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  1. Tooyama I, Yanagisawa D, Taguchi H, Kato T, Hirao K, Shirai N, et al.
    Ageing Res Rev, 2016 09;30:85-94.
    PMID: 26772439 DOI: 10.1016/j.arr.2015.12.008
    The formation of senile plaques followed by the deposition of amyloid-β is the earliest pathological change in Alzheimer's disease. Thus, the detection of senile plaques remains the most important early diagnostic indicator of Alzheimer's disease. Amyloid imaging is a noninvasive technique for visualizing senile plaques in the brains of Alzheimer's patients using positron emission tomography (PET) or magnetic resonance imaging (MRI). Because fluorine-19 ((19)F) displays an intense nuclear magnetic resonance signal and is almost non-existent in the body, targets are detected with a higher signal-to-noise ratio using appropriate fluorinated contrast agents. The recent introduction of high-field MRI allows us to detect amyloid depositions in the brain of living mouse using (19)F-MRI. So far, at least three probes have been reported to detect amyloid deposition in the brain of transgenic mouse models of Alzheimer's disease; (E,E)-1-fluoro-2,5-bis-(3-hydroxycarbonyl-4-hydroxy)styrylbenzene (FSB), 1,7-bis(4'-hydroxy-3'-trifluoromethoxyphenyl)-4-methoxycarbonylethyl-1,6-heptadiene3,5-dione (FMeC1, Shiga-Y5) and 6-(3',6',9',15',18',21'-heptaoxa-23',23',23'-trifluorotricosanyloxy)-2-(4'-dimethylaminostyryl)benzoxazole (XP7, Shiga-X22). This review presents the recent advances in amyloid imaging using (19)F-MRI, including our own studies.
    Matched MeSH terms: Multimodal Imaging/methods
  2. 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: Multimodal Imaging/methods
  3. Yeong CH, Abdullah BJ, Ng KH, Chung LY, Goh KL, Perkins AC
    Nucl Med Commun, 2013 Jul;34(7):645-51.
    PMID: 23612704 DOI: 10.1097/MNM.0b013e32836141e4
    This paper describes the use of gamma scintigraphic and magnetic resonance (MR) fusion images for improving the anatomical delineation of orally administered radiotracers used in gastrointestinal (GI) transit investigations.
    Matched MeSH terms: Multimodal Imaging/methods*
  4. Shahila T, Rushdan MN
    Med J Malaysia, 2011 Oct;66(4):353-8.
    PMID: 22299557 MyJurnal
    The objective of this study was to evaluate the role of PET/CT in diagnosing and evaluating patients with suspected gynaecological tumour recurrence and persistent disease following treatment. This cross-sectional study involving 26 patients with gynaecological malignancies was carried out at Hospital Sultanah Bahiyah between 2006 and 2008. The standard imaging modalities disclosed possible tumour recurrence or persistent disease in 24 of the 26 patients (92.3%). Two patients with negative CT were subjected to PET/CT due to persistently elevated serum tumour markers. PET/CT confirmed tumour recurrence in 9 (34.6%) patients and was inconclusive in 2 (7.7%) patients. No abnormal uptake was observed in 15 (57.7%) patients. Of the 9 patients with positive PET/CT, 7 (77.8%) had a repeat PET/CT and 2 (22.2%) had a CT following subsequent treatment which confirmed no further evidence of disease. Patients with negative or inconclusive PET/CT were either continued with routine follow-up or had a close monitoring by either CT or serum tumour markers. With the availability of PET/CT, almost two-third of patients did not have to undergo unnecessary chemotherapy or radiotherapy. Integrated PET/CT imaging offers beneficial effects in both diagnosing and evaluating suspected tumour recurrence and persistent disease in gynaecological malignancies.
    Matched MeSH terms: Multimodal Imaging/methods*
  5. Leong SH, Ong SH
    PLoS One, 2017;12(7):e0180307.
    PMID: 28686634 DOI: 10.1371/journal.pone.0180307
    This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.
    Matched MeSH terms: Multimodal Imaging/methods
  6. Javed E, Faye I, Malik AS, Abdullah JM
    J Neurosci Methods, 2017 11 01;291:150-165.
    PMID: 28842191 DOI: 10.1016/j.jneumeth.2017.08.020
    BACKGROUND: Simultaneous electroencephalography (EEG) and functional magnetic resonance image (fMRI) acquisitions provide better insight into brain dynamics. Some artefacts due to simultaneous acquisition pose a threat to the quality of the data. One such problematic artefact is the ballistocardiogram (BCG) artefact.

