Association of AI-determined Kellgren-Lawrence grade with medial meniscus extrusion and cartilage thickness by AI-based 3D MRI analysis in early knee osteoarthritis.

The associations among Kellgren-Lawrence (KL) grade, medial meniscus extrusion (MME), and cartilage thickness in knee osteoarthritis (OA) remain insufficiently understood. Our aim was to determine these associations in early to moderate medial tibiofemoral knee OA. We included 469 subjects with no lateral OA from the Kanagawa Knee Study. KL grade was assessed using artificial intelligence (AI) software. The MME was measured by MRI, and the cartilage thickness was evaluated in 18 subregions of the medial femorotibial joint by another AI system. The median MME width was 1.4 mm in KL0, 1.5 mm in KL1, 2.4 mm in KL2, and 6.0 mm in KL3. Cartilage thinning in the medial femur occurred in the anterior central subregion in KL1, expanded inwardly in KL2, and further expanded in KL3. Cartilage thinning in the medial tibia occurred in the anterior and middle external subregions in KL1, expanded into the anterior and middle central subregions in KL2, and further expanded in KL3. The absolute correlation coefficient between MME width and cartilage thickness increased as the KL grade increased in some subregions. This study provides novel insights into the early stages of knee OA and potentially has implications for the development of early intervention strategies.

Morphological analysis of three-dimensional MR images of patellofemoral joints in asymptomatic subjects.

The existing methods for analyzing patellofemoral (PF) osteoarthritis (OA) are limited. Our purpose was to clarify the frequency, localization, and morphological progression of PFOA by observing three-dimensional (3D) magnetic resonance (MR) images from a cohort population. The subjects were 561 patients aged 30-79 years from the Kanagawa Knee Study who had not visited a hospital for more than three consecutive months for knee symptoms. MR images of the PF joints, separated into the medial and lateral types, were presented in order of the highest to lowest patella cartilage area ratios. Cartilage defects in the patella were detected in 37 subjects (6.6%). Medial lesions (4.6%) were significantly more frequent than lateral lesions (2.0%) (p < 0.01). For both medial and lateral lesions, the patellar cartilage defects were divided into confined and unconfined types. The 3D MR images of the PF joint showed that the patellar cartilage defect occurred along each ridge of the femoral trochlea. The 3D MR images revealed a 6.6% prevalence of patellar cartilage defects, higher in the medial than lateral regions. The 3D MR images can easily determine PF morphology and cartilage defect location, making them useful in understanding the pathophysiology and etiology of PFOA.

Association between knee cartilage thickness determined by magnetic resonance imaging three-dimensional analysis and the International Cartilage Repair Society (ICRS) arthroscopic grade.

BACKGROUND: The purpose of this study was to retrospectively investigate whether the average cartilage thickness calculated by magnetic resonance imaging (MRI) three-dimensional (3D) analysis system was correlated with the International Cartilage Repair Society (ICRS) grade at each subregion, as a representative scoring for arthroscopic evaluation. METHODS: The subjects were 102 patients who underwent arthroscopy for meniscus repair or high tibial osteotomy for medial osteoarthritis of the knee. Cartilage lesions were arthroscopically quantified according to the ICRS grade at each subregion. Fluoroscopy was used to compare the subregions on arthroscopic evaluation with subregions on MRI. The average cartilage thickness at each subregion was also automatically calculated from MRI data using our 3D analysis system. The association between ICRS grade and the average cartilage thickness at 18 subregions in the medial femoral and medial tibial regions was evaluated using Spearman's rank correlation coefficient. RESULTS: Examination of the fluoroscopic images revealed that the posterior subregions in the medial femoral region did not match the position between arthroscopy and MRI; therefore, those three subregions were excluded. In the medial femoral region, the ICRS grade correlated moderately with cartilage thickness at five subregions and weakly at one subregion. In the medial tibial region, the ICRS grade correlated moderately with cartilage thickness at four subregions and weakly at one subregion, but it did not correlate at the other four subregions. CONCLUSION: The average cartilage thickness determined by MRI 3D analysis correlated with arthroscopic grade at 11 of 15 subregions in the medial femoral and tibial regions.

