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Fulltext Lung Diseases Detection Using Various Deep Learning Algorithms

Jasmine Pemeena Priyadarsini M, Kotecha K, Rajini GK, Hariharan K, Utkarsh Raj K, Bhargav Ram K, et al.

J Healthc Eng, 2023;2023:3563696.
PMID: 36776955 DOI: 10.1155/2023/3563696

The primary objective of this proposed framework work is to detect and classify various lung diseases such as pneumonia, tuberculosis, and lung cancer from standard X-ray images and Computerized Tomography (CT) scan images with the help of volume datasets. We implemented three deep learning models namely Sequential, Functional & Transfer models and trained them on open-source training datasets. To augment the patient's treatment, deep learning techniques are promising and successful domains that extend the machine learning domain where CNNs are trained to extract features and offers great potential from datasets of images in biomedical application. Our primary aim is to validate our models as a new direction to address the problem on the datasets and then to compare their performance with other existing models. Our models were able to reach higher levels of accuracy for possible solutions and provide effectiveness to humankind for faster detection of diseases and serve as best performing models. The conventional networks have poor performance for tilted, rotated, and other abnormal orientation and have poor learning framework. The results demonstrated that the proposed framework with a sequential model outperforms other existing methods in terms of an F1 score of 98.55%, accuracy of 98.43%, recall of 96.33% for pneumonia and for tuberculosis F1 score of 97.99%, accuracy of 99.4%, and recall of 98.88%. In addition, the functional model for cancer outperformed with an accuracy of 99.9% and specificity of 99.89% and paves way to less number of trained parameters, leading to less computational overhead and less expensive than existing pretrained models. In our work, we implemented a state-of-the art CNN with various models to classify lung diseases accurately.

Matched MeSH terms: Tomography, X-Ray Computed/methods
Fulltext Automated System for Identifying COVID-19 Infections in Computed Tomography Images Using Deep Learning Models

Abdulkareem KH, Mostafa SA, Al-Qudsy ZN, Mohammed MA, Al-Waisy AS, Kadry S, et al.

J Healthc Eng, 2022;2022:5329014.
PMID: 35368962 DOI: 10.1155/2022/5329014

Coronavirus disease 2019 (COVID-19) is a novel disease that affects healthcare on a global scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) images are presently being employed to assist doctors in detecting COVID-19 in its early stages. In several scenarios, a combination of epidemiological criteria (contact during the incubation period), the existence of clinical symptoms, laboratory tests (nucleic acid amplification tests), and clinical imaging-based tests are used to diagnose COVID-19. This method can miss patients and cause more complications. Deep learning is one of the techniques that has been proven to be prominent and reliable in several diagnostic domains involving medical imaging. This study utilizes a convolutional neural network (CNN), stacked autoencoder, and deep neural network to develop a COVID-19 diagnostic system. In this system, classification undergoes some modification before applying the three CT image techniques to determine normal and COVID-19 cases. A large-scale and challenging CT image dataset was used in the training process of the employed deep learning model and reporting their final performance. Experimental outcomes show that the highest accuracy rate was achieved using the CNN model with an accuracy of 88.30%, a sensitivity of 87.65%, and a specificity of 87.97%. Furthermore, the proposed system has outperformed the current existing state-of-the-art models in detecting the COVID-19 virus using CT images.

Matched MeSH terms: Tomography, X-Ray Computed/methods
Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information

Md Shah MN, Azman RR, Chan WY, Ng KH

Can Assoc Radiol J, 2024 Feb;75(1):92-97.
PMID: 37075322 DOI: 10.1177/08465371231171700

The past two decades have seen a significant increase in the use of CT, with a corresponding rise in the mean population radiation dose. This rise in CT use has caused improved diagnostic certainty in conditions that were not previously routinely evaluated using CT, such as headaches, back pain, and chest pain. Unused data, unrelated to the primary diagnosis, embedded within these scans have the potential to provide organ-specific measurements that can be used to prognosticate or risk-profile patients for a wide variety of conditions. The recent increased availability of computing power, expertise and software for automated segmentation and measurements, assisted by artificial intelligence, provides a conducive environment for the deployment of these analyses into routine use. Data gathering from CT has the potential to add value to examinations and help offset the public perception of harm from radiation exposure. We review the potential for the collection of these data and propose the incorporation of this strategy into routine clinical practice.