    METHODS: We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. The algorithm does not require extra electrocardiogram (ECG) or electrooculogram (EOG) recordings to extract the BCG artefact.

    RESULTS: The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. On the other hand, real data were recorded with two conditions, i.e. resting state (eyes closed dataset) and task influenced (event-related potentials (ERPs) dataset). Using qualitative (visual inspection) and quantitative (similarity index, improved normalized power spectrum (INPS) ratio, power spectrum, sample entropy (SE)) evaluation parameters, the assessment results showed that the proposed method can efficiently reduce the BCG artefact while preserving the neuronal signals.

    COMPARISON WITH EXISTING METHODS: Compared with conventional methods, namely, average artefact subtraction (AAS), optimal basis set (OBS) and combined independent component analysis and principal component analysis (ICA-PCA), the statistical analyses of the results showed that the proposed method has better performance, and the differences were significant for all quantitative parameters except for the power and sample entropy.

    CONCLUSIONS: The proposed method does not require any reference signal, prior information or assumption to extract the BCG artefact. It will be very useful in circumstances where the reference signal is not available.

    Matched MeSH terms: Multimodal Imaging/methods*
  7. Wong PS, Lau WF, Worth LJ, Thursky KA, Drummond E, Slavin MA, et al.
    Intern Med J, 2012 Feb;42(2):176-83.
    PMID: 21309995 DOI: 10.1111/j.1445-5994.2011.02450.x
    BACKGROUND:
    FDG-PET/CT is widely used in the management of a variety of malignancies with excellent overall accuracy, despite the potential for false positive results related to infection and inflammation.

    AIM:
      As cancer patients can develop clinically inapparent infections, we evaluated the prevalence and nature of incidental findings reported to be suggestive of infections that had been identified during clinical cancer staging with FDG-PET/CT.

    METHODS:
    The study involved a retrospective analysis of 60 patients managed primarily at our facility from a total of 121 cases identified as having possible infection on clinical reporting of more than 4500 cancer staging investigations performed during the calendar year of 2008.

    RESULTS:
    Occult infections were uncommon overall (≤1%), but most often because of pneumonia (31.6%), upper respiratory tract infections (21.1%) or wound infections (15.8%). Abnormal scans contributed to patients' management in 52.7% of cases. Two out of 13 patients whose scan abnormalities were not investigated further had worsening changes on repeated scan and one of these patients had clinical deterioration.

    CONCLUSIONS:
    In patients with FDG-PET/CT scans suggestive of infection and in whom a final diagnosis could be reached, the positive predictive value for FDG-PET/CT scans was 89% suggesting that abnormal scans indicative of infection should be investigated further in this population.
    Matched MeSH terms: Multimodal Imaging/methods*
  8. Yokoe M, Hata J, Takada T, Strasberg SM, Asbun HJ, Wakabayashi G, et al.
    J Hepatobiliary Pancreat Sci, 2018 Jan;25(1):41-54.
    PMID: 29032636 DOI: 10.1002/jhbp.515
    The Tokyo Guidelines 2013 (TG13) for acute cholangitis and cholecystitis were globally disseminated and various clinical studies about the management of acute cholecystitis were reported by many researchers and clinicians from all over the world. The 1st edition of the Tokyo Guidelines 2007 (TG07) was revised in 2013. According to that revision, the TG13 diagnostic criteria of acute cholecystitis provided better specificity and higher diagnostic accuracy. Thorough our literature search about diagnostic criteria for acute cholecystitis, new and strong evidence that had been released from 2013 to 2017 was not found with serious and important issues about using TG13 diagnostic criteria of acute cholecystitis. On the other hand, the TG13 severity grading for acute cholecystitis has been validated in numerous studies. As a result of these reviews, the TG13 severity grading for acute cholecystitis was significantly associated with parameters including 30-day overall mortality, length of hospital stay, conversion rates to open surgery, and medical costs. In terms of severity assessment, breakthrough and intensive literature for revising severity grading was not reported. Consequently, TG13 diagnostic criteria and severity grading were judged from numerous validation studies as useful indicators in clinical practice and adopted as TG18/TG13 diagnostic criteria and severity grading of acute cholecystitis without any modification. Free full articles and mobile app of TG18 are available at: http://www.jshbps.jp/modules/en/index.php?content_id=47. Related clinical questions and references are also included.
    Matched MeSH terms: Multimodal Imaging/methods*
  9. Woolley AK, Hedger NA, Veettil RP
    Acute Med, 2013;12(2):107-10.
    PMID: 23732136
    Pyrexia of unknown origin (PUO) is a frequent presentation to the Acute Medical Unit, and is a source of significant morbidity, both the psychological burden of an uncertain diagnosis and prognosis and untreated complications of the underlying pathology. We present a problem based review of the management of PUO, illustrated by a patient who recently presented to our unit with fever and systemic malaise after returning from abroad and in whom no cause could be found for more than two months. We describe a structured approach making use of complex modern techniques such as Positron Emission Tomography-Computed Tomography (PET-CT) which ultimately provided the diagnosis for our patient.
    Matched MeSH terms: Multimodal Imaging/methods
  10. Tenekecioglu E, Serruys PW, Onuma Y, Costa R, Chamié D, Sotomi Y, et al.
    JACC Cardiovasc Interv, 2017 06 12;10(11):1115-1130.
    PMID: 28527768 DOI: 10.1016/j.jcin.2017.03.015
    OBJECTIVES: The primary objective of this study was to evaluate the safety and effectiveness of the Mirage (Manli Cardiology, Singapore) bioresorbable microfiber sirolimus-eluting scaffold compared with the Absorb (Abbott Vascular, Santa Clara, California) bioresorbable vascular scaffold in the treatment of stenotic target lesions located in native coronary arteries, ranging from ≥2.25 to ≤4.0 mm in diameter. Secondary objectives were to establish the medium-term safety, effectiveness, and performance of the Mirage device.

