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@#Any metallic object within the CT scanning field can produce metal artefacts, which will degrade the diagnostic image quality. Previous methods described for quantifying this kind of artefacts were complicated and difficult to reproduce. The purpose of this study was to introduce a new rapid method for quantifying the artefacts produced in craniofacial CT images. This is an in-vitro experimental study. Four different compositions of orthodontic brackets were bonded consecutively in the tooth surfaces of a cadaveric skull head. All scans were performed by a single operator using the same CT machine followed by a standard scanning protocol. Artefact intensity for all data sets was quantified by following a modified method with a freely available open-source software ImageJ. All datasets were duplicated where metal artefacts were quantified according to the previous conventional method. Statistical analysis included independent samples t-test for validation and intraclass correlation coefficient (ICC) with a 95% confidence interval for both intra- and inter-examiner reliability. The modified method of measuring artefact score exhibited excellent intra (0.997–0.941) and inter-rater (0.996–0.905) reliability. In addition, no significant difference (p = 0.072) of mean artefact score was noted between the groups measured by the modified method and the conventional method. This modified method for measuring the artefact intensity is valid and reliable.
ABSTRACT
OBJECTIVES: Patients with head and neck cancer (HNC) have a high risk of sarcopenia, which is associated with poor prognosis. Skeletal-muscle area and index at the third lumbar (L3) vertebra level (L3MA and L3MI) are recommended for the detection of sarcopenia. However, L3 level is not included in many imaging protocols and there are no data for optimal levels and cutoffs for the diagnosis of sarcopenia in head and neck computed tomography (HNCT) scans. Our aim was to assess the relationship between cervical paravertebral muscle values and L3MI and to investigate optimal level to diagnose sarcopenia on HNCTs. METHODS: Patients with HNC (n=159) who underwent positron emission tomography-CT for tumor staging were retrospectively analyzed. On CT images, paravertebral and sternocleidomastoid muscle areas at second (C2), third (C3), and fourth (C4) cervical vertebrae levels (C2MA, C3MA, C4MA, SCMA) and L3MA were measured. Cross-sectional areas were normalized for stature (muscle area/height square) and muscle index (C2MI, C3MI, C4MI, SCMI, L3MI) values were obtained. Spearman correlation and linear regression analyses were used for assessing correlations. To calculate the diagnostic performance of SCMI, C2MI, C3MI, and C4MI for the diagnosis of sarcopenia with respect to the cutoffs of L3MI, receiver operating characteristic (ROC) analysis was used. RESULTS: Males had significantly higher muscle areas than females. Although C2MI, C3MI, C4MI, and SCMI values all showed very strong and significant correlation with L3MI (P<0.001). According to the ROC analysis, the best discriminative for sarcopenia was C3MI in males (area under curve [AUC], 0.967) and SCMI in females (AUC, 0.898). CONCLUSION: C2MI, C3MI, C4MI, and SCMI values can be used as alternatives for the diagnosis of sarcopenia in routine HNCT examinations.