Three-dimensional conditional generative adversarial network-based virtual thin-slice technique for the morphological evaluation of the spine.

Virtual thin-slice (VTS) technique is a generative adversarial network-based algorithm that can generate virtual 1-mm-thick CT images from images of 3-10-mm thickness. We evaluated the performance of VTS technique for assessment of the spine. VTS was applied to 4-mm-thick CT images of 73 patients, and the visibility of intervertebral spaces was evaluated on the 4-mm-thick and VTS images. The heights of vertebrae measured on sagittal images reconstructed from the 4-mm-thick images and VTS images were compared with those measured on images reconstructed from 1-mm-thick images. Diagnostic performance for the detection of compression fractures was also compared. The intervertebral spaces were significantly more visible on the VTS images than on the 4-mm-thick images (P < 0.001). The absolute value of the measured difference in mean vertebral height between the VTS and 1-mm-thick images was smaller than that between the 4-mm-thick and 1-mm-thick images (P < 0.01-0.54). The diagnostic performance of the VTS images for detecting compression fracture was significantly lower than that of the 4-mm-thick images for one reader (P = 0.02). VTS technique enabled the identification of each vertebral body, and enabled accurate measurement of vertebral height. However, this technique is not suitable for diagnosing compression fractures.

Three-dimensional MRI shows cartilage defect extension with no separation from the meniscus in women in their 70 s with knee osteoarthritis.

The positional relationship between cartilage defects and the meniscus is poorly understood for osteoarthritis of the knee. Our purpose was to clarify how cartilage defects extend and their association with the meniscus location during osteoarthritis progression. The subjects were women in their 70 s who were registered in the Kanagawa Knee Study. We obtained 3D MRI images of the tibial surfaces with menisci in subjects with cartilage area ratios < 0.95 and examined the morphological association between cartilage defects and the medial meniscus (MM) by viewing the defects according to the cartilage area ratio at the medial tibial region. Of the 561 Kanagawa Knee Study subjects, 45 were included in the analyses, and 11 had a cartilage area ratio < 0.95 at the medial tibia. Significant differences were observed in the localization of cartilage defects among 9 subregions, with cartilage defects occurring predominantly in the middle external subregion. The inner margin of the MM contacted the cartilage defect in 7 knees and crossed the cartilage defect in 4 knees but was never found separated from the cartilage defect. The cartilage defects occurred from the middle external subregion and extended to the surrounding area without separating from the inner margin of the MM.Trial registration UMIN, UMIN000032826; 1 September 2018.

Medial Tibial Osteophyte Width Strongly Reflects Medial Meniscus Extrusion Distance and Medial Joint Space Width Moderately Reflects Cartilage Thickness in Knee Radiographs.

BACKGROUND: The presence of medial tibial osteophytes on knee radiographs suggests cartilage wear, but may be associated with medial meniscus extrusion (MME). The joint space width of the medial compartment consists anatomically of cartilage and the medial meniscus, but which is most responsible for joint space narrowing remains unclear. Magnetic resonance imaging (MRI) reveals MME and cartilage thickness. PURPOSES: To determine which radiographic medial tibial osteophyte width correlates better with cartilage thickness or MME distance and which radiographic medial joint space width correlates better with cartilage thickness or MME distance. STUDY TYPE: Cross-sectional. POPULATION: Total of 527 subjects, 253 females and 274 males, aged 30-79 years, included in the Kanagawa Knee Study. FIELD STRENGTH/SEQUENCE: 3 T/fat-suppressed spoiled gradient echo and proton density weighted. ASSESSMENT: The medial tibial osteophyte width and "the minimum joint space width at the medial compartment" (mJSW) were measured from plain radiographs. The cartilage region was automatically extracted from MRI data using software. The medial femoral and tibial cartilage regions were each divided into nine subregions, and the average thickness of the cartilage was determined in each region and subregion. MME was manually measured by two orthopedic surgeons using MRI coronal section images. STATISTICAL TESTS: Pearson's correlation coefficient and their comparison, with P < 0.05 considered statistically significant. RESULTS: The absolute values of the correlation coefficients were 0.33 at maximum between osteophyte width and cartilage thickness and 0.76 between osteophyte width and MME; the value was significantly higher with MME than with cartilage thickness (P < 0.001). The absolute values of the correlation coefficients were 0.50 at maximum between mJSW and cartilage thickness and 0.16 between mJSW and MME; the value was significantly higher with cartilage thickness than with MME (P < 0.001). DATA CONCLUSION: The medial tibial osteophyte width strongly reflected MME and the medial joint space width moderately reflected cartilage thickness. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Difference in the joint space of the medial knee compartment between full extension and Rosenberg weight-bearing radiographs.

