Tomography最新文献

Tumor hypoxia is a negative prognostic factor in many tumors and is predictive of metastatic spread and poor responsiveness to both chemotherapy and radiotherapy. Purpose: To assess the feasibility of using ¹⁸F-Fluoroazomycin arabinoside (FAZA) PET/MR to image tumor hypoxia in patients with locally advanced rectal cancer (LARC) prior to and following neoadjuvant chemoradiotherapy (nCRT). The secondary objective was to compare different reference tissues and thresholds for tumor hypoxia quantification. Patients and Methods: Eight patients with histologically proven LARC were included. All patients underwent ¹⁸F-FAZA PET/MR prior to initiation of nCRT, four of whom also had a second scan following completion of nCRT and prior to surgery. Tumors were segmented using T₂-weighted MR. Each voxel within the segmented tumor was defined as hypoxic or oxic using thresholds derived from various references: ×1.0 or ×1.2 SUVmean of blood pool [BP] or left ventricle [LV] and SUVmean +3SD for gluteus maximus. Correlation coefficient (CoC) between HF and tumor SUVmax/reference SUVmean TRR for the various thresholds was calculated. Hypoxic fraction (HF), defined as the % hypoxic voxels within the tumor volume was calculated for each reference/threshold. Results: For all cases, baseline and follow-up, the CoCs for gluteus maximus and for BP and LV (×1.0) were 0.241, 0.344, and 0.499, respectively, and HFs were (median; range) 16.6% (2.4-33.8), 36.8% (0.3-72.9), and 30.7% (0.8-55.5), respectively. For a threshold of ×1.2, the CoCs for BP and LV as references were 0.611 and 0.838, respectively, and HFs were (median; range) 10.4% (0-47.6), and 4.3% (0-20.1%), respectively. The change in HF following nCRT ranged from (-18.9%) to (+54%). Conclusions: Imaging of hypoxia in LARC with ¹⁸F-FAZA PET/MR is feasible. Blood pool as measured in the LV appears to be the most reliable reference for calculating the HF. There is a wide range of HF and variable change in HF before and after nCRT.

Background: Radiation-induced lung injury (RILI), a serious side effect of thoracic radiotherapy, can lead to acute radiation pneumonitis (RP) and chronic pulmonary fibrosis (PF). Despite various interventions, no effective protocol exists to prevent pneumonitis. Oxytocin (OT), known for its anti-inflammatory, antiapoptotic, and antioxidant properties, has not been explored for its potential in mitigating RILI.

Materials and methods: This study involved 24 female Wistar albino rats, divided into three groups: control group, radiation (RAD) + saline, and RAD + OT. The RAD groups received 18 Gy of whole-thorax irradiation. The RAD + OT group was treated with OT (0.1 mg/kg/day) intraperitoneally for 16 weeks. Computerizing tomography (CT) imaging and histopathological, biochemical, and blood gas analyses were performed to assess lung tissue damage and inflammation.

Results: Histopathological examination showed significant reduction in alveolar wall thickening, inflammation, and vascular changes in the RAD + OT group compared to the RAD + saline group. Biochemical analysis revealed decreased levels of TGF-beta, VEGF, and PDGF, and increased BMP-7 and prostacyclin in the RAD + oxytocin group (p < 0.05). Morphometric analysis indicated significant reductions in fibrosis, edema, and immune cell infiltration. CT imaging demonstrated near-normal lung parenchyma density in the RAD + oxytocin group (p < 0.001).

Conclusion: Oxytocin administration significantly mitigates radiation-induced pneumonitis in rats, implying that is has potential as a therapeutic agent for preventing and treating RILI.

