Multi-modal evaluation of respiratory diaphragm motion in chronic obstructive pulmonary disease using MRI series and CT images.

PURPOSE: Chronic obstructive pulmonary disease (COPD), characterized by airflow limitation and breathing difficulty, is usually caused by prolonged inhalation of toxic substances or long-term smoking habits. Some abnormal features of COPD can be observed using medical imaging methods, such as magnetic resonance imaging (MRI) and computed tomography (CT). This study aimed to conduct a multi-modal analysis of COPD, focusing on assessing respiratory diaphragm motion using MRI series in conjunction with low attenuation volume (LAV) data derived from CT images. MATERIALS AND METHOD: This study utilized MRI series from 10 normal subjects and 24 COPD patients, along with thoracic CT images from the same patients. Diaphragm profiles in the sagittal thoracic MRI series were extracted using field segmentation, and diaphragm motion trajectories were generated from estimated diaphragm displacements via registration. Re-sliced sagittal CT images were used to calculate regional LAVs for four distinct lung regions. The similarities among diaphragm motion trajectories at various positions were assessed, and their correlations with regional LAVs were analyzed. RESULTS: Compared with the normal subjects, patients with COPD typically exhibited fewer similarities in diaphragm motion, as indicated by the mean normalized correlation coefficient of the vertical motion component (0.96 for normal subjects vs. 0.76 for severity COPD patients). This reduction was significantly correlated with the LAV% in the two lower lung regions with a regression coefficient of 0.81. CONCLUSION: Our proposed evaluation method may assist in the diagnosis and therapy planning for patients with COPD.

Measuring and imaging of transcutaneous bilirubin, hemoglobin, and melanin based on diffuse reflectance spectroscopy.

Significance: Evaluation of biological chromophore levels is useful for detection of various skin diseases, including cancer, monitoring of health status and tissue metabolism, and assessment of clinical and physiological vascular functions. Clinically, it is useful to assess multiple different chromophores in vivo with a single technique or instrument. Aim: To investigate the possibility of estimating the concentration of four chromophores, bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin from diffuse reflectance spectra in the visible region. Approach: A new diffuse reflectance spectroscopic method based on the multiple regression analysis aided by Monte Carlo simulations for light transport was developed to quantify bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin. Three different experimental animal models were used to induce hyperbilirubinemia, hypoxemia, and melanogenesis in rats. Results: The estimated bilirubin concentration increased after ligation of the bile duct and reached around 18 mg/dl at 50 h after the onset of ligation, which corresponds to the reference value of bilirubin measured by a commercially available transcutaneous bilirubin meter. The concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin decreased and increased, respectively, as the fraction of inspired oxygen decreased. Consequently, the tissue oxygen saturation dramatically decreased. The time course of melanin concentration after depilation of skin on the back of rats was indicative of the supply of melanosomes produced by melanocytes of hair follicles to the growing hair shaft. Conclusions: The results of our study showed that the proposed method is capable of the in vivo evaluation of percutaneous bilirubin level, skin hemodynamics, and melanogenesis in rats, and that it has potential as a tool for the diagnosis and management of hyperbilirubinemia, hypoxemia, and pigmented skin lesions.

Computer-aided diagnosis for screening of lower extremity lymphedema in pelvic computed tomography images using deep learning.

Lower extremity lymphedema (LEL) is a common complication after gynecological cancer treatment, which significantly reduces the quality of life. While early diagnosis and intervention can prevent severe complications, there is currently no consensus on the optimal screening strategy for postoperative LEL. In this study, we developed a computer-aided diagnosis (CAD) software for LEL screening in pelvic computed tomography (CT) images using deep learning. A total of 431 pelvic CT scans from 154 gynecological cancer patients were used for this study. We employed ResNet-18, ResNet-34, and ResNet-50 models as the convolutional neural network (CNN) architecture. The input image for the CNN model used a single CT image at the greater trochanter level. Fat-enhanced images were created and used as input to improve classification performance. Receiver operating characteristic analysis was used to evaluate our method. The ResNet-34 model with fat-enhanced images achieved the highest area under the curve of 0.967 and an accuracy of 92.9%. Our CAD software enables LEL diagnosis from a single CT image, demonstrating the feasibility of LEL screening only on CT images after gynecologic cancer treatment. To increase the usefulness of our CAD software, we plan to validate it using external datasets.

