The modified Polsby-Popper score, a novel quantitative histomorphological biomarker and its potential to predict lymph node positivity and cancer-specific survival in oral tongue squamous cell carcinoma

BACKGROUND

The significance of different histological spreading patterns of tumor tissue in oral tongue squamous cell carcinoma (TSCC) is well known. Our aim was to construct a numeric parameter on a continuous scale, that is, the modified Polsby-Popper (MPP) score, to describe the aggressiveness of tumor growth and infiltration, with the potential to analyze hematoxylin and eosin-stained whole slide images (WSIs) in an automated manner. We investigated the application of the MPP score in predicting survival and cervical lymph node metastases as well as in determining patients at risk in the context of different surgical margin scenarios.

METHODS

We developed a semiautomated image analysis pipeline to detect areas belonging to the tumor tissue compartment. Perimeter and area measurements of all detected tissue regions were derived, and a specific mathematical formula was applied to reflect the perimeter/area ratio in a comparable, observer-independent manner across digitized WSIs. We demonstrated the plausibility of the MPP score by correlating it with well-established clinicopathologic parameters. We then performed survival analysis to assess the relevance of the MPP score, with an emphasis on different surgical margin scenarios. Machine learning models were developed to assess the relevance of the MPP score in predicting survival and occult cervical nodal metastases.

RESULTS

The MPP score was associated with unfavorable tumor growth and infiltration patterns, the presence of lymph node metastases, the extracapsular spread of tumor cells, and higher tumor thickness. Higher MPP scores were associated with worse overall survival (OS) and tongue carcinoma-specific survival (TCSS), both when assessing all pT-categories and pT1-pT2 categories only; moreover, higher MPP scores were associated with a significantly worse TCSS in cases where a cancer-free surgical margin of <5 mm could be achieved on the main surgical specimen. This discriminatory capacity remained constant when examining pT1-pT2 categories only. Importantly, the MPP score could successfully define cases at risk in terms of metastatic disease in pT1-pT2 cancer where tumor thickness failed to exhibit a significant predictive value. Machine learning (ML) models incorporating the MPP score could predict the 5-year TCSS efficiently. Furthermore, we demonstrated that machine learning models that predict occult cervical lymph node involvement can benefit from including the MPP score.

CONCLUSIONS

We introduced an objective, quantifiable, and observer-independent parameter, the MPP score, representing the aggressiveness of tumor growth and infiltration in TSCC. We showed its prognostic relevance especially in pT1-pT2 category TSCC, and its possible use in ML models predicting TCSS and occult lymph node metastases.

Phosphatase and Tensin Homolog (PTEN) Expression as a Surrogate Biomarker Correlated With the Depth of Invasion in Cutaneous Malignant Melanoma

Objective The aim of this study is to evaluate the expression of the phosphatase and tensin homolog (PTEN), which is a tumor suppressor gene that is implicated in the pathogenesis of cutaneous malignant melanoma, in normal skin and melanoma tissue samples. The study also aimed to correlate PTEN expression levels with various clinicopathological parameters of melanoma lesions, thus highlighting the utility of PTEN expression as a prognostic biomarker for melanoma. Study design Immunohistochemistry (IHC) staining was performed on tissue microarray samples representing normal skin and melanoma biopsies of different clinicopathological parameters. Tissue photomicrographs were evaluated with Aperio ImageScope, which has a positive-pixel-counting algorithm built in. Subsequently, a histochemical score (H-score) was derived from the percentage of positive cells (%-staining) and their staining intensity. The H-scores were averaged in groups of tissue samples representing the different melanomas' tumor (T), node (N), and distant metastasis (M), also known as TNM parameters, as set forth by the American Joint Committee on Cancer (AJCC) classification. The mean H-scores were statistically compared using a two-tailed unpaired t-test. Results The PTEN protein expression was measured by IHC and found to be correlated with tumor thickness (T), which is a reliable indicator for survival rates. Specifically, PTEN was significantly downregulated in tumors with a thickness over 2 mm (T3+T4) compared to tumors with a thickness at or below 2 mm (T1+T2). Conclusions The PTEN protein expression, as measured by immunohistochemistry, helped differentiate between tumors with a thickness over 2 mm and tumors with a thickness at or below 2 mm, suggesting PTEN as a potential surrogate marker for the melanoma's invasion depth along with possible prognostic implications. Longitudinal studies evaluating risk stratification based on the expression of PTEN are needed to establish the utility of this promising biomarker in the clinic as an adjunct for pathological examination.

Augmented and Virtual Reality for Preoperative Trauma Planning, Focusing on Orbital Reconstructions: A Systematic Review

BACKGROUND

This systematic review summarizes recent literature on the use of extended reality, including augmented reality (AR), mixed reality (MR), and virtual reality (VR), in preoperative planning for orbital fractures.

METHODS

A systematic search was conducted in PubMed, Embase, Web of Science and Cochrane on 6 April 2023. The included studies compared extended reality with conventional planning techniques, focusing on computer-aided surgical simulation based on Computed Tomography data, patient-specific implants (PSIs), fracture reconstruction of the orbital complex, and the use of extended reality. Outcomes analyzed were technical accuracy, planning time, operative time, complications, total cost, and educational benefits.

RESULTS

A total of 6381 articles were identified. Four articles discussed the educational use of VR, while one clinical prospective study examined AR for assisting orbital fracture management.

CONCLUSION

AR was demonstrated to ameliorate the accuracy and precision of the incision and enable the better identification of deep anatomical tissues in real time. Consequently, intraoperative imaging enhancement helps to guide the orientation of the orbital reconstruction plate and better visualize the precise positioning and fixation of the PSI of the fractured orbital walls. However, the technical accuracy of 2-3 mm should be considered. VR-based educational tools provided better visualization and understanding of craniofacial trauma compared to conventional 2- or 3-dimensional images.

Automated contour extraction for light-sheet microscopy images of zebrafish embryos based on object edge detection algorithm

Embryo contour extraction is the initial step in the quantitative analysis of embryo morphology, and it is essential for understanding the developmental process. Recent developments in light-sheet microscopy have enabled the in toto time-lapse imaging of embryos, including zebrafish. However, embryo contour extraction from images generated via light-sheet microscopy is challenging owing to the large amount of data and the variable sizes, shapes, and textures of objects. In this report, we provide a workflow for extracting the contours of zebrafish blastula and gastrula without contour labeling of an embryo. This workflow is based on the edge detection method using a change point detection approach. We assessed the performance of the edge detection method and compared it with widely used edge detection and segmentation methods. The results showed that the edge detection accuracy of the proposed method was superior to those of the Sobel, Laplacian of Gaussian, adaptive threshold, Multi Otsu, and k-means clustering-based methods, and the noise robustness of the proposed method was superior to those of the Multi Otsu and k-means clustering-based methods. The proposed workflow was shown to be useful for automating small-scale contour extractions of zebrafish embryos that cannot be specifically labeled owing to constraints, such as the availability of microscopic channels. This workflow may offer an option for contour extraction when deep learning-based approaches or existing non-deep learning-based methods cannot be applied.

Phosphotungstic Acid-treated Picrosirius Red Staining Improves Whole-slide Quantitative Analysis of Collagen in Histological Specimens

We tried to prevent nonspecific nuclear staining (NS-NS) of picrosirius red (PSR) staining by treating the specimens with one of the heteropoly acids phosphotungstic acid (PTA). We analyzed a total of 35 cases of non-cancerous liver tissue for fibrosis and NS-NS under PSR-alone, phosphomolybdic acid (PMA)-pretreated PSR (PMA + PSR), or PTA-pretreated PSR (PTA + PSR) condition. In addition, we analyzed the photosensitivity of PMA or PTA single stain specimens. PTA + PSR significantly suppressed NS-NS compared with PSR. The color of the specimens did not change into blue by 30 times the exposure to whole slide scanner (WSS) light. The PTA + PSR condition showed the highest correlation with the Ishak score (pathological evaluation of liver fibrosis) compared with other conditions. Furthermore, Sirius Red-positive percentage (SRP%) in PSR was increased in the NS-NS observed cases. SRP% in PMA + PSR was significantly affected by WSS light exposure time. Moreover, the deposition of non-polarized PSR-stained substances (NP-PSR+S) clinging to the collagen fibers potentially explains why SRP% seemed bigger under PSR than PTA + PSR. Our protocol enabled us to analyze the whole slide image of PSR staining by high magnification, which would contribute to the accurate analysis of collagen amount in the tissue sections.