Matched MeSH terms: Tomography, X-Ray Computed*
Fulltext Application of three-dimensional computed tomography in craniofacial clinical practice and research

Anderson PJ, Yong R, Surman TL, Rajion ZA, Ranjitkar S

Aust Dent J, 2014 Jun;59 Suppl 1:174-85.
PMID: 24611727 DOI: 10.1111/adj.12154

Following the invention of the first computed tomography (CT) scanner in the early 1970s, many innovations in three-dimensional (3D) diagnostic imaging technology have occurred, leading to a wide range of applications in craniofacial clinical practice and research. Three-dimensional image analysis provides superior and more detailed information compared with conventional plain two-dimensional (2D) radiography, with the added benefit of 3D printing for preoperative treatment planning and regenerative therapy. Current state-of-the-art multidetector CT (MDCT), also known as medical CT, has an important role in the diagnosis and management of craniofacial injuries and pathology. Three-dimensional cone beam CT (CBCT), pioneered in the 1990s, is gaining increasing popularity in dental and craniofacial clinical practice because of its faster image acquisition at a lower radiation dose, but sound guidelines are needed to ensure its optimal clinical use. Recent innovations in micro-computed tomography (micro-CT) have revolutionized craniofacial biology research by enabling higher resolution scanning of teeth beyond the capabilities of MDCT and CBCT, presenting new prospects for translational clinical research. Even after four decades of refinement, CT technology continues to advance and broaden the horizons of craniofacial clinical practice and phenomics research.

Matched MeSH terms: Tomography, X-Ray Computed/methods*; Cone-Beam Computed Tomography; Multidetector Computed Tomography/methods
Radiation risk for patients undergoing cardiac computed tomography examinations

Alkhorayef M, Sulieman A, Alzahrani K, Abuzaid M, Alomair OI, Almuwannis M, et al.

Appl Radiat Isot, 2021 Feb;168:109520.
PMID: 33307438 DOI: 10.1016/j.apradiso.2020.109520

The various technological advancements in computed tomography (CT) have resulted in remarkable growth in the use of CT imaging in clinical practice, not the least of which has been its establishment as the most valuable imaging examination for the assessment of cardiovascular system disorders. The objective of this study was to assess the effective radiation dose and radiation risk for patients during cardiac CT procedures, based on studies from four different hospitals equipped with 128 slice CT equipment. A total of eighty-three patients were investigated in this study with different clinical indications. Effective doses were also calculated using software based on Monte Carlo simulation. The mean patient age (years), weight (kg), and body mass index (BMI (kg/m2)) were 49 ± 11, 82 ± 12, and 31 ± 6, respectively. The results of the study revealed that the tube voltage (kVp) and tube current-exposure time product (mAs) ranged between 100 to 140 and 50 to 840 respectively. The overall average patient dose values for the volume CT dose index [(CTDIvol), in mGy)] and dose length product (DLP) (in mGy·cm) were 34.8 ± 15 (3.7-117.0) and 383.8 ± 354 (46.0-3277.0) respectively. The average effective dose (mSv) was 15.2 ± 8 (1.2-61.8). The radiation dose values showed wide variation between different hospitals and even within the same hospital. The results indicate the need to optimize radiation dose and to establish diagnostic reference levels (DRLs) for patients undergoing coronary computed tomography angiography (CCTA), also to harmonize the imaging protocols to ensure reduced radiation risk.