Detection improvement of gliomas in hyperspectral imaging of protoporphyrin IX fluorescence - in vitro comparison of visual identification and machine thresholds.

BACKGROUND: 5-aminolevulinic acid (5-ALA) - precursor of protoporphyrin IX (PpIX) - is utilized in fluorescence guided surgery (FGS) of high-grade gliomas. PpIX is used to identify traces of glioma during resection. Visual inspection of the fluorescence seems inaccurate in comparison to optic techniques such as hyperspectral imaging (HSI). AIM: To characterize the limits of PpIX fluorescence detection of (i) visual evaluation and (ii) HSI analysis and to (iii) develop a classification system for visible and non-visible PpIX fluorescence. METHODS: Samples with increasing concentrations (C) of PpIX and non-fluorescent controls were evaluated using a surgical microscope under blue light illumination. Similar samples were imaged with a HSI system tuned to PpIX fluorescence peak wavelength (635 nm) and control (RGB) channels. Samples' intensities were defined, leading to 96 analysed pixels after batching. RESULTS: Three expert neurosurgeons assessed the PpIX samples (n = 16) and controls (n = 8) with unanimous decisions (ICC = 0.704), resulting in 63% recognition rate, 48% sensitivity, 92% specificity, 92% positive predictive value (PPV) and 47% negative predictive value (NPV). HSI image analysis, comparing mean relative values, resulted in 96%, 100%, 86%, 94%, 100%, respectively. Minimum PpIX concentration detection for experts was 0.6-1.8 µmol/l and HSI's 0.03-0.15 µmol/l. CONCLUSIONS: PpIX concentrations of low-grade gliomas, and those reported on glioblastoma infiltration zones, are below experts' detection threshold. HSI analysis exceeds the performance of expert's visual inspection nearly by 20-fold. Hybrid FGS-HSI systems should be investigated in parallel to long-term outcomes. Described methods are applicable as a standard for calibration, testing and development of subvisual FGS techniques.

Connector sensors for permittivity-based thrombus monitoring in extracorporeal life support.

Extracorporeal circulation is vital in cardiovascular surgery, but thrombus formation at connector interface is a major threat. Optical coherence tomography (OCT) is presently used to monitor thrombogenesis at connectors, but it is expensive to install and complex to use. This study fabricated and evaluated a connector sensor for real-time permittivity-based thrombus monitoring at tube-connector interface. Computational simulations were initially done to pre-evaluate the applicability of connector sensor. The sensor was fabricated by incorporating two stainless steel electrodes on acrylic tube for measuring permittivity changes at the tube-connector interface. OCT images were also taken from the interface at intervals for comparisons. Results show that the sensor was able to detect thrombus formation at the interface in form of sudden rise in permittivity after time t = 9 min. The permittivity changes were confirmed by OCT images which showed thrombus formation after time t = 14 min implying that permittivity changes were due to regional aggregation of red blood cells. The connector sensor is therefore envisioned as an affordable alternative to OCT for real-time permittivity-based monitoring of thrombogenesis at tube-connector interface.

Three-Dimensional Vessel Segmentation in Whole-Tissue and Whole-Block Imaging Using a Deep Neural Network: Proof-of-Concept Study.

In the field of pathology, micro-computed tomography (micro-CT) has become an attractive imaging modality because it enables full analysis of the three-dimensional characteristics of a tissue sample or organ in a noninvasive manner. However, because of the complexity of the three-dimensional information, understanding would be improved by development of analytical methods and software such as those implemented for clinical CT. As the accurate identification of tissue components is critical for this purpose, we have developed a deep neural network (DNN) to analyze whole-tissue images (WTIs) and whole-block images (WBIs) of neoplastic cancer tissue using micro-CT. The aim of this study was to segment vessels from WTIs and WBIs in a volumetric segmentation method using DNN. To accelerate the segmentation process while retaining accuracy, a convolutional block in DNN was improved by introducing a residual inception block. Three colorectal tissue samples were collected and one WTI and 70 WBIs were acquired by a micro-CT scanner. The implemented segmentation method was then tested on the WTI and WBIs. As a proof-of-concept study, our method successfully segmented the vessels on all WTI and WBIs of the colorectal tissue sample. In addition, despite the large size of the images for analysis, all segmentation processes were completed in 10 minutes.