Negative correlation between the nuclear size and nuclear Lamina component Lamin A in intraductal papillary mucinous neoplasms of the pancreas

Background: The nuclear laminar protein Lamin A and inner nuclear membrane protein Emerin plays important role in sustaining nuclear structure. However, They have not investigated the significance of these proteins for development of pancreatic intraductal papillary mucinous neoplasm (IPMN). Methods: We examined pancreatic IPMN specimens for nuclear morphology and nuclear protein expression pattern of Lamin A and Emerin. Forty-two IPMN specimens were included, with 30 classified as intraductal papillary mucinous adenoma (IPMA) and 12 as intraductal papillary mucinous carcinoma (IPMC). Results: Classification according to histological subtype revealed that 26 specimens were of the gastric subtype (1 IPMC case), 8 were pancreatobiliary (6 IPMC cases), 6 were intestinal (3 IPMC cases), and 2 were oncocytic (all cases were IPMC). The frequency of IPMN subtypes in this study seemed to agree with those in previous reports. We analyzed Feulgen staining sections for nuclear morphological analysis using computer-assisted image analysis. Nuclear area and perimeter were significantly larger in IPMC than in IPMA. Finally, we examined the positive ratios of Lamin A and Emerin in immunohistochemical staining sections by image analysis. We found a negative correlation between the nuclear size and Lamin A-positive ratio, which was significantly lower in IPMC than that in IPMA. However, no significant correlation was observed between nuclear size and Emerin expression was observed, and no differences were found in the Emerin-positive ratio between IPMA and IPMC. Conclusion: Our results suggest that a decreased Lamin A positive ratio induces nuclear enlargement in adenomas, which thereby induce promotion to carcinomas. Furthermore, Lamin A expression can be a reliable biomarker for distinguishing between IPMC and IPMA.

Cornulin as a Prognosticator for Lymph Node Involvement in Cutaneous Squamous Cell Carcinoma

Background Cornulin is an epidermal differentiation marker and a stress-related protein. Its expression patterns are likely to reflect the multi-step tumorigenesis process of cSCC, given its role as a tumor suppressor. The aim of this study is to evaluate the utility of Cornulin as a prognosticator for cutaneous squamous cell carcinoma (cSCC). Specifically, the correlation between Cornulin expression and the clinicopathological parameter of lymph node involvement (nodal status), which plays a major role in determining cSCC prognosis and recurrence. We predicted that Cornulin expression declines as cSCC tumors metastasize to regional lymph nodes. Methodology Tissue samples of cSCC lesions of variable nodal involvement status were stained using immunohistochemistry, and high-resolution images were acquired. Aperio ImageScope software (Leica Biosystems) equipped with a positive-pixel-counting algorithm was used to quantify the staining intensity. Subsequently, Cornulin immunoreactivity was calculated as a Histo-score (H-score) value, which is based on the staining intensity and the percentage of positively stained cells. Mean H-scores were compared between groups using an unpaired t-test. Results A significant inverse correlation was found between Cornulin expression levels and metastasis to the lymph nodes. Specifically, primary tumors with metastasis to regional lymph nodes (N1) exhibited 9.5-fold decrease in Cornulin immunoreactivity compared to the primary tumor samples without lymph node involvement (N0). Conclusion Cornulin was found to be significantly downregulated in primary tumors with lymph node metastases. Detection assays to measure Cornulin expression in cSCC primary tumors might aid in determining the nodal status in these patients and possibly help determine cases of occult lymph node metastasis or micrometastasis. Future clinical studies are needed to help establish Cornulin's role in enhancing the predictive power of histopathological examination and improving survival rates for patients suffering from this type of skin cancer.

Cornulin as a Potential Novel Biomarker for Cutaneous Squamous Cell Carcinoma

Background This study aimed to evaluate the expression of an epidermal differentiation marker, cornulin, in cutaneous squamous cell carcinoma (cSCC). Cornulin has been found to be downregulated in various squamous cell carcinomas of other tissues; however, its expression in cSCC has never been studied. We predicted that cornulin expression in cSCC is reduced compared to the normal epidermis. Moreover, we hypothesized that an inverse relationship exists between cornulin expression and the loss of differentiation, as defined by histopathological grading of cSCC lesions. Methodology Samples of normal skin and cSCC lesions of variable histopathological grades were stained using immunohistochemistry. High-resolution tissue images were analyzed with Aperio ImageScope (Leica Biosystems) utilizing a positive-pixel-counting algorithm to quantify the staining intensity. Histo-score (H-score) was calculated based on staining intensity and percentage of positive cell staining. Mean H-scores were compared using an unpaired t-test. Results We documented cornulin expression in cSCC for the first time. Cornulin levels were downregulated by more than two-fold in cSCC compared to the normal epidermis. Additionally, we observed a 4.5-fold downregulation in cornulin expression in tumors with high histopathological grades when compared to low histopathological grade tumors. Conclusions Cornulin expression levels measured through immunohistochemistry staining can help distinguish among the different histopathological grades of cSCC. Therefore, we propose that cornulin detection can be an adjunct to pathological examination to evaluate the differentiation status of cSCC specimens. Longitudinal studies are needed to establish the utility of cornulin as a diagnostic and prognostic biomarker for cSCC.

Application of artificial intelligence for diagnosis of pancreatic ductal adenocarcinoma by EUS: A systematic review and meta-analysis

EUS-guided tissue acquisition carries certain risks from unnecessary needle puncture in the low-likelihood lesions. Artificial intelligence (AI) system may enable us to resolve these limitations. We aimed to assess the performance of AI-assisted diagnosis of pancreatic ductal adenocarcinoma (PDAC) by off-line evaluating the EUS images from different modes. The databases PubMed, EMBASE, SCOPUS, ISI, IEEE, and Association for Computing Machinery were systematically searched for relevant studies. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic curve were estimated using R software. Of 369 publications, 8 studies with a total of 870 PDAC patients were included. The pooled sensitivity and specificity of AI-assisted EUS were 0.91 (95% confidence interval [CI], 0.87-0.93) and 0.90 (95% CI, 0.79-0.96), respectively, with DOR of 81.6 (95% CI, 32.2-207.3), for diagnosis of PDAC. The area under the curve was 0.923. AI-assisted B-mode EUS had pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 0.91, 0.90, 0.94, and 0.84, respectively; while AI-assisted contrast-enhanced EUS and AI-assisted EUS elastography had sensitivity, specificity, PPV, and NPV of 0.95, 0.95, 0.97, and 0.90; and 0.88, 0.83, 0.96 and 0.57, respectively. AI-assisted EUS has a high accuracy rate and may potentially enhance the performance of EUS by aiding the endosonographers to distinguish PDAC from other solid lesions. Validation of these findings in other independent cohorts and improvement of AI function as a real-time diagnosis to guide for tissue acquisition are warranted.

Scatter-to-primary ratio in dentomaxillofacial cone-beam CT: effect of field of view and beam energy

OBJECTIVE

The aim of this study was to evaluate the effect of field of view (FOV) and beam energy on the scatter-to-primary ratio (SPR) in dental cone-beam CT (CBCT).

METHODS

An anthropomorphic phantom representing an adult male (ATOM Max 711-HN, Norfolk, VA, USA) was scanned using the 3D Accuitomo 170 CBCT (J. Morita, Kyoto, Japan) using 11 FOVs. During each scan, half of the X-ray beam was blocked. Each scan was performed at three exposure settings with varying beam energy and equal radiation dose: 90 kV 5 mA, 77 kV 7.5 mA and 69 kV 10 mA. The SPR was estimated by measuring the grey values in the blocked and non-blocked regions of the RAW data. The effect of FOV on SPR was evaluated using Dunn's multiple comparison test, and the effect of the exposure settings was compared using a Wilcoxon signed rank test.

RESULTS

Larger FOVs showed increased scatter. FOVs with a shorter isocenter-detector distance showed a particularly high SPR. Most intercomparisons between FOVs were statistically significant. The largest difference was found between 17 × 12 cm and 6 × 6 cm (lower jaw), with the former showing a 4.9-fold higher SPR. The effect of beam energy was relatively small and varied between FOV sizes and positions.

CONCLUSION

While the choice of FOV size and position is determined by the diagnostic region of interest, the image quality deterioration for large FOVs due to scatter provides another incentive to limit the FOV size as much as possible.

Automated immunofluorescence analysis for sensitive and precise dystrophin quantification in muscle biopsies

Aims

Dystrophin, the protein product of the DMD gene, plays a critical role in muscle integrity by stabilising the sarcolemma during contraction and relaxation. The DMD gene is vulnerable to a variety of mutations that may cause complete loss, depletion or truncation of the protein, leading to Duchenne and Becker muscular dystrophies. Precise and reproducible dystrophin quantification is essential in characterising DMD mutations and evaluating the outcome of efforts to induce dystrophin through gene therapies. Immunofluorescence microscopy offers high sensitivity to low levels of protein expression along with confirmation of localisation, making it a critical component of quantitative dystrophin expression assays.