OBJECTIVES: Radiographs are the most widespread imaging tool for diagnosing osteoarthritis (OA) of the knee. Our purpose was to determine which of the two factors, medial meniscus extrusion (MME) or cartilage thickness, had a greater effect on the difference in the minimum joint space width (mJSW) at the medial compartment between the extension anteroposterior view (extension view) and the 45° flexion posteroanterior view (Rosenberg view). METHODS: The subjects were 546 participants (more than 50 females and 50 males in their 30 s, 40 s, 50 s, 60 s, and 70 s) in the Kanagawa Knee Study. The mJSW at the medial compartment was measured from both the extension and the Rosenberg views, and the "mJSW difference" was defined as the mJSW in the Rosenberg view subtracted from the mJSW in the extension view. The cartilage region was automatically extracted from MRI data and constructed in three dimensions. The medial region of the femorotibial joint cartilage was divided into 18 subregions, and the cartilage thickness in each subregion was determined. The MME was also measured from MRI data. RESULTS: The mJSW difference and cartilage thickness were significantly correlated at 4 subregions, with 0.248 as the highest absolute value of the correlation coefficient. The mJSW difference and MME were also significantly correlated, with a significantly higher correlation coefficient (0.547) than for the mJSW difference and cartilage thickness. CONCLUSIONS: The MME had a greater effect than cartilage thickness on the difference between the mJSW at the medial compartment in the extension view and in the Rosenberg view. KEY POINTS: • The difference in the width at the medial compartment of the knee between the extension and the flexion radiographic views was more affected by medial meniscus extrusion than by cartilage thickness.

Artificial intelligence analysis of three-dimensional imaging data derives factors associated with postoperative recurrence in patients with radiologically solid-predominant small-sized lung cancers.

OBJECTIVES: Indications of limited resection, such as segmentectomy, have recently been reported for patients with solid-predominant lung cancers ≤2 cm. This study aims to identify unfavourable prognostic factors using three-dimensional imaging analysis with artificial intelligence (AI) technology. METHODS: A total of 157 patients who had clinical N0 non-small cell lung cancer with a radiological size ≤2 cm, and a consolidation tumour ratio > 0.5, who underwent anatomical lung resection between 2011 and 2017 were enrolled. To evaluate the three-dimensional structure, the ground-glass nodule/Solid Automatic Identification AI software Beta Version (AI software; Fujifilm Corporation, Japan) was used. RESULTS: Maximum standardized uptake value (SUVmax) and solid-part volume measured by AI software (AI-SV) showed significant differences between the 139 patients with adenocarcinoma and the 18 patients with non-adenocarcinoma. Among the adenocarcinoma patients, 42 patients (30.2%) were found to be pathological upstaging. Multivariable analysis demonstrated that high SUVmax, high carcinoembryonic antigen level and high AI-SV were significant prognostic factors for recurrence-free survival (RFS; P < 0.05). The 5-year RFS was compared between patients with tumours showing high SUVmax and those showing low SUVmax (67.7% vs 95.4%, respectively, P < 0.001). The 5-year RFS was 91.0% in patients with small AI-SV and 68.1% in those with high AI-SV (P = 0.001). CONCLUSIONS: High AI-SV, high SUVmax and abnormal carcinoembryonic antigen level were unfavourable prognostic factors of patients with solid-predominant lung adenocarcinoma with a radiological size ≤2 cm. Our results suggest that lobectomy should be preferred to segmentectomy for patients with these prognostic factors.