Matched MeSH terms: Tomography, X-Ray Computed; Cone-Beam Computed Tomography; Computed Tomography Angiography
Application of 18F-FDG PET-CT in the management of pulmonary nodule and mass - a pictorial review

Wong TH, Tan TH, George UR, Kow KS, Liam CK

Med J Malaysia, 2019 Jun;74(3):250-256.
PMID: 31256186

BACKGROUND: Lung cancer is one of the leading causes of cancer-related mortality worldwide. Pulmonary nodules are commonly encountered in clinical practice because of the recent implementation of low-dose CT lung screening programme, incidental finding on cardiac CT or CT for nonthoracic related disease. 18F-FDG PET-CT plays an important role in the management of pulmonary nodules.
METHODS: In this pictorial review, we present six different scenarios of using 18F-FDG PET-CT in the management of suspicious pulmonary nodule or mass. The advantages and limitations of 18F-FDG PET-CT and Herder model are discussed.
RESULTS: 18F-FDG PET-CT with risk assessment using Herder model provides added value in characterising indeterminate pulmonary nodules. Besides, 18F-FDG PET-CT is valuable to guide the site of biopsy and provide accurate staging of lung cancer.
CONCLUSION: To further improve its diagnostic accuracy, careful history taking, and CT morphological evaluation should be taken into consideration when interpreting 18FFDG PET-CT findings in patients with these nodules.

Matched MeSH terms: Tomography, X-Ray Computed; Positron Emission Tomography Computed Tomography
Fulltext Systematic Review on the Accuracy of Positron Emission Tomography/Computed Tomography and Positron Emission Tomography/Magnetic Resonance Imaging in the Management of Ovarian Cancer: Is Functional Information Really Needed?

Suppiah S, Chang WL, Hassan HA, Kaewput C, Asri AAA, Saad FFA, et al.

World J Nucl Med, 2017 Jul-Sep;16(3):176-185.
PMID: 28670174 DOI: 10.4103/wjnm.WJNM_31_17

Ovarian cancer (OC) often presents at an advanced stage with frequent relapses despite optimal treatment; thus, accurate staging and restaging are required for improving treatment outcomes and prognostication. Conventionally, staging of OC is performed using contrast-enhanced computed tomography (CT). Nevertheless, recent advances in the field of hybrid imaging have made positron emission tomography/CT (PET/CT) and PET/magnetic resonance imaging (PET/MRI) as emerging potential noninvasive imaging tools for improved management of OC. Several studies have championed the role of PET/CT for the detection of recurrence and prognostication of OC. We provide a systematic review and meta-analysis of the latest publications regarding the role of molecular imaging in the management of OC. We retrieved 57 original research articles with one article having overlap in both diagnosis and staging; 10 articles (734 patients) regarding the role of PET/CT in diagnosis of OC; 12 articles (604 patients) regarding staging of OC; 22 studies (1429 patients) for detection of recurrence; and 13 articles for prognostication and assessment of treatment response. We calculated pooled sensitivity and specificity of PET/CT performance in various aspects of imaging of OC. We also discussed the emerging role of PET/MRI in the management of OC. We aim to give the readers and objective overview on the role of molecular imaging in the management of OC.

Matched MeSH terms: Tomography, X-Ray Computed; Positron Emission Tomography Computed Tomography
Fulltext Incremental Value of Single-photon Emission Computed Tomography-computed Tomography for Characterization of Skeletal Lesions in Breast Cancer Patients

Mahaletchumy T, AbAziz A

World J Nucl Med, 2017 Oct-Dec;16(4):303-310.
PMID: 29033679 DOI: 10.4103/1450-1147.215496

The incremental value of single-photon emission computed tomography-computed tomography (SPECT-CT) over planar bone scintigraphy and SPECT in detecting skeletal lesions in breast cancer patients and its effect on patient management is assessed in this study. This is a prospective study which was conducted over 1-year duration. Whole-body planar scintigraphy, SPECT, and SPECT-CT were performed in 85 breast cancer patients with total of 128 lesions. Correlative imaging and clinical follow-up was used as the reference standard. McNemar's multistep analysis was performed for each patient and each lesion. On patient-wise analysis, 47 patients had equivocal diagnosis on planar bone scintigraphy, 28 on SPECT, and eight on SPECT-CT. On lesion-wise analysis, there were 72 equivocal lesions on planar bone scintigraphy, 48 on SPECT, and 15 on SPECT-CT. Overall, SPECT-CT resulted in a significant reduction in the proportion of equivocal diagnosis on both patient-wise (P < 0.004) and lesion-wise basis (P < 0.004), irrespective of the skeletal region involved. The sensitivity on a per-patient basis was 43%, 58%, and 78% for planar bone scintigraphy, SPECT, and SPECT-CT, respectively. Similarly, the specificity was 85%, 92%, and 94% for planar bone scintigraphy, SPECT, and SPECT-CT, respectively. Patient management was correctly altered in 32% of the patients based on SPECT-CT interpretation. Our data suggest that adding SPECT-CT to whole-body imaging significantly improves sensitivity and specificity in diagnosing bone metastases and significantly reduces the proportion of equivocal diagnosis in all regions of the skeleton. The most important outcome is derived from the accurate alteration in patient management clinically by down- and up-staging of patients and a more precise identification of metastatic extent.