Studies addressing the anatomical values of the supraspinatus outlet area (SOA) and the available supraspinatus outlet area (ASOA) are insufficient. This study focused on precisely measuring the SOA and ASOA values in a sample from the Chinese population using 3D CT (computed tomography) reconstruction. We analyzed CT imaging of 96 normal patients (59 males and 37 females) who underwent shoulder examinations in a hospital between 2011 and 2021. The SOA, ASOA, acromiohumeral distance (AHD), coracohumeral distance (CHD), coracoacromial arch radius (CAR), and humeral head radius (HHR) were estimated, and statistical correlation analyses were performed. There were significant sex differences observed in SOA (men: 957.62 ± 158.66 mm²; women: 735.87 ± 95.86 mm²) and ASOA (men: 661.35 ± 104.88 mm²; women: 511.49 ± 69.26 mm²), CHD (men: 11.22 ± 2.24 mm; women: 9.23 ± 1.35 mm), CAR (men: 37.18 ± 2.70 mm; women: 33.04 ± 3.15 mm), and HHR (men: 22.65 ± 1.44 mm; women: 20.53 ± 0.95 mm). Additionally, both SOA and ASOA showed positive and linear correlations with AHD, CHD, CAR, and HHR (R: 0.304-0.494, all p < 0.05). This study provides physiologic reference values of SOA and ASOA in the Chinese population, highlighting the sex differences and the correlations with shoulder anatomical parameters.

Background: On 6 February 2023, two major earthquakes occurred in Turkey on the same day. More than 50,000 people died, and more than 100,000 people were injured in these earthquakes. The aim of this study is to contribute to disaster management plans by evaluating the functioning of a radiology department and the imaging examinations performed after this disaster.

Methods: The functioning of the radiology clinic at Malatya Training and Research Hospital in the first 24 h after the earthquake was evaluated. The images of 596 patients who were admitted to Malatya Training and Research Hospital for earthquake-related trauma between 6 February 2023, at 4:17 a.m. and 7 February 2023, at 4:17 a.m., and who underwent radiography and computed tomography (CT) were retrospectively reviewed.

Results: The mean age of the patients was 37.3 ± 20.1 years. A total of 313 (52.5%) patients were male. The most frequently performed imaging test was a CT scan. In total, 437 (73.3%) of 596 patients underwent a CT scan. At least one body part was affected in 160 patients (26.8%). The most commonly affected regions were the thorax, vertebrae, and extremities. Thoracic findings were observed in 52 patients (32.5%), vertebral findings in 52 patients (32.5%), and extremity findings in 46 patients (28.7%). Fractures were the most common finding in our study. Of the 160 patients with pathologic findings, 139 (86.9%) had evidence of fractures.

Conclusions: The role of radiology in disasters is important. When disaster preparedness plans are made, radiology departments should be actively involved in these plans. This will ensure the quick and efficient functioning of radiology departments.

Background: Distinguishing between Charcot Neuroarthropathy (CN), osteomyelitis (OM), and CN complicated with superimposed OM in diabetic patients is crucial for the treatment choice. Given that current diagnostic methods lack specificity, advanced techniques, e.g., magnetic resonance imaging (MRI) and 99mTc-HMPAO-WBC Single Photon Emission Computed Tomography (SPECT/CT), are needed. This study addresses the challenges in distinguishing OM and CN.

Methods: We included diabetic patients with CN and soft tissue ulceration. MRI and 99mTc-HMPAO-WBC SPECT/CT were used for the diagnosis. The patients were classified into three probability levels for OM (i.e., Definite, Probable, and Unlikely) according to the Consensus Criteria for Diabetic Foot Osteomyelitis (CC-DFO).

Results: Eight patients met the eligibility criteria. MRI, supported by SPECT-CT and CC-DFO, showed consistency with the OM diagnosis in three cases. The key diagnostic features included the location of signal abnormalities and secondary features such as skin ulcers, sinus tracts, and abscesses. Notably, cases with inconclusive MRI were clarified by SPECT/CT, emphasizing its efficacy in challenging scenarios.