Alterations in cartilage quantification before and after injections of mesenchymal stem cells into osteoarthritic knees.

Several studies have reported improvement in knee pain following mesenchymal stem cell (MSC) injections for knee osteoarthritis (OA). We developed a novel 3D magnetic resonance imaging (MRI) analysis software program that provides "projected cartilage area ratios" for automatic detection of changes in cartilage amounts. The primary objective of this prospective interventional study was to compare alterations in the projected cartilage area ratio (thickness ≥ 1.5 mm) at the femoral posteromedial region between 30 weeks before and 30 weeks after synovial MSC injections. Secondary objectives were to assess the clinical scores and safety of MSC injections. Patients with OA who complained of knee pain underwent autologous synovial MSC injections into the knee at time 0 and again 15 weeks later. MRI examinations were performed at - 30, - 15, - 1, and 30 weeks. Patients showing < 3% decreases in the projected cartilage area ratio (thickness ≥ 1.5 mm) at the femoral the posteromedial region from - 30 weeks to - 15 weeks were excluded from the study. The Lysholm Knee Score, Knee Injury and Osteoarthritis Outcome Scale (KOOS), and Numerical Rating Scale (NRS) scores were evaluated at - 30, - 15, - 5, - 2, 0, 5, 10, 15, 20, 25, and 30 weeks. Five patients were excluded because 3D MRI analysis showed no cartilage loss at - 15 weeks. Ultimately, eight OA patients underwent MSC injections. The projected cartilage area ratio significantly decreased by 0.07 in the 30 weeks before MSC injections (p = 0.01), but no further decreases occurred in the 30 weeks after MSC injections. The projected cartilage area ratio at the femoral posteromedial region showed a significant difference between 30 weeks before and 30 weeks after MSC injections. The Lysholm Knee Score, KOOS, and NRS values improved significantly after the injections. MSC injection could not be ruled out as the cause of two adverse events: transient knee pain and itching in both hands. Fully automatic 3D MRI analysis showed that synovial MSC injections suppressed cartilage loss in patients with progressive OA.Trial registration: Intraarticular injections of synovial stem cells for osteoarthritis of the knee (Number UMIN 000026732). Date of registration; June 1, 2017. https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000029967 .

Interscan measurement error of knee cartilage thickness and projected cartilage area ratio at 9 regions and 45 subregions by fully automatic three-dimensional MRI analysis.

BACKGROUND: We have developed a fully automatic three-dimensional MRI analysis software program for automatic segmentation of knee cartilage using a deep neural network. The purpose of this study was to use this software to clarify the interscan measurement error of the knee cartilage thickness and projected cartilage area ratio at 9 regions and 45 subregions in the knee. METHODS: Ten healthy volunteers underwent MRI twice in the same day. The software provided cartilage thickness and projected cartilage area ratio (thickness ≥ 1.5 mm) at 9 regions and 45 subregions of the knee without any manual correction. The interscan measurement error was calculated at each region and subregion from the data of nine donors, except for one donor who had body motion during the MRI examination. RESULTS: The interscan measurement error of cartilage thickness was less than 0.10 mm at all 9 regions and at 39 subregions among 45 subregions. The measurement errors ranged from 0.03 to 0.21 mm. The intraclass correlation coefficients (ICC) of cartilage thickness were higher than 0.75 at all 9 regions and 41 subregions. The interscan measurement error of the projected cartilage area ratio ranged from 0.01 to 0.03 for all 9 regions. CONCLUSIONS: This study clarified the interscan measurement error of the knee cartilage thickness and projected cartilage area ratio.

Synovial mesenchymal stem cells promote the meniscus repair in a novel pig meniscus injury model.