Matched MeSH terms: Tomography, Emission-Computed, Single-Photon; Single Photon Emission Computed Tomography Computed Tomography
Fulltext SPECT-CT in differentiating metastatic and degenerative lesions of the spine

Khadijah Abdul Hamid, Sazilah Ahmad Sarji, Mohammad Nazri Md Shah, Ibrahim Lutfi Shuaib

Malaysian Journal of Medicine and Health Sciences, 2020;16(102):31-37.
MyJurnal

Introduction: The purpose of this study was to determine the usefulness of SPECT-CT in differentiating metastatic and degenerative disease of the spine. Methods: Twenty-eight patients aged 50 years and above diagnosed with various cancers were referred for whole body (WB) planar bone scintigraphy. Those with a maximum three foci of tracer up- take in the spine were selected for the study. SPECT-CT of these areas of uptake was performed and the lesions were classified as degenerative, indeterminate or metastasis. A repeat study (WB planar bone scintigraphy and SPECT-CT) was performed between 3 to 12 months later. These areas of uptake were reassessed and compared with the first WB planar bone scintigraphy and SPECT-CT. The second SPECT-CT was used as the standard for the diagnosis. Results: Thirty-seven lesions in 28 patients were assessed. The sensitivity of the first WB planar bone scintigraphy, second WB planar bone scintigraphy and first SPECT-CT is 75%, 62.5% and 75% respectively. The specificity of the first WB planar bone scintigraphy, second WB planar bone scintigraphy and first SPECT-CT is 86%, 93%, 90% respectively. There was 2.7% of ‘indeterminate lesion’ in the first WB planar bone scintigraphy, 5.4% in the second WB planar bone scintigraphy, and 5.4% in the first SPECT-CT. The indeterminate lesions were resolved in the second SPECT-CT. Conclusion: SPECT- CT is useful in differentiating degenerative disease from metastatic lesions in the spine.

Matched MeSH terms: Tomography, X-Ray Computed; Single Photon Emission Computed Tomography Computed Tomography
Fulltext The effectiveness of Hyoscine-N-Butylbromide (Buscopan) in reducing physiological bowel uptake in 18F-FDG PET/CT

Mohd Fahmi Shukur Ramli, Fadzilah Hamzah, Muhamad Zabidi Ahmad

Malaysian Journal of Medicine and Health Sciences, 2018;14(201):1-7.
MyJurnal

Positron Emission Tomography-Computed Tomography (PET-CT) was introduced over four decades ago as an imaging tool to evaluate functional and anatomical aspects of disease such as malignancy. Besides pathological uptake, PET-CT also shows physiological uptake, especially in the gastrointestinal system, thus impacting diagnostic accuracy in these cases. There are many conditions that can attribute to increasing physiological uptake in PET-CT including microbial activity and drugs. Therefore, certain anti-spasmodic agents have been introduced to help reduce physiological uptake during scanning such as Hyoscine-n-butylbromide (Buscopan). This study aims to establish its effectiveness in reducing physiological bowel uptake on 18F-FDG PET-CT scan. Methods: 133 subjects were recruited in random for this study and divided into hyoscine (68 subjects) and control groups (65 subjects), respectively. Subjects in control group not given any anti-spasmodic medications and both groups received intravenous 18F-FDG according to body weight. PET-CT scan and images were interpreted by experienced nuclear medicine physician who scored the images according to the degree of bowel uptake and difficulty of image interpretation. Results: There were no statistical difference in bowel uptake based on SUV mean of the bowel and bowel-to-liver ratio between hyoscine and control groups. Conclusion: There was no significant effect of Hyoscine-n-butylbromide in reducing physiological bowel uptake in PET-CT scan.

