional and anatomical differentiation images containing regional brain activation information based on the Brodmann's and anatomical areas, respectively. In addition, the regional brain lateralization indices were automatically determined, in order to evaluate the hemispheric predominance, with the positive (+) and negative (-) indices showing left and right predominance, respectively. Results: The manual counting method currently used is time consuming and has limited accuracy and reliability in the case of the activated cerebrocortical regions. The FALBA program we developed was 240 times faster than the manual counting method: -10 hours for manual accounting and -2.5 minutes for the FALBA program using a Pentium IV processor. Compared with the FALBA program, the manual quantification method showed an average error of 0.3340.007 (%). Thus, the manual counting method gave less accurate quantitative information on brain activation than the FALBA program. Conclusion: The FALBA program is capable of providing accurate quantitative results, including the identification of the brain activation region and lateralization index with respect to the functional and anatomical areas. Also, the processing time was dramatically shortened in comparison with the manual counting method.

Evaluating root growth potential of tree seedlings with an automated measuring system

Root growth of tree seedlings was quantified as change in root area index by using a video camera and digitizing area meter system that sums scanning line and root intersections. Number and total length of roots 〉0.5 cm and area index change were measured over a wide range of values. Linear regressions indicated that the automated and manual quantification methods yield essentially the same result. The automated method reduces measurement time, minimizes observer subjectivity, and estimates all new root growth. However, the equipment is costly, and the method does not provide information on the origin or size of new roots.