Methods

We have developed an automated and unbiased approach for precise quantification of dystrophin immunofluorescence in muscle sections. This methodology uses microscope images of whole‐tissue sections stained for dystrophin and spectrin to measure dystrophin intensity and the proportion of dystrophin‐positive coverage at the sarcolemma of each muscle fibre. To ensure objectivity, the thresholds for dystrophin and spectrin are derived empirically from non‐sarcolemmal signal intensity within each tissue section. Furthermore, this approach is readily adaptable for measuring fibre morphology and other tissue markers.

Results

Our method demonstrates the sensitivity and reproducibility of this quantification approach across a wide range of dystrophin expression in both dystrophinopathy patient and healthy control samples, with high inter‐operator concordance.

Conclusion

As efforts to restore dystrophin expression in dystrophic muscle bring new potential therapies into clinical trials, this methodology represents a valuable tool for efficient and precise analysis of dystrophin and other muscle markers that reflect treatment efficacy.

Role of Lamin A and emerin in maintaining nuclear morphology in different subtypes of ovarian epithelial cancer

The nuclear lamina protein, Lamin A and inner nuclear membrane protein, emerin participate in maintaining nuclear morphology. However, their correlations with the nuclear shape in the four representative ovarian epithelial cancer subtypes, high-grade serous carcinoma (HGSCa), clear cell carcinoma (CCCa), endometrioid carcinoma (EMCa) and mucinous carcinoma (MUCa), remains unclear. The present study aimed to investigate the association between nuclear morphology and nuclear membrane protein expression in four histological subtypes of ovarian epithelial cancer. A total of 140 surgically resected ovarian cancer specimens were subjected to Feulgen staining to evaluate nuclear morphology, and immunohistochemistry analysis to assess Lamin A and emerin expression. The histological images were analyzed via computer-assisted image analysis (CAIA). The results demonstrated that the mean nuclear area of EMCa was significantly smaller compared with CCCa (P=0.0009). The standard deviation of the mean nuclear area was used to assess nuclear size variation, and the results indicated that EMCa lesions were significantly smaller than CCCa lesions (P=0.0006). Regarding the correlation between the Lamin A-positive rate and nuclear morphological factors, positive correlations were observed with nuclear area in CCCa and EMCa (R=0.2855 and R=0.2858, respectively) and nuclear perimeter in CCCa, EMCa and MUCa (R=0.2409, R=0.4054 and R=0.2370, respectively); however, a negative correlation with nuclear shape factor was observed in HGSCa and EMCa (R=-0.2079 and R=-0.3707, respectively). With regards to the correlation between emerin positivity and nuclear morphological factors, positive correlations were observed with nuclear shape factor in HGSCa (R=0.2673) and nuclear area in CCCa (R=0.3310). It is well-known that HGSCa and CCCa have conspicuous nuclear size variation, and EMCa has small nuclei without strong atypia. These findings were verified in the present study via CAIA. Taken together, the results of the present study suggest that Lamin A strongly contributes to the maintenance of nuclear morphology in ovarian epithelial cancer compared with emerin, although their contributions differ based on tumor subtype.

Computer-assisted image analysis of cytological specimens clarify the correlation between nuclear size and intranuclear cytoplasmic inclusions regardless of BRAFV600E mutation in papillary thyroid carcinoma

OBJECTIVE

The morphological features of nuclei in cytological and histological specimens were compared and examined for the presence of BRAFV600E mutation and the appearance rate of intranuclear cytoplasmic inclusions (NI).

METHODS

BRAFV600E mutation was identified using a mutation-specific antibody (clone; VE1) in 103 thyroid papillary carcinoma cases at Gunma University Hospital. The nuclear area, perimeter, and roundness of the corresponding cytological specimens and haematoxylin and eosin-stained specimens were analysed using image analysis software, and the appearance rate of NI was calculated and compared.

RESULTS

BRAFV600E mutation was detected in 71 (69%) cases. The appearance rate of NI was significantly higher in the BRAFV600E mutation-positive group in cytological and histological specimens (P = .0070 and .0184, respectively). Significant differences were observed between the BRAFV600E mutation-negative and -positive groups in the average nuclear area and average nuclear perimeter in cytological specimens (P = .0137 and .0152, respectively). In addition, nuclear enlargement was correlated with the appearance rate of NI regardless of the presence of BRAFV600E mutation in cytological specimens. In the BRAFV600E mutation-negative group, the nuclear area and perimeter were significantly smaller in the lymph node metastasis-positive cases (P = .0182 and .0260, respectively).

CONCLUSION

This study found that the appearance rate of NI was positively correlated with the nuclear area and perimeter and negatively correlated with nuclear roundness in cytological specimens. Furthermore, these results were observed regardless of the existence of BRAFV600E mutation. These results have never been previously reported and clearly demonstrate the usefulness of cytological specimens in computer-assisted image analysis.

Interstitial lung disease in systemic sclerosis quantification of disease classification and progression with high-resolution computed tomography: An observational study

INTRODUCTION

Systemic sclerosis-associated interstitial lung disease accounts for up to 20% of mortality in these patients and has a highly variable prognosis. Functional respiratory imaging, a quantitative computed tomography imaging technique which allows mapping of regional information, can provide a detailed view of lung structures. It thereby shows potential to better characterize this disease.

PURPOSE

To evaluate the use of functional respiratory imaging quantitative computed tomography in systemic sclerosis-associated interstitial lung disease staging, as well as the relationship between short-term changes in pulmonary function tests and functional respiratory imaging quantitative computed tomography with respect to disease severity.

MATERIALS AND METHODS

An observational cohort of 35 patients with systemic sclerosis was retrospectively studied by comparing serial pulmonary function tests and in- and expiratory high-resolution computed tomography over 1.5-year interval. After classification into moderate to severe lung disease and limited lung disease (using a hybrid method integrating quantitative computed tomography and pulmonary function tests), post hoc analysis was performed using mixed-effects models and estimated marginal means in terms of functional respiratory imaging parameters.

RESULTS

At follow-up, relative mean forced vital capacity percentage change was not significantly different in the limited (6.37%; N = 13; p = 0.053) and moderate to severe disease (-3.54%; N = 16; p = 0.102) groups, respectively. Specific airway resistance decreased from baseline for both groups. (Least square mean changes -25.11% predicted (p = 0.006) and -14.02% predicted (p = 0.001) for limited and moderate to severe diseases.) In contrast to limited disease from baseline, specific airway radius increased in moderate to severe disease by 8.57% predicted (p = 0.011) with decline of lower lobe volumes of 2.97% predicted (p = 0.031).

CONCLUSION

Functional respiratory imaging is able to differentiate moderate to severe disease versus limited disease and to detect disease progression in systemic sclerosis.

Utility of Multi-Modal MRI for Differentiating of Parkinson's Disease and Progressive Supranuclear Palsy Using Machine Learning

Background: Patients with Parkinson's disease (PD) and progressive supranuclear palsy Richardson's syndrome (PSP-RS) often show overlapping clinical features, leading to misdiagnoses. The objective of this study was to investigate the feasibility and utility of using multi-modal MRI datasets for an automatic differentiation of PD patients, PSP-RS patients, and healthy control (HC) subjects. Material and Methods: T1-weighted, T2-weighted, and diffusion-tensor (DTI) MRI datasets from 45 PD patients, 20 PSP-RS patients, and 38 HC subjects were available for this study. Using an atlas-based approach, regional values of brain morphology (T1-weighted), brain iron metabolism (T2-weighted), and microstructural integrity (DTI) were measured and employed for feature selection and subsequent classification using combinations of various established machine learning methods. Results: The optimal machine learning model using regional morphology features only achieved a classification accuracy of 65% (67/103 correct classifications) differentiating PD patients, PSP-RS patients, and HC subjects. The optimal machine learning model using only quantitative T2 values performed slightly better and achieved an accuracy of 75.7% (78/103). The optimal classifier using DTI features alone performed considerably better with 95.1% accuracy (98/103). The optimal multi-modal classifier using all features also achieved an accuracy of 95.1% but required more features and achieved a slightly lower F1-score compared to the optimal model using DTI features alone. Conclusion: Machine learning models using multi-modal MRI perform significantly better than uni-modal machine learning models using morphological parameters based on T1-weighted MRI datasets alone or brain iron metabolism markers based on T2-weighted MRI datasets alone. However, machine learnig models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to the optimal multi-modal machine learning model. Thus, given the results from this study cohort, it appears that morphology and brain iron metabolism markers may not provide additional value for classification compared to using DTI metrics alone.

Ryanodine Receptor 1-Related Myopathies: Quantification of Intramuscular Fatty Infiltration from T1-Weighted MRI

Background:

Ryanodine receptor 1-related myopathy (RYR1-RM) can present with a selective pattern and gradient of intramuscular fatty infiltration (IMFI) on magnetic resonance imaging (MRI).