Relationship between knee osteoarthritis and meniscal shape in observation of Japanese patients by using magnetic resonance imaging.

BACKGROUND: The aims of this study were to reveal the characteristics of the meniscal shape at each knee osteoarthritis (OA) severity level and to predict trends or patterns of the meniscal shape change as associated with knee OA progression. METHODS: Fifty-one patients diagnosed with knee OA based on X-ray and magnetic resonance (MR) images were evaluated. They were divided into three groups based on the Kellgren-Lawrence (KL) grade: normal group (KL grade of 0 or 1), mild group (KL grade of 2 or 3), and severe group (KL grade of 4). We measured the patients' meniscal size and meniscal extrusion using MR images. In addition, semiquantitative measurement was performed using MR images to determine the arthritic status of the corresponding compartment using a whole-organ magnetic resonance imaging score (WORMS). RESULTS: The longitudinal diameter and posterior wedge angle of the medial meniscus were significantly larger, and the posterior wedge width of the medial meniscus was significantly smaller in the severe group than in the normal group. The WORMS scores for cartilage and osteophytes in the medial region were significantly different among the groups. The WORMS score of each region was strongly correlated with the longitudinal diameter. The WORMS scores of the lateral region were lower than those of the medial region. CONCLUSION: Our observation of the shape change of the medial meniscus in the posterior region was roughly consistent with that in many previous studies of meniscal degeneration. On the other hand, we saw that the most relevant relation between the progression of the knee OA and the deformation of the meniscus was in the longitudinal direction.

Geometry calibration between X-ray source and detector for tomosynthesis with a portable X-ray system.

PURPOSE: Tomosynthesis is attracting attention as a low-dose tomography technology compared with X-ray CT. However, conventional tomosynthesis imaging devices are large and stationary. Furthermore, there is a limitation in the working range of the X-ray source during image acquisition. We have previously proposed the use of a portable X-ray device for tomosynthesis that can be used for ward rounds and emergency medicine. The weight of this device can be reduced by using a flat panel detector (FPD), and flexibility is realized by the free placement of the X-ray source and FPD. Tomosynthesis using a portable X-ray device requires calibration of the geometry between the X-ray source and detector at each image acquisition. We propose a method for geometry calibration and demonstrate tomosynthesis image reconstruction by this method. METHODS: An image processing-based calibration method using an asymmetric and multilayered calibration object (AMCO) is presented. Since the AMCO is always attached to the X-ray source housing for geometry calibration, the additional setting of a calibration object or marker around or on the patients is not required. The AMCO's multilayer structure improves the calibration accuracy, especially in the out-of-plane direction. RESULTS: Two experiments were conducted. The first was performed to evaluate the calibration accuracy using an XY positioning stage and a gonio stage. As a result, an accuracy of approximately 1 mm was achieved both in the in-plane and out-of-plane directions. An angular accuracy of approximately [Formula: see text] was confirmed. The second experiment was conducted to evaluate the reconstructed image using a foot model phantom. Only the sagittal plane could be clearly observed with the proposed method. CONCLUSION: We proposed a tomosynthesis imaging system using a portable X-ray device. From the experimental results, the proposed method could provide sufficient calibration accuracy and a clear sagittal plane of the reconstructed tomosynthesis image.

Deformable image registration between pathological images and MR image via an optical macro image.

Computed tomography (CT) and magnetic resonance (MR) imaging have been widely used for visualizing the inside of the human body. However, in many cases, pathological diagnosis is conducted through a biopsy or resection of an organ to evaluate the condition of tissues as definitive diagnosis. To provide more advanced information onto CT or MR image, it is necessary to reveal the relationship between tissue information and image signals. We propose a registration scheme for a set of PT images of divided specimens and a 3D-MR image by reference to an optical macro image (OM image) captured by an optical camera. We conducted a fundamental study using a resected human brain after the death of a brain cancer patient. We constructed two kinds of registration processes using the OM image as the base for both registrations to make conversion parameters between the PT and MR images. The aligned PT images had shapes similar to the OM image. On the other hand, the extracted cross-sectional MR image was similar to the OM image. From these resultant conversion parameters, the corresponding region on the PT image could be searched and displayed when an arbitrary pixel on the MR image was selected. The relationship between the PT and MR images of the whole brain can be analyzed using the proposed method. We confirmed that same regions between the PT and MR images could be searched and displayed using resultant information obtained by the proposed method. In terms of the accuracy of proposed method, the TREs were 0.56±0.39mm and 0.87±0.42mm. We can analyze the relationship between tissue information and MR signals using the proposed method.