Subject(s)
Female , Humans , Male , Body Mass Index , Cervical Vertebrae , Diagnosis , Electrons , Head and Neck Neoplasms , Head , Image Processing, Computer-Assisted , Linear Models , Neck , Neoplasm Staging , Prognosis , Retrospective Studies , ROC Curve , Sarcopenia , SpineABSTRACT
OBJECTIVE: To define optimal method that calculate the safe direction of cervical pedicle screw placement using computed tomography (CT) image based three dimensional (3D) cortical shell model of human cervical spine. METHODS: Cortical shell model of cervical spine from C3 to C6 was made after segmentation of in vivo CT image data of 44 volunteers. Three dimensional Cartesian coordinate of all points constituting surface of whole vertebra, bilateral pedicle and posterior wall were acquired. The ideal trajectory of pedicle screw insertion was defined as viewing direction at which the inner area of pedicle become largest when we see through the biconcave tubular pedicle. The ideal trajectory of 352 pedicles (eight pedicles for each of 44 subjects) were calculated using custom made program and were changed from global coordinate to local coordinate according to the three dimensional position of posterior wall of each vertebral body. The transverse and sagittal angle of trajectory were defined as the angle between ideal trajectory line and perpendicular line of posterior wall in the horizontal and sagittal plane. The averages and standard deviations of all measurements were calculated. RESULTS: The average transverse angles were 50.60º±6.22º at C3, 51.42º ±7.44º at C4, 47.79º ±7.61º at C5, and 41.24º ±7.76º at C6. The transverse angle becomes more steep from C3 to C6. The mean sagittal angles were 9.72º ±6.73º downward at C3, 5.09º±6.39º downward at C4, 0.08º ±6.06º downward at C5, and 1.67º ±6.06º upward at C6. The sagittal angle changes from caudad to cephalad from C3 to C6. CONCLUSION: The absolute values of transverse and sagittal angle in our study were not same but the trend of changes were similar to previous studies. Because we know 3D address of all points constituting cortical shell of cervical vertebrae. we can easily reconstruct 3D model and manage it freely using computer program. More creative measurement of morphological characteristics could be carried out than direct inspection of raw bone. Furthermore this concept of measurement could be used for the computing program of automated robotic screw insertion.
Subject(s)
Female , Humans , Cervical Vertebrae , Image Processing, Computer-Assisted , Methods , Pedicle Screws , Spine , VolunteersABSTRACT
OBJECTIVE: To define optimal method that calculate the safe direction of cervical pedicle screw placement using computed tomography (CT) image based three dimensional (3D) cortical shell model of human cervical spine.METHODS: Cortical shell model of cervical spine from C3 to C6 was made after segmentation of in vivo CT image data of 44 volunteers. Three dimensional Cartesian coordinate of all points constituting surface of whole vertebra, bilateral pedicle and posterior wall were acquired. The ideal trajectory of pedicle screw insertion was defined as viewing direction at which the inner area of pedicle become largest when we see through the biconcave tubular pedicle. The ideal trajectory of 352 pedicles (eight pedicles for each of 44 subjects) were calculated using custom made program and were changed from global coordinate to local coordinate according to the three dimensional position of posterior wall of each vertebral body. The transverse and sagittal angle of trajectory were defined as the angle between ideal trajectory line and perpendicular line of posterior wall in the horizontal and sagittal plane. The averages and standard deviations of all measurements were calculated.RESULTS: The average transverse angles were 50.60º±6.22º at C3, 51.42º ±7.44º at C4, 47.79º ±7.61º at C5, and 41.24º ±7.76º at C6. The transverse angle becomes more steep from C3 to C6. The mean sagittal angles were 9.72º ±6.73º downward at C3, 5.09º±6.39º downward at C4, 0.08º ±6.06º downward at C5, and 1.67º ±6.06º upward at C6. The sagittal angle changes from caudad to cephalad from C3 to C6.CONCLUSION: The absolute values of transverse and sagittal angle in our study were not same but the trend of changes were similar to previous studies. Because we know 3D address of all points constituting cortical shell of cervical vertebrae. we can easily reconstruct 3D model and manage it freely using computer program. More creative measurement of morphological characteristics could be carried out than direct inspection of raw bone. Furthermore this concept of measurement could be used for the computing program of automated robotic screw insertion.