Objective:

To demonstrate an automated protocol for quantification of IMFI in the lower extremity muscles of individuals with RYR1-RM using T1-weighted MRI and to examine the relationships of IMFI with motor function and clinical severity.

Methods:

Axial images of the lower extremity muscles were acquired by T1-weighted fast spin-echo and short tau inversion recovery (STIR) sequences. A modified ImageJ-based program was used for quantification. IMFI data was analyzed by mode of inheritance, motor function, and clinical severity.

Results:

Upper and lower leg IMFI from 36 genetically confirmed and ambulatory RYR1-RM affected individuals (26 dominant and 10 recessive) were analyzed using Grey-scale quantification. There was no statistically significant difference in IMFI between dominant and recessive cases in upper or lower legs. IMFI in both upper and lower legs was inversely correlated with participant performance on the motor function measure (MFM-32) total score (upper leg: p < 0.001; lower leg: p = 0.003) and the six-minute walk test (6MWT) distance (upper leg: p < 0.001; lower leg: p = 0.010). There was no significant difference in mean IMFI between participants with mild versus severe clinical phenotypes (p = 0.257).

Conclusion:

A modified ImageJ-based algorithm was able to select and quantify fatty infiltration in a cohort of heterogeneously affected individuals with RYR1-RM. IMFI was not predictive of mode of inheritance but showed strong correlation with motor function and capacity tests including MFM-32 and 6MWT, respectively.

Is it possible to estimate volume of bone defects formed on dry sheep mandibles more practically by secondarily reconstructing section thickness of cone beam computed tomography images?

OBJECTIVES

The purpose of this study was to evaluate the effect of section thickness on volume estimations of bone defects scanned using cone beam computed tomography (CBCT).

METHODS

25 bone defects were prepared on sheep mandibles and scanned using a KaVo 3D eXam (KaVo Dental, Biberach, Germany) CBCT device. Section thickness of images were reconstructed at 0.25, 0.5, and 0.75 mm to estimate the volume of these defects using the semiautomatic segmentation method. The volume averages obtained using microcomputed tomography and Archimedes' method served as reference values. The estimated volumes at each section thickness were compared with the actual volumes using the Friedman test. The accuracy of volume estimation was determined by the percentage error with respect to the reference values, and the mean absolute error (MAE) was calculated.

RESULTS

Volumetric values of bone defects obtained with CBCT at section thicknesses up to 0.5 mm were compatible with the actual volumes (p > 0.05). The percentage errors at section thicknesses of 0.25, 0.5, and 0.75 mm were -5.4%, -7.3%, and -13.1%, respectively. The mean absolute errors were 13.6 mm³, 15.7 mm³, and 18.2 mm³, respectively.

CONCLUSIONS

The section thickness values of CBCT images can be increased to a reasonable level to obtain accurate volume estimation results and save time. The semiautomatic segmentation method can be used reliably for volume estimations of bone defects.

Opportunistic Osteoporosis Screening Reveals Low Bone Density in Patients With Screw Loosening After Lumbar Semi-Rigid Instrumentation: A Case-Control Study

Objective

Decreased bone mineral density (BMD) impairs screw purchase in trabecular bone and can cause screw loosening following spinal instrumentation. Existing computed tomography (CT) scans could be used for opportunistic osteoporosis screening for decreased BMD. Purpose of this case-control study was to investigate the association of opportunistically assessed BMD with the outcome after spinal surgery with semi-rigid instrumentation for lumbar degenerative instability.

Methods

We reviewed consecutive patients that had primary surgery with semi-rigid instrumentation in our hospital. Patients that showed screw loosening in follow-up imaging qualified as cases. Patients that did not show screw loosening or-if no follow-up imaging was available (n = 8)-reported benefit from surgery ≥ 6 months after primary surgery qualified as controls. Matching criteria were sex, age, and surgical construct. Opportunistic BMD screening was performed at L1 to L4 in perioperative CT scans by automatic spine segmentation and using asynchronous calibration. Processing steps of this deep learning-driven approach can be reproduced using the freely available online-tool Anduin (https://anduin.bonescreen.de). Area under the curve (AUC) was calculated for BMD as a predictor of screw loosening.

Results

Forty-six elderly patients (69.9 ± 9.1 years)-23 cases and 23 controls-were included. The majority of surgeries involved three spinal motion segments (n = 34). Twenty patients had low bone mass and 13 had osteoporotic BMD. Cases had significantly lower mean BMD (86.5 ± 29.5 mg/cm³) compared to controls (118.2 ± 32.9 mg/cm³, p = 0.001), i.e. patients with screw loosening showed reduced BMD. Screw loosening was best predicted by a BMD < 81.8 mg/cm³ (sensitivity = 91.3%, specificity = 56.5%, AUC = 0.769, p = 0.002).

Conclusion

Prevalence of osteoporosis or low bone mass (BMD ≤ 120 mg/cm³) was relatively high in this group of elderly patients undergoing spinal surgery. Screw loosening was associated with BMD close to the threshold for osteoporosis (< 80 mg/cm³). Opportunistic BMD screening is feasible using the presented approach and can guide the surgeon to take measures to prevent screw loosening and to increase favorable outcomes.

Improved Reliability of Automated ASPECTS Evaluation Using Iterative Model Reconstruction from Head CT Scans

BACKGROUND AND PURPOSE

Iterative model reconstruction (IMR) has shown to improve computed tomography (CT) image quality compared to hybrid iterative reconstruction (HIR). Alberta Stroke Program Early CT Score (ASPECTS) assessment in early stroke is particularly dependent on high-image quality. Purpose of this study was to investigate the reliability of ASPECTS assessed by humans and software based on HIR and IMR, respectively.

METHODS

Forty-seven consecutive patients with acute anterior circulation large vessel occlusions (LVOs) and successful endovascular thrombectomy were included. ASPECTS was assessed by three neuroradiologists (one attending, two residents) and by automated software in noncontrast axial CT with HIR (iDose4; 5 mm) and IMR (5 and 0.9 mm). Two expert neuroradiologists determined consensus ASPECTS reading using all available image data including MRI. Agreement between four raters (three humans, one software) and consensus were compared using square-weighted kappa (κ).

RESULTS

Human raters achieved moderate to almost perfect agreement (κ = .557-.845) with consensus reading. The attending showed almost perfect agreement for 5 mm HIR (κ_HIR  = .845), while residents had mostly substantial agreements without clear trends across reconstructions. Software had substantial to almost perfect agreement with consensus, increasing with IMR 5 and 0.9 mm slice thickness (κ_HIR  = .751, κ_IMR  = .777, and κ_IMR0.9  = .814). Agreements inversely declined for these reconstructions for the attending (κ_HIR  = .845, κ_IMR  = .763, and κ_IMR0.9  = .681).

CONCLUSIONS

Human and software rating showed good reliability of ASPECTS across different CT reconstructions. Human raters performed best with the reconstruction algorithms they had most experience with (HIR for the attending). Automated software benefits from higher resolution with better contrasts in IMR with 0.9 mm slice thickness.

Macrophages in Giemsa-stained cerebrospinal fluid specimens predict carcinomatous meningitis

Carcinomatous meningitis is a condition in which tumor cells spread to the subarachnoid space. Leukocyte counting and typing of cerebrospinal fluid (CSF) cell components are performed manually or using flow cytometry. However, a detailed analysis of these variables using cytological specimens has not yet been reported. The present study analyzed cytological specimens using Giemsa staining and whole slide imaging with computer-assisted image analysis (CAIA) to clarify the characteristics of the leukocyte population in CSF, especially in carcinomatous meningitis. Manual evaluation was performed using 280 Giemsa-stained cytological CSF specimens. For 49 samples, CAIA was used for the whole area of Papanicolaou (Pap) staining, and Giemsa-stained specimens of the same samples were imaged using a virtual slide scanner. The nuclear morphology of the leukocytes was assessed, and the total leukocyte and leukocyte subset (lymphocytes, neutrophils and macrophages) counts were evaluated. Then, the number and percentage of each leukocyte subset population were evaluated. The total leukocyte count was significantly higher in Giemsa-stained specimens compared with in Pap-stained specimens. The percentage of macrophages was significantly higher in samples from patients with non-hematological tumors compared with in samples from patients without tumors, which was confirmed by manual evaluation of the specimens. In addition, the cut-off value of the percentage of macrophages that could discriminate between the tumor history negative cases and cytologically tumor positive cases was determined, revealing that a higher proportion of macrophages reflected the existence of atypical/malignant epithelial tumor cells in CSF samples. Thus, atypical cell screening and analysis of the background characteristics of the leukocyte population should be the focus of cytological specimen screening, especially not to miss carcinomatous meningitis.