Matched MeSH terms: Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
Papillary Thyroid Carcinoma Presenting As a Cystic Neck Lesion: Case Series

Subha ST, Bakri MA, Salleh H, Doi M, Nordin AJ

Iran J Otorhinolaryngol, 2018 Jan;30(96):49-54.
PMID: 29387664

Introduction: Papillary thyroid carcinoma (PTC) constitutes 75-85% of all thyroid cancers. PTC usually presents as a subtle, commonly slow-growing, painless thyroid mass or a solitary nodule in the neck. This presentation of a cystic neck lump, without the presence of a thyroid nodule, may imitate the course of a benign disease, thus delaying diagnosis and proper treatment.
Case Report: Three cases that had been initially presented as a cystic neck lesion in which a benign etiology was considered primarily were compiled in this study. PTC was only diagnosed after surgical excision of these cystic neck lesions in the first two cases, and after performing fine needle aspiration cytology (FNAC) and an 18fluorine-fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG-PET CT) scan in the latter case.
Conclusion: PTC can sometimes present as a cystic neck mass; a presentation which is usually related to a benign lesion. This case series emphasizes that patients who appear to have a solitary cystic neck mass must be treated with a high index of clinical suspicion. Although not a first-line imaging modality, 18F-FDG-PET can be extremely useful in assessing patients with a cystic neck lesion, where diagnosis is still uncertain after standard investigations such as ultrasonography and FNAC have been performed.

Matched MeSH terms: Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
Fulltext The value of 18F-fluorodeoxyglucose –positron emission tomography/ computed tomography (18F- FDG PET/CT) in the staging and impact on the management of patients with nasopharyngeal carcinoma

Sethu Thakachy Subha, Fathinul Fikri Ahmad Saad, Abdul Jalil Nordin, Saraiza Abu Bakar

Pertanika Journal of Science & Technology, 2017;25(3):687-696.
MyJurnal

This study sought to prospectively evaluate the influence of contrasted fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDGPET/CT) in the staging of and impact on the management plan for treatment in patients with nasopharyngeal carcinoma (NPC). A total of 14 histologically proven NPC patients (mean age: 44.64±4.01years) were included in the study. These patients underwent contrasted Computed Tomography (CT) as well as 18F-FDGPET/CT imaging. Staging was based on the 7th edition of the American Joint Committee on Cancer Tumor Node Metastases (AJCCTNM) recommendations.The oncologist was asked to prospectively assign a treatment plan for all patients being evaluated by CT and 18F-FDGPET/CT. The treatment plans were compared with the incremental information supplied by the FDG-PET/CT. The maximum standardised uptake value (SUVmax) and the widest dimension of the primary tumour, cervical lymph nodes size and the distant metastatic lesions were quantified on the co-registered PET/CT images by two experienced nuclear radiologists. The contrasted 18F-FDGPET/CT changed the management intent in nine patients (64.7%). A univariate analysis showed that there were significant correlations between SUVmax and the size of the metastatic
lymph nodes (R2 =0.0761, p

Matched MeSH terms: Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space

Fallahpoor M, Chakraborty S, Pradhan B, Faust O, Barua PD, Chegeni H, et al.

Comput Methods Programs Biomed, 2024 Jan;243:107880.
PMID: 37924769 DOI: 10.1016/j.cmpb.2023.107880

Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurology, cardiology, and emerging medical fields. The success stems from the cohesive information that hybrid PET/CT imaging offers, surpassing the capabilities of individual modalities when used in isolation for different malignancies. However, manual image interpretation requires extensive disease-specific knowledge, and it is a time-consuming aspect of physicians' daily routines. Deep learning algorithms, akin to a practitioner during training, extract knowledge from images to facilitate the diagnosis process by detecting symptoms and enhancing images. This acquired knowledge aids in supporting the diagnosis process through symptom detection and image enhancement. The available review papers on PET/CT imaging have a drawback as they either included additional modalities or examined various types of AI applications. However, there has been a lack of comprehensive investigation specifically focused on the highly specific use of AI, and deep learning, on PET/CT images. This review aims to fill that gap by investigating the characteristics of approaches used in papers that employed deep learning for PET/CT imaging. Within the review, we identified 99 studies published between 2017 and 2022 that applied deep learning to PET/CT images. We also identified the best pre-processing algorithms and the most effective deep learning models reported for PET/CT while highlighting the current limitations. Our review underscores the potential of deep learning (DL) in PET/CT imaging, with successful applications in lesion detection, tumor segmentation, and disease classification in both sinogram and image spaces. Common and specific pre-processing techniques are also discussed. DL algorithms excel at extracting meaningful features, and enhancing accuracy and efficiency in diagnosis. However, limitations arise from the scarcity of annotated datasets and challenges in explainability and uncertainty. Recent DL models, such as attention-based models, generative models, multi-modal models, graph convolutional networks, and transformers, are promising for improving PET/CT studies. Additionally, radiomics has garnered attention for tumor classification and predicting patient outcomes. Ongoing research is crucial to explore new applications and improve the accuracy of DL models in this rapidly evolving field.

Matched MeSH terms: Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
Medical imaging modalities using nanoprobes for cancer diagnosis: A literature review on recent findings

Shahbazi-Gahrouei D, Moradi Khaniabadi P, Moradi Khaniabadi B, Shahbazi-Gahrouei S

J Res Med Sci, 2019;24:38.
PMID: 31143239 DOI: 10.4103/jrms.JRMS_437_18

Medical imaging modalities are used for different types of cancer detection and diagnosis. Recently, there have been a lot of studies on developing novel nanoparticles as new medical imaging contrast agents for the early detection of cancer. The aim of this review article is to categorize the medical imaging modalities accompanying with using nanoparticles to improve potential imaging for cancer detection and hence valuable therapy in the future. Nowadays, nanoparticles are becoming potentially transformative tools for cancer detection for a wide range of imaging modalities, including computed tomography (CT), magnetic resonance imaging, single photon emission CT, positron emission tomography, ultrasound, and optical imaging. The study results seen in the recent literature provided and discussed the diagnostic performance of imaging modalities for cancer detections and their future directions. With knowledge of the correlation between the application of nanoparticles and medical imaging modalities and with the development of targeted contrast agents or nanoprobes, they may provide better cancer diagnosis in the future.

Matched MeSH terms: Tomography, X-Ray Computed; Tomography, Emission-Computed, Single-Photon; Positron-Emission Tomography
Fulltext Incidental Follicular Thyroid Carcinoma Detected on F-18 FDG PET CT Imaging for Breast Cancer Staging: A Case Report

Cheen Hoe AK, Hamzah F, Abdul Khader MA

Malays J Med Sci, 2014 Sep-Oct;21(5):75-7.
PMID: 25977638 MyJurnal

The detection rate of thyroid incidentalomas is increasing; in fact, as many as 2.3% of patients undergoing FDG PET-CT for other indications have been found to have thyroid incidentalomas. The risk of malignancy in these thyroid incidentalomas can be as high as 47%. The increased uptake and the focal uptake pattern of F-18 fluorodeoxyglucose (FDG) in the thyroid during positron emission tomography (PET)-computed tomography (CT), and the calcification of the thyroid incidentaloma, are associated with even higher risk of malignancy. We report a case of a lady undergoing FDG PET-CT for breast cancer staging but noted to have a calcified thyroid incidentaloma, which was proven to be follicular thyroid carcinoma.

Matched MeSH terms: Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
Fulltext Chest imaging features of patients afflicted with Influenza A (H1N1) in a Malaysian tertiary referral centre

Bux S, Mohd Ramli N, Ahmad Sarji S, Kamarulzaman A

Biomed Imaging Interv J, 2010 Oct-Dec;6(4):e35.
PMID: 21611071 MyJurnal DOI: 10.2349/biij.6.4.e35

This is a retrospective descriptive study of the chest imaging findings of 118 patients with confirmed A(H1N1) in a tertiary referral centre. About 42% of the patients had positive initial chest radiographic (CXR) findings. The common findings were bi-basal air-space opacities and perihilar reticular and alveolar infiltrates. In select cases, high-resolution computed tomography (CT) imaging showed ground-glass change with some widespread reticular changes and atelectasis.