    BACKGROUND: The current generation of bioresorbable scaffolds has several limitations, such as thick square struts with large footprints that preclude their deep embedment into the vessel wall, resulting in protrusion into the lumen with microdisturbance of flow. The Mirage sirolimus-eluting bioresorbable microfiber scaffold is designed to address these concerns.

    METHODS: In this prospective, single-blind trial, 60 patients were randomly allocated in a 1:1 ratio to treatment with a Mirage sirolimus-eluting bioresorbable microfiber scaffold or an Absorb bioresorbable vascular scaffold. The clinical endpoints were assessed at 30 days and at 6 and 12 months. In-device angiographic late loss at 12 months was quantified. Secondary optical coherence tomographic endpoints were assessed post-scaffold implantation at 6 and 12 months.

    RESULTS: Median angiographic post-procedural in-scaffold minimal luminal diameters of the Mirage and Absorb devices were 2.38 mm (interquartile range [IQR]: 2.06 to 2.62 mm) and 2.55 mm (IQR: 2.26 to 2.71 mm), respectively; the effect size (d) was -0.29. At 12 months, median angiographic in-scaffold minimal luminal diameters of the Mirage and Absorb devices were not statistically different (1.90 mm [IQR: 1.57 to 2.31 mm] vs. 2.29 mm [IQR: 1.74 to 2.51 mm], d = -0.36). At 12-month follow-up, median in-scaffold late luminal loss with the Mirage and Absorb devices was 0.37 mm (IQR: 0.08 to 0.72 mm) and 0.23 mm (IQR: 0.15 to 0.37 mm), respectively (d = 0.20). On optical coherence tomography, post-procedural diameter stenosis with the Mirage was 11.2 ± 7.1%, which increased to 27.4 ± 12.4% at 6 months and remained stable (31.8 ± 12.9%) at 1 year, whereas the post-procedural optical coherence tomographic diameter stenosis with the Absorb was 8.4 ± 6.6%, which increased to 16.6 ± 8.9% and remained stable (21.2 ± 9.9%) at 1-year follow-up (Mirage vs. Absorb: dpost-procedure = 0.41, d6 months = 1.00, d12 months = 0.92). Angiographic median in-scaffold diameter stenosis was significantly different between study groups at 12 months (28.6% [IQR: 21.0% to 40.7%] for the Mirage, 18.2% [IQR: 13.1% to 31.6%] for the Absorb, d = 0.39). Device- and patient-oriented composite endpoints were comparable between the 2 study groups.

    CONCLUSIONS: At 12 months, angiographic in-scaffold late loss was not statistically different between the Mirage and Absorb devices, although diameter stenosis on angiography and on optical coherence tomography was significantly higher with the Mirage than with the Absorb. The technique of implantation was suboptimal for both devices, and future trials should incorporate optical coherence tomographic guidance to allow optimal implantation and appropriate assessment of the new technology, considering the novel mechanical properties of the Mirage.

    Matched MeSH terms: Multimodal Imaging/methods*
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