Phosphomolybdic Acid Prevents Nonspecific Nuclear Staining by Picrosirius Red but Is Converted to Molybdenum Blue by Blue Light

Picrosirius red (PSR) staining is generally used to evaluate liver fibrosis; however, PSR sometimes causes nonspecific nuclear staining. In this study, we evaluated the ability of phosphomolybdic acid (PMA) pretreatment to prevent nonspecific nuclear staining by PSR. In a manual evaluation of 27 non-tumor samples from patients with hepatocellular carcinoma, nonspecific nuclear staining was observed in 3.7% of PMA-treated specimens, compared with 85.2% of untreated specimens. Conversely, computer-assisted image analysis (CAIA) identified nonspecific nuclear staining in 0% of PMA-treated samples, vs 44.4% of untreated samples. Surprisingly, after mounting, PMA-treated specimens exhibited a blue tinge because of molybdenum blue (MB) production following sunlight exposure or virtual slide scanning. Using UV cut film, MB production induced by sunlight exposure was prevented; however, the film did not prevent MB production during virtual slide scanning. Moreover, only blue light-emitting diode exposure resulted in a blue tinge in PMA solution. Our data indicated that PMA pretreatment is effective for evaluating liver fibrosis using CAIA. Meanwhile, improvements in virtual slide scanning protocols would directly improve the quality of PMA-pretreated specimens subjected to CAIA.

Computer-assisted measurements of the histological structure of the tibial nerve and its terminal branches

BACKGROUND

The aim of this study was to analyse the histological structure (cross-sectional area [CSA] and number of nerve bundles) of the distal part of the tibial nerve and its terminal branches (medial plantar nerve, lateral plantar nerve) using computer-assisted image analysis.

MATERIALS AND METHODS

The tibial nerve and its distal branches (medial and lateral plantar nerves) were dissected from the fresh cadavers. Each nerve was harvested 5 mm proximally and respectively 5 mm distally from the tibial nerve bifurcation, marked, dehydrated, embedded in paraffin, sectioned at 2 μm slices and stained with haematoxylin and eosin. Then photographed and analysed using Olympus cellSens software.

RESULTS

The studied group comprised 28 female and 32 male feet (mean age 68.1 ± 15.2 years). The mean CSA and the number of nerve bundles were respectively 17.86 ± 4.57 mm2, 33.88 ± 6.31 for the tibial nerve, 9.58 ± 1.95 mm2, 23.41 ± 7.37 for the medial plantar nerve and 7.17 ± 2.36 mm2, 15.06 ± 5.81 for the lateral plantar nerve in males and 12.27 ± 2.45 mm2, 26.32 ± 8.87 for the tibial nerve, 7.81 ± 1.41 mm2, 17.71 ± 5.28 for the medial plantar nerve and 5.83 ± 1.25 mm2, 11.50 ± 3.72 for the lateral plantar nerve in females. Both CSA and number of nerve bundles of the tibial, medial plantar and lateral plantar nerves revealed no statistical differences when comparing foot side of the individual. The statistical difference was related to the gender, showing significantly bigger CSA and number of nerve bundles in males (CSA: p = 0.000, p = 0.000, p = 0.016; number of nerve bundles: p = 0.01, p = 0.003, p = 0.004, respectively). A positive correlation was found between the donor age and the tibial nerve CSA (r = 0.44, p = 0.000). A significant statistical difference was found between the medial and lateral plantar nerves both in CSA and number of nerve bundles (p < 0.001, p < 0.001, respectively).

CONCLUSIONS

The CSA and the number of nerve bundles in the distal part of the tibial nerve and its branches are significantly larger in males with no differences between right and left foot of the individual. The tibial nerve shows increasing CSA with advanced age. The medial plantar nerve has larger CSA and more nerve bundles than the lateral plantar nerve.

Structural integrity of white matter tracts as a predictor of acute ischemic stroke outcome

BACKGROUND AND PURPOSE

Clinical assessment scores in acute ischemic stroke are only moderately correlated with lesion volume since lesion location is an important confounding factor. Many studies have investigated gray matter indicators of stroke severity, but the understanding of white matter tract involvement is limited in the early phase after stroke. This study aimed to measure and model the involvement of white matter tracts with respect to 24-h post-stroke National Institutes of Health Stroke Scale (NIHSS).

MATERIAL AND METHODS

A total of 96 patients (50 females, mean age 66.4 ± 14.0 years, median NIHSS 5, interquartile range: 2-9.5) with follow-up fluid-attenuated inversion recovery magnetic resonance imaging data sets acquired one to seven days after acute ischemic stroke onset due to proximal anterior circulation occlusion were included. Lesions were semi-automatically segmented and non-linearly registered to a common reference atlas. The lesion overlap and tract integrity were determined for each white matter tract in the AALCAT atlas and used to model NIHSS outcomes using a supervised linear-kernel support vector regression method, which was evaluated using leave-one-patient-out cross validation.

RESULTS

The support vector regression model using the tract integrity and tract lesion overlap measurements predicted the 24-h NIHSS score with a high correlation value of r = 0.7. Using the tract overlap and tract integrity feature improved the modeling accuracy of NIHSS significantly by 6% (p < 0.05) compared to using overlap measures only.

CONCLUSION

White matter tract integrity and lesion load are important predictors for clinical outcome after an acute ischemic stroke as measured by the NIHSS and should be integrated for predictive modeling.

What's New on Quantitative CT Analysis as a Tool to Predict Growth in Persistent Pulmonary Subsolid Nodules? A Literature Review

Pulmonary subsolid nodules (SSNs) are observed not infrequently on thin-section chest computed tomography (CT) images. SSNs persisting after a follow-up period of three to six months have a high likelihood of being pre-malignant or malignant lesions. Malignant SSNs usually represent the histologic spectrum of pulmonary adenocarcinomas, and pulmonary adenocarcinomas presenting as SSNs exhibit quite heterogeneous behavior. In fact, while most lesions show an indolent course and may grow very slowly or remain stable for many years, others may exhibit significant growth in a relatively short time. Therefore, it is not yet clear which persistent SSNs should be surgically removed and for how many years stable SSNs should be monitored. In order to solve these two open issues, the use of quantitative analysis has been proposed to define the "tailored" management of persistent SSNs. The main purpose of this review was to summarize recent results about quantitative CT analysis as a diagnostic tool for predicting the behavior of persistent SSNs. Thus, a literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science databases to find original articles published from January 2014 to October 2019. The results of the selected studies are presented and compared in a narrative way.

Unlabeled image analysis-based cell viability assay with intracellular movement monitoring

The need for technologies to monitor cell health is increasing with advancements in the field of cell therapy and regenerative medicine. In this study, we demonstrated unlabeled optical metabolic imaging of cultured living cells. This imaging technique is based on motion vector analysis with a block-matching algorithm to compare sequential time-lapse images. Motion vector analysis evaluates the movement of intracellular granules observed with a phase-contrast microscope. We demonstrated that the motion speed of intracellular movement reflects adenosine triphosphate (ATP)-dependent intracellular trafficking in cells. We also confirmed that intracellular motion speed is correlated with the ATP concentrations of the cells. This assay can measure cellular viability at a single-cell level without requiring any reagents.

Solid Indeterminate Pulmonary Nodules of Less Than 300 mm3: Application of Different Volume Doubling Time Cut-offs in Clinical Practice

In the British Thoracic Society guidelines for incidental pulmonary nodules, volumetric analysis has become the recommended method for growth assessment in solid indeterminate pulmonary nodules (SIPNs) <300 mm³. In these guidelines, two different volume doubling time (VDT) cut-offs, 400 and 600 days, were proposed to differentiate benign from malignant nodules. The present study aims to evaluate the performance of these VDT cut-offs in a group of SIPNs <300 mm³ which were incidentally detected in a routine clinical setting. During a 7-year period, we retrospectively selected 60 patients with a single SIPN <300 mm³. For each SIPN, the volume and VDT were calculated using semiautomatic software throughout the follow-up period, and the performance of the 400- and 600-day VDT cut-offs was compared. In the selected sample, there were 38 benign and 22 malignant nodules. In this group of nodules, the sensitivity, negative predictive value and accuracy of the 600-day VDT cut-off were higher than those of the 400-day VDT cut-off. Therefore, in the management of SIPNs <300 mm³ which were incidentally detected in a clinical setting, the 600-day VDT cut-off was better at differentiating benign from malignant nodules than the 400-day VDT cut-off, by reducing the number of false negatives.

Large-depth-of-field full-field optical angiography

A large-depth-of-field full-field optical angiography (LD-FFOA) method is developed to expand the depth-of-field (DOF) using a contrast pyramid fusion algorithm (CPFA). The absorption intensity fluctuation modulation effect is utilized to obtain full-field optical angiography (FFOA) images at different focus positions. The CPFA is used to process these FFOA images with different focuses. By selecting high-contrast areas, the CPFA can highlight the characteristics and details of blood vessels to obtain LD-FFOA images. In the optimal case of the proposed method, the DOF for FFOA is more than tripled using 10 differently focused FFOA images. Both the phantom and animal experimental results show that the LD-FFOA resolves FFOA defocusing issues induced by surface and thickness inhomogeneities in biological samples. The proposed method can be potentially applied to practical biological experiments.