Stem cell therapy has potential for the treatment of degenerative meniscus injuries; however, an optimal animal model has not been established. Basic and clinical research show that synovial mesenchymal stem cells (MSCs) promote meniscus repair. The purposes of this study were to create a novel meniscus injury model in microminipigs and to investigate the effectiveness of synovial MSCs on meniscus healing in this model. The posterior portion of the medial meniscus in microminipigs was punctuated 200 times with a 23G needle. Allogenic synovial MSC suspension was placed on the injury site for 10 min for transplantation. The meniscus was evaluated histologically and via sagittal magnetic resonance imaging (MRI), radial MRI reconstructed in three dimensional, and T2 mapping at 1 and 8 weeks. Proteoglycan content stained with safranin-o disappeared 1 week after treatment in both the MSC and control groups but increased at 8 weeks only in the MSC group. Histological scores at 8 weeks were significantly higher in the MSC group than in the control group (n = 6). At 8 weeks, the T2 values of the MSC group were significantly closer to those of a normal meniscus than were those of the control group. High signal intensity areas of the MRIs and positive areas stained with picrosirius red coincided with meniscal lesions. In conclusion, we created a novel meniscus injury model in microminipigs. Evaluation via histology, MRIs, and polarized microscopy showed that transplantation of synovial MSCs improved meniscus healing.

Relationship between medial meniscus extrusion and cartilage measurements in the knee by fully automatic three-dimensional MRI analysis.

BACKGROUND: We developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject's actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30-79 years) from the "Kanagawa Knee Study." Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data. METHODS: We constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage. RESULTS: Dice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR. CONCLUSIONS: Our software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. Relations ips were observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurements in our cross-sectional study. TRIAL REGISTRATION: UMIN, UMIN000032826 ; 1 September 2018.

Projected Cartilage Area Ratio Determined by 3-Dimensional MRI Analysis: Validation of a Novel Technique to Evaluate Articular Cartilage.

We have developed 3-dimensional (3D) magnetic resonance imaging (MRI) analysis software that allows measurement of the projected cartilage area ratio with a particular thickness intended to allow quantitation of the cartilage in the knee. Our aims in this study were to validate the projected cartilage area ratio in both pig and human knees and to examine the ratio in patients reporting knee pain. METHODS: After 3D MRI reconstruction, the femoral cartilage was projected onto a flat surface. The projected cartilage area was determined in pig knees using our 3D MRI analysis software, and was compared with the area obtained with other software. The projected cartilage area ratio (for cartilage thickness ≥1.5 mm) at 4 segments was also validated in human knees. Finally, changes in the projected cartilage area ratio were examined in 8 patients with knee pain who had undergone 2 MR images at 3 to 21-month intervals. RESULTS: The projected cartilage areas determined with our 3D MRI analysis software were validated in pig knees. The projected cartilage area ratio at each segment in human knees had an intraclass correlation coefficient (ICC) of 0.87 to 0.99 (n = 16) between readers and 0.76 to 0.99 (n = 20) between measurements on repeat MR images. The projected cartilage area ratio (for cartilage thickness ≥1.5 mm) at the most affected segment in 8 human patients significantly decreased between the pairs of MR images obtained at intervals of 3 to 21 months. CONCLUSIONS: We proposed a novel evaluation method using 3D MRI to quantify the amount of cartilage in the knee. This method had a low measurement error in both pig and human knees. CLINICAL RELEVANCE: The projected cartilage area ratio based on a particular thickness may serve as a sensitive method for assessing changes in cartilage over time.

Application of 3D-MR image registration to monitor diseases around the knee joint.