Subject(s)
Female , Humans , Cervical Vertebrae , Image Processing, Computer-Assisted , Methods , Pedicle Screws , Spine , VolunteersABSTRACT
PURPOSE: In order to evaluate the relationship between the dose to the liver parenchyma and focal liver reaction (FLR) after stereotactic ablative body radiotherapy (SABR), we suggest a novel method using a three-dimensional dose distribution and change in signal intensity of gadoxetate disodium-gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) hepatobiliary phase images. MATERIALS AND METHODS: In our method, change of the signal intensity between the pretreatment and follow-up hepatobiliary phase images of Gd-EOB-DTPA-enhanced MRI was calculated and then threshold dose (TD) for developing FLR was obtained from correlation of dose with the change of the signal intensity. For validation of the method, TDs for six patients, who had been treated for liver cancer with SABR with 45-60 Gy in 3 fractions, were calculated using the method, and we evaluated concordance between volume enclosed by isodose of TD by the method and volume identified as FLR by a physician. RESULTS: The dose to normal liver was correlated with change in signal intensity between pretreatment and follow-up MRI with a median R2 of 0.935 (range, 0.748 to 0.985). The median TD by the method was 23.5 Gy (range, 18.3 to 39.4 Gy). The median value of concordance was 84.5% (range, 44.7% to 95.9%). CONCLUSION: Our method is capable of providing a quantitative evaluation of the relationship between dose and intensity changes on follow-up MRI, as well as determining individual TD for developing FLR. We expect our method to provide better information about the individual relationship between dose and FLR in radiotherapy for liver cancer.
Subject(s)
Humans , Evaluation Studies as Topic , Feasibility Studies , Follow-Up Studies , Gadolinium DTPA , Image Processing, Computer-Assisted , Liver Neoplasms , Liver , Magnetic Resonance Imaging , Pentetic Acid , Radiation Effects , Radiosurgery , RadiotherapyABSTRACT
OBJECTIVES: In this paper, we proposed an algorithm for recognizing a rotator cuff supraspinatus tendon tear using a texture analysis based on a histogram, gray level co-occurrence matrix (GLCM), and gray level run length matrix (GLRLM). METHODS: First, we applied a total of 57 features (5 first order descriptors, 40 GLCM features, and 12 GLRLM features) to each rotator cuff region of interest. Our results show that first order statistics (mean, skewness, entropy, energy, smoothness), GLCM (correlation, contrast, energy, entropy, difference entropy, homogeneity, maximum probability, sum average, sum entropy), and GLRLM features are helpful to distinguish a normal supraspinatus tendon and an abnormal supraspinatus tendon. The statistical significance of these features is verified using a t-test. The support vector machine classification showed accuracy using feature combinations. Support Vector Machine offers good performance with a small amount of training data. Sensitivity, specificity, and accuracy are used to evaluate performance of a classification test. RESULTS: From the results, first order statics features and GLCM and GLRLM features afford 95%, 85%, and 100% accuracy, respectively. First order statistics and GLCM and GLRLM features in combination provided 100% accuracy. Combinations that include GLRLM features had high accuracy. GLRLM features were confirmed as highly accurate features for classified normal and abnormal. CONCLUSIONS: This algorithm will be helpful to diagnose supraspinatus tendon tear on ultrasound images.
Subject(s)
Classification , Data Interpretation, Statistical , Entropy , Image Processing, Computer-Assisted , Rotator Cuff , Sensitivity and Specificity , Subject Headings , Support Vector Machine , Tears , Tendons , UltrasonographyABSTRACT
OBJECTIVES: We propose an automatic breast mass detection algorithm in three-dimensional (3D) ultrasound (US) images using the Hough transform technique. METHODS: One hundred twenty-five cropped images containing 68 benign and 60 malignant masses are acquired with clinical diagnosis by an experienced radiologist. The 3D US images are masked, subsampled, contrast-adjusted, and median-filtered as preprocessing steps before the Hough transform is used. Thereafter, we perform 3D Hough transform to detect spherical hyperplanes in 3D US breast image volumes, generate Hough spheres, and sort them in the order of votes. In order to reduce the number of the false positives in the breast mass detection algorithm, the Hough sphere with a mean or grey level value of the centroid higher than the mean of the 3D US image is excluded, and the remaining Hough sphere is converted into a circumscribing parallelepiped cube as breast mass lesion candidates. Finally, we examine whether or not the generated Hough cubes were overlapping each other geometrically, and the resulting Hough cubes are suggested as detected breast mass candidates. RESULTS: An automatic breast mass detection algorithm is applied with mass detection sensitivity of 96.1% at 0.84 false positives per case, quite comparable to the results in previous research, and we note that in the case of malignant breast mass detection, every malignant mass is detected with false positives per case at a rate of 0.62. CONCLUSIONS: The breast mass detection efficiency of our algorithm is assessed by performing a ROC analysis.