Preoperative low skeletal muscle mass as a risk factor for pharyngocutaneous fistula and decreased overall survival in patients undergoing total laryngectomy

Background

Low skeletal muscle mass (SMM) is associated with postoperative complications, prolonged hospital stay, and short overall survival (OS) in surgical oncology. We aimed to investigate this association in patients undergoing total laryngectomy (TL).

Methods

A retrospective study was performed of patients undergoing TL. SMM was measured using CT or MRI scans at the level of the third cervical vertebra (C3).

Results

In all, 235 patients were included. Low SMM was observed in 109 patients (46.4%). Patients with low SMM had more pharyngocutaneous fistulas (PCFs) than patients with normal SMM (34.9% vs 20.6%; P = .02) and prolonged hospital stay (median, 17 vs 14 days; P < .001). In multivariate analysis, low SMM (hazards ratio, 1.849; 95% confidence interval, 1.202‐2.843) and high N stage were significant prognosticators of decreased OS.

Conclusion

Low SMM is associated with PCF and prolonged hospital stay in patients undergoing TL. Low SMM is an independent prognostic factor for shorter OS.

A novel method for automated assessment of megakaryocyte differentiation and proplatelet formation

Transfusion of platelet concentrates represents an important treatment for various bleeding complications. However, the short half-life and frequent contaminations with bacteria restrict the availability of platelet concentrates and raise a clear demand for platelets generated ex vivo. Therefore, in vitro platelet generation from megakaryocytes represents an important research topic. A vital step for this process represents accurate analysis of thrombopoiesis and proplatelet formation, which is usually conducted manually. We aimed to develop a novel method for automated classification and analysis of proplatelet-forming megakaryocytes in vitro. After fluorescent labelling of surface and nucleus, MKs were automatically categorized and analysed with a novel pipeline of the open source software CellProfiler. Our new workflow is able to detect and quantify four subtypes of megakaryocytes undergoing thrombopoiesis: proplatelet-forming, spreading, pseudopodia-forming and terminally differentiated, anucleated megakaryocytes. Furthermore, we were able to characterize the inhibitory effect of dasatinib on thrombopoiesis in more detail. Our new workflow enabled rapid, unbiased, quantitative and qualitative in-depth analysis of proplatelet formation based on morphological characteristics. Clinicians and basic researchers alike will benefit from this novel technique that allows reliable and unbiased quantification of proplatelet formation. It thereby provides a valuable tool for the development of methods to generate platelets ex vivo and to detect effects of drugs on megakaryocyte differentiation.

Effect of starvation and refeeding on the hepatopancreas of whiteleg shrimp Penaeus vannamei (Boone) using computer-assisted image analysis

Under normal farming conditions, shrimp can experience starvation periods attributable to disease outbreaks or adverse environmental conditions. Starvation leads to significant morphological changes in the hepatopancreas (HP), being the main organ for absorption and storage of nutrients. In the literature, limited research has described the effect on the HP of periods of starvation followed by refeeding and none in whiteleg shrimp (Penaeus vannamei) using computer-assisted image analysis (CAIA). This study describes the effect of starvation and starvation followed by refeeding on the HP of whiteleg shrimp using CAIA. Visiopharm^® software was used to quantify the following morphological parameters, measured as ratio to the total tissue area (TLA): total lumen area (TLA:TTA), haemocytic infiltration area in the intertubular spaces (HIA:TTA), B-cell vacuole area (VBA:TTA), lipid droplet area within R cells (LDA:TTA) and F-cell area (FCA:TTA). Significant changes were measured for HIA:TTA and LDA:TTA during starvation (increase in HIA:TTA associated with decrease in LDA:TTA) and starvation followed by refeeding (decrease in HIA:TTA associated with increase in LDA:TTA). In the future, HIA:TTA and LDA:TTA have the potential to be used in a pre-emptive manner to monitor the health of the HP, facilitate early diagnosis of diseases and study the pathophysiology of the organ.

Use of computer-assisted image analysis for semi-quantitative histology of the hepatopancreas in whiteleg shrimp Penaeus vannamei (Boone)

Despite the increasing use of novel molecular techniques in pathology, histology remains the standard method for monitoring tissue alterations and for assessing pathology. Histopathological evaluation is generally laborious and subjective with risk of discrepancies in semi-quantitative scoring between pathologists. In contrast, computer-assisted image analysis (CAIA) is potentially faster, more objective and thus suitable for routine screening. Limited research has been carried out on CAIA in crustacean histopathology, and the methods described were not fully automated. Therefore, the aim of this study was to develop CAIA in whiteleg shrimp (Penaeus vannamei) for the study of the hepatopancreas. Paraffin sections were immunohistochemically stained with monoclonal antibodies WSH8 against haemocytes and counterstained with Mayer's haematoxylin for detection of haemocytes and B-cell vacuoles, and modified toluidine blue protocol was used for detection of F-cells; frozen sections were stained with Oil Red O for detection of lipid droplets within R-cells. Visiopharm^® software was used to develop and validated protocols for the quantification of morphological parameters (areas of haemocyte infiltration, F-cells, B-cell vacuoles, lipid droplets and their ratios to total tissue area and total lumen area). These protocols enable the future use of CAIA for determination of the nutritional and pathological condition of this organ.

Quantitative tumor heterogeneity assessment on a nuclear population basis

Immunohistochemistry Ki-67 stain is widely used for visualizing cell proliferation. The common method for scoring the proliferation is to manually select and score a hot spot. This method is time-consuming and will often not give reproducible results due to subjective selection of the hotspots and subjective scoring. An automatic hotspot detection and proliferative index scoring would be time-saving, make the determination of the Ki-67 score easier and minimize the uncertainty of the score by introducing a more objective and standardized score. Tissue Micro Array cores stained for Ki-67 and their neighbor slide stained for Pan Cytokeratin were aligned and Ki-67 positive and negative nuclei were identified inside tumor regions. A heatmap was calculated based on these and illustrates the distribution of the heterogenous response of Ki-67 positive nuclei in the tumor tissue. An automatic hot spot detection was developed and the Ki-67 score was calculated. All scores were compared with scores provided by a pathologist using linear regression models. No significant difference was found between the Ki-67 scores guided by the developed heatmap and the scores provided by a pathologist. For comparison, scores were also calculated at a random place outside the hot spot and these scores were found to be significantly different from the pathologist scores. A heatmap visualizing the heterogeneity in tumor tissue expressed by Ki-67 was developed and used for an automatic identification of hot spots in which a Ki-67 score was calculated. The Ki-67 scores did not differ significantly from scores provided by a pathologist. © 2017 International Society for Advancement of Cytometry.

Development and Validation of an Automatic Segmentation Algorithm for Quantification of Intracerebral Hemorrhage

BACKGROUND AND PURPOSE

ABC/2 is still widely accepted for volume estimations in spontaneous intracerebral hemorrhage (ICH) despite known limitations, which potentially accounts for controversial outcome-study results. The aim of this study was to establish and validate an automatic segmentation algorithm, allowing for quick and accurate quantification of ICH.

METHODS

A segmentation algorithm implementing first- and second-order statistics, texture, and threshold features was trained on manual segmentations with a random-forest methodology. Quantitative data of the algorithm, manual segmentations, and ABC/2 were evaluated for agreement in a study sample (n=28) and validated in an independent sample not used for algorithm training (n=30).

RESULTS

ABC/2 volumes were significantly larger compared with either manual or algorithm values, whereas no significant differences were found between the latter (P<0.0001; Friedman+Dunn's multiple comparison). Algorithm agreement with the manual reference was strong (concordance correlation coefficient 0.95 [lower 95% confidence interval 0.91]) and superior to ABC/2 (concordance correlation coefficient 0.77 [95% confidence interval 0.64]). Validation confirmed agreement in an independent sample (algorithm concordance correlation coefficient 0.99 [95% confidence interval 0.98], ABC/2 concordance correlation coefficient 0.82 [95% confidence interval 0.72]). The algorithm was closer to respective manual segmentations than ABC/2 in 52/58 cases (89.7%).

CONCLUSIONS

An automatic segmentation algorithm for volumetric analysis of spontaneous ICH was developed and validated in this study. Algorithm measurements showed strong agreement with manual segmentations, whereas ABC/2 exhibited its limitations, yielding inaccurate overestimations of ICH volume. The refined, yet time-efficient, quantification of ICH by the algorithm may facilitate evaluation of clot volume as an outcome predictor and trigger for surgical interventions in the clinical setting.