Registration and Summation of Respiratory-Gated or Breath-Hold PET Images Based on Deformation Estimation of Lung from CT Image.

Lung motion due to respiration causes image degradation in medical imaging, especially in nuclear medicine which requires long acquisition times. We have developed a method for image correction between the respiratory-gated (RG) PET images in different respiration phases or breath-hold (BH) PET images in an inconsistent respiration phase. In the method, the RG or BH-PET images in different respiration phases are deformed under two criteria: similarity of the image intensity distribution and smoothness of the estimated motion vector field (MVF). However, only these criteria may cause unnatural motion estimation of lung. In this paper, assuming the use of a PET-CT scanner, we add another criterion that is the similarity for the motion direction estimated from inhalation and exhalation CT images. The proposed method was first applied to a numerical phantom XCAT with tumors and then applied to BH-PET image data for seven patients. The resultant tumor contrasts and the estimated motion vector fields were compared with those obtained by our previous method. Through those experiments we confirmed that the proposed method can provide an improved and more stable image quality for both RG and BH-PET images.

Development of fast patient position verification software using 2D-3D image registration and its clinical experience.

To improve treatment workflow, we developed a graphic processing unit (GPU)-based patient positional verification software application and integrated it into carbon-ion scanning beam treatment. Here, we evaluated the basic performance of the software. The algorithm provides 2D/3D registration matching using CT and orthogonal X-ray flat panel detector (FPD) images. The participants were 53 patients with tumors of the head and neck, prostate or lung receiving carbon-ion beam treatment. 2D/3D-ITchi-Gime (ITG) calculation accuracy was evaluated in terms of computation time and registration accuracy. Registration calculation was determined using the similarity measurement metrics gradient difference (GD), normalized mutual information (NMI), zero-mean normalized cross-correlation (ZNCC), and their combination. Registration accuracy was dependent on the particular metric used. Representative examples were determined to have target registration error (TRE) = 0.45 ± 0.23 mm and angular error (AE) = 0.35 ± 0.18° with ZNCC + GD for a head and neck tumor; TRE = 0.12 ± 0.07 mm and AE = 0.16 ± 0.07° with ZNCC for a pelvic tumor; and TRE = 1.19 ± 0.78 mm and AE = 0.83 ± 0.61° with ZNCC for lung tumor. Calculation time was less than 7.26 s.The new registration software has been successfully installed and implemented in our treatment process. We expect that it will improve both treatment workflow and treatment accuracy.

Development of a small prototype for a proof-of-concept of OpenPET imaging.

The OpenPET geometry is our new idea to visualize a physically opened space between two detector rings. In this paper, we developed the first small prototype to show a proof-of-concept of OpenPET imaging. Two detector rings of 110 mm diameter and 42 mm axial length were placed with a gap of 42 mm. The basic imaging performance was confirmed through phantom studies; the open imaging was realized at the cost of slight loss of axial resolution and 24% loss of sensitivity. For a proof-of-concept of PET image-guided radiation therapy, we carried out the in-beam tests with (11)C radioactive beam irradiation in the heavy ion medical accelerator in Chiba to visualize in situ distribution of primary particles stopped in a phantom. We showed that PET images corresponding to dose distribution were obtained. For an initial proof-of-concept of real-time multimodal imaging, we measured a tumor-inoculated mouse with (18)F-FDG, and an optical image of the mouse body surface was taken during the PET measurement by inserting a digital camera in the ring gap. We confirmed that the tumor in the gap was clearly visualized. The result also showed the extension effect of an axial field-of-view (FOV); a large axial FOV of 126 mm was obtained with the detectors that originally covered only an 84 mm axial FOV. In conclusion, our initial imaging studies showed promising performance of the OpenPET.