Subject(s)
Breast Neoplasms , Breast , Diagnosis , Diagnosis, Computer-Assisted , Early Detection of Cancer , Image Processing, Computer-Assisted , Masks , ROC Curve , UltrasonographyABSTRACT
Objective To investigate the feasibility of centerline measurement method in estimating aortic diameter at the proximal landing zone in Stanford B type aortic dissection. Methods CT angiography materials of 30 patients with type B aortic dissection were randomly selected from the hospital database (24 males with a median age of 49.5 years), which were retrospectively analyzed with multiplanar reformation (MPR) and centerline technique by two experts in vascular radiology. Difference between two measurement techniques was analyzed by using mixed linear model, and the agreement of measurements between two readers as well as between two techniques were evaluated by Bland-Altman plots. Results The diameters measured with MPR method by two experts were (29.73±2.99) mm and (29.86±2.95) mm respectively, while the diameters measured with centerline measurement method by two experts were (29.66 ±2.81) mm and (29.71 ±2.91) mm respectively. No statistically significant differences in the diameter value existed between the two measurement methods, although the results determined by centerline measurement method were more stable. Conclusion In determining aortic diameter at the proximal landing zone in Stanford B type aortic dissection, the centerline analysis provides a checking method for MPR measurement.
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PURPOSE: The objective of this study was to assess the trabecular bone changes that occurred around functional endosseous dental implants by means of radiographic image analysis techniques. MATERIALS AND METHODS: Immediate preoperative and postoperative periapical radiographs of de-identified implant patients at the University Dental Hospital of Manchester were retrieved, screened for specific inclusion criteria, digitized, and quantified for structural elements of the trabecular bone around the endosseous implants, by using image analysis techniques. Data were analyzed using SPSS version 11.5. P values of less than 0.05 were considered statistically significant. RESULTS: A total of 12 implants from 11 patients were selected for the study, and 26 regions of interest were obtained. There was a significant increase in the bone area in terms of the mean distance between nodes (p=0.006) and a significant decrease in the marrow area in terms of the bone area (p=0.006) and the length of marrow spaces (p=0.032). CONCLUSION: It appeared that the bone around the implant underwent remodeling that resulted in a net increase in bone after implant placement.
Subject(s)
Humans , Bone and Bones , Bone Marrow , Dental Implants , Image Processing, Computer-AssistedABSTRACT
BACKGROUND: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy. OBJECTIVE: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance. METHODS: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle. RESULTS: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis. CONCLUSION: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.
Subject(s)
Humans , Bioengineering , Cosmetics , Dermatology , Diagnosis, Differential , Image Processing, Computer-Assisted , Keratosis, Seborrheic , Lentigo , Nevus , SkinABSTRACT
BACKGROUND: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy. OBJECTIVE: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance. METHODS: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle. RESULTS: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis. CONCLUSION: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.
Subject(s)
Humans , Bioengineering , Cosmetics , Dermatology , Diagnosis, Differential , Image Processing, Computer-Assisted , Keratosis, Seborrheic , Lentigo , Nevus , SkinABSTRACT
Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. Many different CAD schemes are being developed for use in the detection and/or characterization of various lesions found through various types of medical imaging. These imaging technologies employ conventional projection radiography, computed tomography, magnetic resonance imaging, ultrasonography, etc. In order to achieve a high performance level for a computerized diagnosis, it is important to employ effective image analysis techniques in the major steps of a CAD scheme. The main objective of this review is to attempt to introduce the diverse methods used for quantitative image analysis, and to provide a guide for clinicians.