Segmentation of facial bone surfaces by patch growing from cone beam CT volumes

OBJECTIVES

The motivation behind this work was to design an automatic algorithm capable of segmenting the exterior of the dental and facial bones including the mandible, teeth, maxilla and zygomatic bone with an open surface (a surface with a boundary) from CBCT images for the anatomy-based reconstruction of radiographs. Such an algorithm would provide speed, consistency and improved image quality for clinical workflows, for example, in planning of implants.

METHODS

We used CBCT images from two studies: first to develop (n = 19) and then to test (n = 30) a segmentation pipeline. The pipeline operates by parameterizing the topology and shape of the target, searching for potential points on the facial bone-soft tissue edge, reconstructing a triangular mesh by growing patches on from the edge points with good contrast and regularizing the result with a surface polynomial. This process is repeated for convergence.

RESULTS

The output of the algorithm was benchmarked against a hand-drawn reference and reached a 0.50 ± 1.0-mm average and 1.1-mm root mean squares error in Euclidean distance from the reference to our automatically segmented surface. These results were achieved with images affected by inhomogeneity, noise and metal artefacts that are typical for dental CBCT.

CONCLUSIONS

Previously, this level of accuracy and precision in dental CBCT has been reported in segmenting only the mandible, a much easier target. The segmentation results were consistent throughout the data set and the pipeline was found fast enough (<1-min average computation time) to be considered for clinical use.

Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study

Background

Computed tomography (CT) is often viewed as one of the most accurate methods for measuring visceral adipose tissue (VAT). However, measuring VAT and subcutaneous adipose tissue (SAT) from CT is a time-consuming and tedious process. Thus, evaluating patients’ obesity levels during clinical trials using CT scans is both cumbersome and limiting.

Objective

To describe an image-processing-based and automated method for measuring adipose tissue in the entire abdominal region.

Methods

The method detects SAT and VAT levels using a separation mask based on muscles of the human body. The separation mask is the region that minimizes the unnecessary space between a closed path and muscle area. In addition, a correction mask, based on bones, corrects the error in VAT.

Results

To validate the method, the volume of total adipose tissue (TAT), SAT, and VAT were measured for a total of 100 CTs using the automated method, and the results compared with those from manual measurements obtained by 2 experts. Dice’s similarity coefficients (DSCs) between the first manual measurement and the automated result for TAT, SAT, and VAT are 0.99, 0.98, and 0.97, respectively. The DSCs between the second manual measurement and the automated result for TAT, SAT, and VAT are 0.98, 0.98, and 0.97, respectively. Moreover, intraclass correlation coefficients (ICCs) between the automated method and the results of the manual measurements indicate high reliability as the ICCs for the items are all .99 (P<.001).

Conclusions

The results described in this paper confirm the accuracy and reliability of the proposed method. The method is expected to be both convenient and useful in the clinical evaluation and study of obesity in patients who require SAT and VAT measurements.

Computer-assisted staging of chronic rhinosinusitis correlates with symptoms

BACKGROUND

The Lund-Mackay (LM) staging system for chronic rhinosinusitis (CRS) does not correlate with clinical parameters, likely due to its coarse scale. We developed a "Modified Lund Mackay" (MLM) system, which uses a three-dimensional (3D), computerized method to quantify the volume of mucosal inflammation in the sinuses, and sought to determine whether the MLM would correlate with symptoms and disease-specific quality of life.

METHODS

We obtained Total Nasal Symptom Score (TNSS) and 22-item Sino-Nasal Outcome Test (SNOT-22) data from 55 adult subjects immediately prior to sinus imaging. The volume of each sinus occupied by mucosal inflammation was measured using MATLAB algorithms created using customized, image analysis software after manual outlining of each sinus. Linear regression was used to model the relationship between the MLM and the SNOT-22 and TNSS. Correlation between the LM and MLM was tested using Spearman's rank correlation coefficient.

RESULTS

Adjusting for age, gender, and smoking, a higher symptom burden was associated with increased sinonasal inflammation as captured by the MLM (β = 0.453, p < 0.013). As expected due to the differences in scales, the LM and MLM scores were significantly different (p < 0.011). No association between MLM and SNOT-22 scores was found.

CONCLUSION

The MLM is one of the first imaging-based scoring systems that correlates with sinonasal symptoms. Further development of this custom software, including full automation and validation in larger samples, may yield a biomarker with great utility for both treatment of patients and outcomes assessment in clinical trials.

Computerized image analysis of the Ki-67 proliferation index in mantle cell lymphoma

AIMS

Manual counting of the fraction of Ki-67-positive cells (the Ki-67 index) in 1000 tumour cells is considered the 'gold standard' to predict prognosis in mantle cell lymphoma (MCL). This time-consuming method is replaced by the faster, but less accurate, semiquantitative estimation in routine practice. The aim of this study was to investigate the use of computerized image analysis software for scoring of Ki-67 in MCL.

METHODS AND RESULTS

We developed an automated method for determining the Ki-67 index by computerized image analysis and tested it using a cohort of 62 MCL patients. The data were compared to Ki-67 scores obtained by semiquantitative estimation and image-based manual counting. When using the Ki-67 index as a continuous parameter, both image-based manual counting and computerized image analysis were related inversely to survival (P = 0.020 and P = 0.025, respectively). Ki-67 index obtained by semiquantitative estimation was not associated significantly with survival (P = 0.093). The results were validated in a second patient cohort with similar results.

CONCLUSION

Computerized image analysis of the Ki-67 index in MCL is an attractive alternative to semiquantitative estimation and can be introduced easily in a routine diagnostic setting for risk stratification in MCL.

Poisson-event-based analysis of cell proliferation

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS‐2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS‐2B cells. Comparison of the mitotic event series for the BEAS‐2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 The Authors. Published by Wiley Periodicals, Inc.

Multi-modal robust inverse-consistent linear registration

Registration performance can significantly deteriorate when image regions do not comply with model assumptions. Robust estimation improves registration accuracy by reducing or ignoring the contribution of voxels with large intensity differences, but existing approaches are limited to monomodal registration. In this work, we propose a robust and inverse-consistent technique for cross-modal, affine image registration. The algorithm is derived from a contextual framework of image registration. The key idea is to use a modality invariant representation of images based on local entropy estimation, and to incorporate a heteroskedastic noise model. This noise model allows us to draw the analogy to iteratively reweighted least squares estimation and to leverage existing weighting functions to account for differences in local information content in multimodal registration. Furthermore, we use the nonparametric windows density estimator to reliably calculate entropy of small image patches. Finally, we derive the Gauss-Newton update and show that it is equivalent to the efficient second-order minimization for the fully symmetric registration approach. We illustrate excellent performance of the proposed methods on datasets containing outliers for alignment of brain tumor, full head, and histology images.

Does quantitative lung SPECT detect lung abnormalities earlier than lung function tests? Results of a pilot study

BACKGROUND

Heterogeneous ventilation in lungs of individuals with allergies, cigarette smokers, asthmatics and chronic obstructive pulmonary disease (COPD) patients has been demonstrated using imaging modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT). These individuals suffer from narrow and/or closed airways to various extents. By calculating regional heterogeneity in lung ventilation SPECT images as the coefficient of variation (CV) in small elements of the lung, heterogeneity maps and CV-density curves can be generated and used to quantitatively measure heterogeneity. This work explores the potential to use such measurements to detect mild ventilation heterogeneities in lung-healthy subjects.

METHOD

Fourteen healthy subjects without documented lung disease or respiratory symptoms, and two patients with documented airway disease, inhaled on average approximately 90 MBq (99m)Tc-Technegas immediately prior to the 20-min SPECT acquisition. Variation in activity uptake between subjects was compensated for in resulting CV values. The area under the compensated CV density curve (AUC), for CV values greater than a threshold value CVT, AUC(CV > CVT), was used as the measure of ventilation heterogeneity.

RESULTS

Patients with lung function abnormalities, according to lung function tests, generated higher AUC(CV > 20%) values compared to healthy subjects (p = 0.006). Strong linear correlations with the AUC(CV > 20%) values were found for age (p = 0.006) and height (p = 0.001). These demonstrated that ventilation heterogeneities increased with age and that they depend on lung size. Strong linear correlations were found for the lung function value related to indices of airway closure/air trapping, residual volume/total lung capacity (RV/TLC; p = 0.009), and diffusion capacity of the lung for carbon monoxide adjusted for haemoglobin concentration in the blood (DLCOc; p = 0.009), a value partly related to supposed ventilation/perfusion mismatch. These findings support the association between conventional lung function tests and the AUC(CV > 20%) value.

CONCLUSIONS

Among the healthy subjects, there is a group with increased AUC(CV > 20%) values, but with normal lung function tests, which implies that it might be possible to differentiate ventilation heterogeneities earlier in a disease process than by lung function tests.