PURPOSE: To estimate the accuracy and consistency of a method using a voxel-based MR image registration algorithm for precise monitoring of knee joint diseases. MATERIALS AND METHODS: Rigid body transformation was calculated using a normalized cross-correlation (NCC) algorithm involving simple manual segmentation of the bone region based on its anatomical features. The accuracy of registration was evaluated using four phantoms, followed by a consistency test using MR data from the 11 patients with knee joint disease. RESULTS: The registration accuracy in the phantom experiment was 0.49+/-0.19 mm (SD) for the femur and 0.56+/-0.21 mm (SD) for the tibia. The consistency value in the experiment using clinical data was 0.69+/-0.25 mm (SD) for the femur and 0.77+/-0.37 mm (SD) for the tibia. These values were all smaller than a voxel (1.25 x 1.25 x 1.5 mm). CONCLUSION: The present method based on an NCC algorithm can be used to register serial MR images of the knee joint with error on the order of a sub-voxel. This method would be useful for precisely assessing therapeutic response and monitoring knee joint diseases; normalized cross-correlation; accuracy.

Application of three-dimensional magnetic resonance image registration for monitoring hip joint diseases.

The purpose of this study was to estimate the accuracy of a method in which three-dimensional (3D) magnetic resonance (MR) volume registration is used for monitoring hip joint disease. Data were analyzed using a normalized cross-correlation (NCC) algorithm involving a user-selected 3D box including the proximal femur. Most of the femoral head was not included in the 3D box because it can become deformed during the course of disease. The accuracy of registration around the femoral head was evaluated using five phantoms and clinical MR data of 17 patients with hip joint disease. In the phantom experiment, registration accuracy was evaluated using four fiducial markers attached to the femoral head. In the experiment using clinical data, registration accuracy was evaluated using a landmark in the femoral head. The registration accuracy in the phantom and clinical experiment was 0.43+/-0.18 mm (S.D.) and 1.12+/-0.46 mm (S.D.), respectively. The former is a value less than half the minimum dimension of a voxel (1.25 x 1.25 x 1.0 mm). Although the latter is slightly larger than the minimum dimension of a voxel, actual errors would be smaller because of the uncertainty in landmark localization. In conclusion, the present method based on an NCC algorithm can be used to accurately register serial MR images of the femoral heads with an error on the order of a voxel. We believe that this method is sufficiently accurate for monitoring hip joint diseases.

In vivo three-dimensional wrist motion analysis using magnetic resonance imaging and volume-based registration.

This study represents a new attempt to non-invasively analyze three-dimensional motions of the wrist in vivo. A volume-based registration method using magnetic resonance imaging (MRI) was developed to avoid radiation exposure. The primary aim was to evaluate the accuracy of volume-based registration and compare it with surface-based registration. The secondary aim was to evaluate contributions of the scaphoid and lunate to global wrist motion during flexion-extension motion (FEM), radio-ulnar deviation (RUD) and radial-extension/ulnoflexion, "dart-throwing" motion (DTM) in the right wrists of 12 healthy volunteers. Volume-based registration displayed a mean rotation error of 1.29 degrees +/-1.03 degrees and a mean translation error of 0.21+/-0.25 mm and was significantly more accurate than surface-based registration in rotation. Different patterns of contribution of the scaphoid and lunate were identified for FEM, RUD, and DTM. The scaphoid contributes predominantly in the radiocarpal joint during FEM, in the midcarpal joint during RUD and almost equally between these joints during DTM. The lunate contributes almost equally in both joints during FEM and predominantly in the midcarpal joint during RUD and DTM.

A similarity measure for nonrigid volume registration using known joint distribution of targeted tissue: application to dynamic CT data of the liver.

A similarity measure for nonrigid volume registration with known joint distribution of a targeted tissue is developed to process tissue slide at the boundaries between the targeted and non-targeted tissues. Pre-segmentation of the targeted tissue is unnecessary. This measure is applied to registering volumes acquired at different time-phases in dynamic CT scans of the liver using contrast materials and can be derived for the case where only the joint distribution of the targeted tissue is known. The similarity measure is formulated as a likelihood by introducing a concept termed 'exclusivity condition' and embedded into a cost function for nonrigid registration to be combined with the smoothness term. In addition, a practical method for estimating the joint distribution of the liver from unregistered clinical CT data is described. We demonstrate experimentally that tissue slide is effectively processed by this proposed measure using simulated dynamic CT data generated from a software phantom and clinical CT data of eight patients.