Matched MeSH terms: Tomography; Tomography, X-Ray Computed
Fulltext Computed tomography (CT) in blunt liver injury: a pictorial essay

Radhiana H, Azian AA, Razali MR, Kamariah CM

Med J Malaysia, 2010 Dec;65(4):319-25.
PMID: 21901958

Computed tomography (CT) is widely used in assessing clinically stable patients with blunt abdominal trauma. In these patients, liver is one of the commonest organs being injured and CT can accurately identify and assess the extent of the injury. The CT features of blunt liver trauma include laceration, subcapsular or parenchymal haematomas, active haemorrhage and vascular injuries. Widespread use of CT has notably influenced the management of blunt liver injury from routine surgical to nonsurgical management. We present pictorial illustrations of various liver injuries depicted on CT in patients with blunt trauma.

Matched MeSH terms: Tomography, X-Ray Computed/methods*
Real time mass flow rate measurement using multiple fan beam optical tomography

Abdul Rahim R, Leong LC, Chan KS, Rahiman MH, Pang JF

ISA Trans, 2008 Jan;47(1):3-14.
PMID: 17709106

This paper presents the implementing multiple fan beam projection technique using optical fibre sensors for a tomography system. From the dynamic experiment of solid/gas flow using plastic beads in a gravity flow rig, the designed optical fibre sensors are reliable in measuring the mass flow rate below 40% of flow. Another important matter that has been discussed is the image processing rate or IPR. Generally, the applied image reconstruction algorithms, the construction of the sensor and also the designed software are considered to be reliable and suitable to perform real-time image reconstruction and mass flow rate measurements.

Matched MeSH terms: Tomography/instrumentation*
Fulltext Spiral CT angiography in an infant with a hypoplastic aortic arch

Man Harun S, Faridah Y

Biomed Imaging Interv J, 2006 Apr;2(2):e11.
PMID: 21614223 MyJurnal DOI: 10.2349/biij.2.2.e11

The advent of multislice computed tomography (CT) has revolutionised the performance of body CT and allowed the development of CT angiography (CTA). CTA is a robust and minimally invasive method of visualizing the arterial vascular system. The newer generation of multidetector scans has allowed for shorter scanning times with no respiratory misregistration at peak vascular opacification following peripheral contrast injection. The volume of data obtained from these scans can be further manipulated to generate two-dimensional (2D) and three-dimensional (3D) images with no increase in radiation to the patient. Hence, CTA has gained popularity and importance as the alternative diagnostic tool especially for ill patients in which conventional angiography is inadvisable.We present an infant with coarctation of the aorta and hypoplastic aortic arch, in which CT angiography was used to pinpoint the diagnosis. The CT findings were subsequently confirmed at surgery.

Matched MeSH terms: Multidetector Computed Tomography; Computed Tomography Angiography
Improving the (18)F-fluoromethylcholine ((18)F-FCH) radiochemical yield via optimising the azeotropic drying of non-carrier-added (18)F-fluorine

Hassan H, Abu Bakar S, Halim KN, Idris J, Ahmad Saad FF, Nordin AJ

J Labelled Comp Radiopharm, 2015 Sep-Oct;58(11-12):458-9.
PMID: 26395258 DOI: 10.1002/jlcr.3347

(18)F-Fluoromethylcholine ((18)F-FCH) has been suggested as one of the reputable imaging tracers for diagnosis of prostate tumour in PET/CT examination. Nevertheless, it has never been synthesised in Malaysia. We acknowledged the major problem with (18)F-FCH is due to its relatively low radiochemical yield at the end of synthesis (EOS). Therefore, this technical note presents improved (18)F-FCH radiochemical yields after carrying out optimisation on azeotropic drying of non-carrier-added (18)F-Fluorine.

Matched MeSH terms: Positron Emission Tomography Computed Tomography

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