Subject(s)
Humans , Diagnostic Imaging , Evaluation Studies as Topic , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Research SubjectsABSTRACT
BACKGROUND: Histologic evidence of destruction of a cutaneous nerve by granulomatous inflammation is a feature of tuberculoid leprosy. However, identifying remnants of the nerve in the granuloma may be difficult in some instances because of morphologic similarities with granulomatous dermatoses, such as sarcoidosis, lupus vulgaris, tertiary syphilis, etc. OBJECT: The purpose of this study was to investigate the expressions of S-100 and EMA and to estimate area, thickness and density of nerves for differentiation tuberculoid leprosy from sarcoidosis. METHODS: Paraffin embedded tissues from patients of 11 tuberculoid leprosy, and 4 sarcoidosis were investigated for the expression of S-100, EMA and for the measurement of area, thickness, density of nerves by image analysis. RESULTS: S-100 staining in tuberculoid leprosy demonstrated fragmented, infiltrated, swollen nerves or the absence of dermal nerves(45.5%). All of the detectable nerves were identified within granulomas from tuberculoid leprosy, but nerves from sarcoidosis were widely distributed over inside(33.3%) or outside of the granulomas, perivascular, and periappendageal areas. There was no expression of EMA in skin lesions from leprosy, sarcoidosis, even in the site showing perineural thickening in S-100 stain. The cross-section area and the thickness of nerves were decreased in order of tuberculoid leprosy, sarcoidosis, and normal control group(p<0.05). The density of nerves was decreased in order of normal control group tuberculoid leprosy, and sarcoidosis with statistical significance between tuberculoid leprosy and sarcoidosis. CONCLUSION: It is possible to differentiate tuberculoid leprosy from sarcoidosis by the observation of the morphologic changes with S-100 protein stain and the measurement of the cross-section area, thickness and density with image analysis.
Subject(s)
Humans , Diagnosis, Differential , Granuloma , Image Processing, Computer-Assisted , Inflammation , Leprosy , Leprosy, Tuberculoid , Lupus Vulgaris , Paraffin , S100 Proteins , Sarcoidosis , Skin , Skin Diseases , SyphilisABSTRACT
BACKGROUND: Histologic evidence of destruction of a cutaneous nerve by granulomatous inflammation is a feature of tuberculoid leprosy. However, identifying remnants of the nerve in the granuloma may be difficult in some instances because of morphologic similarities with granulomatous dermatoses, such as sarcoidosis, lupus vulgaris, tertiary syphilis, etc. OBJECT: The purpose of this study was to investigate the expressions of S-100 and EMA and to estimate area, thickness and density of nerves for differentiation tuberculoid leprosy from sarcoidosis. METHODS: Paraffin embedded tissues from patients of 11 tuberculoid leprosy, and 4 sarcoidosis were investigated for the expression of S-100, EMA and for the measurement of area, thickness, density of nerves by image analysis. RESULTS: S-100 staining in tuberculoid leprosy demonstrated fragmented, infiltrated, swollen nerves or the absence of dermal nerves(45.5%). All of the detectable nerves were identified within granulomas from tuberculoid leprosy, but nerves from sarcoidosis were widely distributed over inside(33.3%) or outside of the granulomas, perivascular, and periappendageal areas. There was no expression of EMA in skin lesions from leprosy, sarcoidosis, even in the site showing perineural thickening in S-100 stain. The cross-section area and the thickness of nerves were decreased in order of tuberculoid leprosy, sarcoidosis, and normal control group(p<0.05). The density of nerves was decreased in order of normal control group tuberculoid leprosy, and sarcoidosis with statistical significance between tuberculoid leprosy and sarcoidosis. CONCLUSION: It is possible to differentiate tuberculoid leprosy from sarcoidosis by the observation of the morphologic changes with S-100 protein stain and the measurement of the cross-section area, thickness and density with image analysis.