Prognostic factors that increase the risk for reduced white matter volumes and deficits in attention and learning for survivors of childhood cancers

OBJECTIVE

In children, CNS-directed cancer therapy is thought to result in decreased cerebral white matter volumes (WMV) and subsequent neurocognitive deficits. This study was designed as a prospective validation of the purported reduction in WMV, associated influential factors, and its relationship to neurocognitive deficits in a very large cohort of both acute lymphoblastic leukemia (ALL) and malignant brain tumors (BT) survivors in comparison to an age similar cohort of healthy sibling controls.

PROCEDURES

The effects of host characteristics and CNS treatment intensity on WMV were investigated in 383 childhood cancer survivors (199 ALL, 184 BT) at least 12 months post-completion of therapy and 67 healthy siblings that served as a control group. t-Tests and multiple variable linear models were used to assess cross-sectional WMV and its relation with neurocognitive function.

RESULTS

BT survivors had lower WMV than ALL survivors, who had less than the control group. Increased CNS treatment intensity, younger age at treatment, and greater time since treatment were significantly associated with lower WMV. Additionally, cancer survivors did not perform as well as the control group on neurocognitive measures of intelligence, attention, and academic achievement. Reduced WMV had a larger impact on estimated IQ among females and children treated at a younger age.

CONCLUSIONS

Survivors of childhood cancer that have undergone higher intensity therapy at a younger age have significantly less WMV than their peers and this difference increases with time since therapy. Decreased WMV is associated with significantly lower scores in intelligence, attention, and academic performance in survivors.

Cross gender-age trabecular texture analysis in cone beam CT

OBJECTIVES

To investigate whether multiple texture features in different regions of interest (ROIs) on cone beam CT (CBCT) are correlated with gender-age variation of trabecular patterns.

METHODS

CBCT volumes from 96 subjects were used. The data set was divided into four gender-age subgroups, including males younger than 40 years, males older than 40 years, females younger than 40 years and females older than 40 years. For each volume, cubes containing trabecular patterns at four ROIs in the jaws were manually cropped. 18 distinct texture features were calculated and their correlation with gender-age variations at different ROIs was studied through t-test statistical analysis.

RESULTS

For the 432 test pairs with different gender-age groups at different ROIs and texture features tested, 149 of them were shown to be statistically different at the 0.05 significance level and 60 of them at the 0.001 significance level. These features can therefore capture changes in trabecular patterns and have the potential to be used for trabecular analysis. Furthermore, fractal features were found to be better than intensity features in separating different gender-age groups. Trabecular patterns in the body of the mandible were more correlated with gender-age changes than other ROIs.

CONCLUSIONS

Multiple texture features on CBCT were found to be correlated with the cross gender-age variation of trabecular patterns. The results support the use of CBCT for advanced trabecular analysis, including osteoporosis screening tools in the jaws.

Three-dimensional volumetric computed tomographic scoring as an objective outcome measure for chronic rhinosinusitis: clinical correlations and comparison to Lund-Mackay scoring

BACKGROUND

We aimed to test the hypothesis that three-dimensional (3D) volume-based scoring of computed tomography (CT) images of the paranasal sinuses was superior to Lund-Mackay CT scoring of disease severity in chronic rhinosinusitis (CRS). We determined correlation between changes in CT scores (using each scoring system) with changes in other measures of disease severity (symptoms, endoscopic scoring, and quality of life) in patients with CRS treated with triamcinolone.

METHODS

The study group comprised 48 adult subjects with CRS. Baseline symptoms and quality of life were assessed. Endoscopy and CT scans were performed. Patients received a single systemic dose of intramuscular triamcinolone and were reevaluated 1 month later. Strengths of the correlations between changes in CT scores and changes in CRS signs and symptoms and quality of life were determined.

RESULTS

We observed some variability in degree of improvement for the different symptom, endoscopic, and quality-of-life parameters after treatment. Improvement of parameters was significantly correlated with improvement in CT disease score using both CT scoring methods. However, volumetric CT scoring had greater correlation with these parameters than Lund-Mackay scoring.

CONCLUSION

Volumetric scoring exhibited higher degree of correlation than Lund-Mackay scoring when comparing improvement in CT score with improvement in score for symptoms, endoscopic exam, and quality of life in this group of patients who received beneficial medical treatment for CRS.

Detailed analysis of inflammatory cell infiltration in colorectal cancer

BACKGROUND

Higher-grade inflammatory infiltrate is a promising marker for better prognosis in colorectal cancer (CRC). However, the knowledge on the interrelationships between different inflammatory cells and classifications is fragmentary.

METHODS

We analysed the densities of eight types of inflammatory cells in a prospectively recruited group of 117 CRC patients and determined their interrelationships and contributions to Klintrup-Mäkinen (K-M) score of overall peritumoural inflammation. We characterised the inflammatory infiltrate in relation to stage and recurrences in 24-month follow-up.

RESULTS

There were high positive correlations between the inflammatory cell densities, with the exception of mast cells and CD1a+ immature dendritic cells. High K-M score associated with high peri- and intratumoural densities of CD3+, CD8+, CD68+, CD83+, and FoxP3+ cells and neutrophils. Advanced stage associated with low K-M score, as well as low CD3+, CD8+, CD83+, and FoxP3+ cell counts, of which low K-M score, low CD3(+) T-cell count, and low FoxP3+ T-cell count were linked to higher recurrence rate.

CONCLUSION

The density of CRC inflammatory infiltrate declines as stage advances. Especially, low K-M score and low T-cell counts predict higher recurrence rate. The high positive correlations between the individual inflammatory markers support the value of overall inflammatory reaction scoring.

Validation of the automated method VIENA: an accurate, precise, and robust measure of ventricular enlargement

BACKGROUND

In many retrospective studies and large clinical trials, high-resolution, good-contrast 3DT1 images are unavailable, hampering detailed analysis of brain atrophy. Ventricular enlargement then provides a sensitive indirect measure of ongoing central brain atrophy. Validated automated methods are required that can reliably measure ventricular enlargement and are robust across magnetic resonance (MR) image types.

AIM

To validate the automated method VIENA for measuring the percentage ventricular volume change (PVVC) between two scans.

MATERIALS AND METHODS

Accuracy was assessed using four image types, acquired in 15 elderly patients (five with Alzheimer's disease, five with mild cognitive impairment, and five cognitively normal elderly) and 58 patients with multiple sclerosis (MS), by comparing PVVC values from VIENA to manual outlining. Precision was assessed from data with three imaging time points per MS patient, by measuring the difference between the direct (one-step) and indirect (two-step) measurement of ventricular volume change between the first and last time points. The stringent concordance correlation coefficient (CCC) was used to quantify absolute agreement.

RESULTS

CCC of VIENA with manual measurement was 0.84, indicating good absolute agreement. The median absolute difference between two-step and one-step measurement with VIENA was 1.01%, while CCC was 0.98. Neither initial ventricular volume nor ventricular volume change affected performance of the method.

DISCUSSION

VIENA has good accuracy and good precision across four image types. VIENA therefore provides a useful fully automated method for measuring ventricular volume change in large datasets.

CONCLUSION

VIENA is a robust, accurate, and precise method for measuring ventricular volume change.

A research agenda for appearance changes due to breast cancer treatment

Breast cancer is one of the most prevalent forms of cancer in the US. It is estimated that more than 180,000 American women will be diagnosed with invasive breast cancer in 2008. Fortunately, the survival rate is relatively high and continually increasing due to improved detection techniques and treatment methods. However, maintaining quality of life is a factor often under emphasized for breast cancer survivors. Breast cancer treatments are invasive and can lead to deformation of the breast. Breast reconstruction is important for restoring the survivor’s appearance. However, more work is needed to develop technologies for quantifying surgical outcomes and understanding women’s perceptions of changes in their appearance. A method for objectively measuring breast anatomy is needed in order to help both the breast cancer survivors and their surgeons take expected changes to the survivor’s appearance into account when considering various treatment options. In the future, augmented reality tools could help surgeons reconstruct a survivor’s breasts to match her preferences as much as possible.

A simple image display application for windows

The purpose of this project was to develop a simple application for displaying low-to-moderate resolution digital images under the Windows operating environment. The display of scintigraphic images was of special interest, and for this reason the program was designed to show sequences of images and to account for broad ranges of pixel values. In order to function under a variety of Windows versions, the program was developed using the 16-bit Microsoft C +2 compiler and targeted for Windows 3.1 enhanced. It was tested with Trionix images for nuclear medicine and Siemens for computed tomography (CT) and magnetic resonance (MR). The resulting application, called SID, successfully read Magnetom, Somatom, Trionix, and Interfile images of dimension 512 or less on Intel-based Windows PCs with 256 color SVGA-compatible (Super Video Graphics Adapters) video hardware. Early applications of the program included remote monitoring of image studies, resident review of teaching cases, review of research images, and preparation of educational materials. This article describes the features, operation, and potential applications of SID.