Conclusions: The primary objective of this study was to compare the results of MRI and 99mTc-HMPAO-WBC SPECT/CT with the CC-DFO score in the diabetic foot with CN and suspected OM. Advanced imaging offers a complementary approach to distinguish between CN and OM. This can help delineate the limits of the disease for presurgical planning. While MRI is valuable, 99mTc-HMPAO-WBC SPECT/CT provides additional clarity, especially in challenging cases or when metallic implants affect MRI accuracy.

Objective: This study aimed to retrospectively assess the benefits of combining low-dose computed tomography (LDCT) with ventilation/perfusion single-photon emission computed tomography (V/Q SPECT) for the diagnosis of pulmonary embolism (PE).

Methods: A retrospective analysis was performed on 92 patients with suspected PE who underwent V/Q SPECT with ldCT (V/Q SPECT CT) between January 2020 and December 2022 at King Khalid Hospital Najran. Data were collected using the hospital's picture archiving and communication system. Scans were categorized on the basis of perfusion defects, matched or mismatched ventilation, and CT findings. The specificity of V/Q SPECT CT was compared with that of Q SPECT CT.

Results: This study included 92 patients (54 females and 38 males; median age, 53 years). The results demonstrated that V/Q SPECT CT had higher specificity (93%) than V/Q SPECT alone (88%). If CT had been used as a ventilation substitute, 21% of patients would have been reported to be positive for PE (8% false-positive), yielding a specificity of 60% for Q SPECT CT. These findings align with the existing literature, although discrepancies in specificity values were noted due to the different study designs and sample sizes.

Conclusion: This study highlights the enhanced specificity of V/Q SPECT CT compared to V/Q SPECT and Q SPECT CT alone. Including low-dose CT improves diagnostic accuracy by reducing false positives and providing detailed anatomical information. V/Q SPECT CT offers superior specificity in diagnosing PE compared with V/Q SPECT alone, supporting its use in clinical practice.

Background: The usefulness of monitoring treatment effect of tafamidis using magnetic resonance imaging (MRI) extracellular volume fraction (ECV) has been reported.

Objective: we conducted a meta-analysis to evaluate the usefulness of this method.

Methods: Data from 246 ATTR-CMs from six studies were extracted and included in the analysis. An inverse variance meta-analysis using a random effects model was performed to evaluate the change in MRI-ECV before and after tafamidis treatment. The analysis was also performed by classifying the patients into ATTR-CM types (wild-type or hereditary).

Results: ECV change before and after tafamidis treatment was 0.33% (95% CI: -1.83-2.49, I² = 0%, p = 0.76 for heterogeneity) in the treatment group and 4.23% (95% CI: 0.44-8.02, I² = 0%, p = 0.18 for heterogeneity) in the non-treatment group. The change in ECV before and after treatment was not significant in the treated group (p = 0.76), but there was a significant increase in the non-treated group (p = 0.03). There was no difference in the change in ECV between wild-type (95% CI: -2.65-3.40) and hereditary-type (95% CI: -9.28-4.28) (p = 0.45).

Conclusions: The results of this meta-analysis suggest that MRI-ECV measurement is a useful imaging method for noninvasively evaluating the efficacy of tafamidis treatment for ATTR-CM.

The retinacula of the ankle are specialized anatomical structures characterized by localized thickenings of the crural fascia that envelop the deep components of the lower leg, ankle and foot. The ankle retinacula include the extensor retinacula, the peroneal retinacula and flexor retinaculum. Despite their potential to explain persistent and unexplained pain following an injury, these structures are often overlooked or incorrectly diagnosed. Hence, this comprehensive review was performed aiming to investigate the use and the methodology of US imaging to assess ankle retinacula. The search was performed on PubMed and Web of Science databases from inception to May 2024. The MeSH keywords used were as follows: "Ankle Retinacula", "Foot Retinacula", "Superior extensor retinaculum", "Inferior extensor retinaculum", "peroneal retinaculum", "superior peroneal retinaculum", "inferior peroneal retinaculum", "flexor retinaculum", "Ultrasound Imaging", "Ultrasound", "Ultrasonography" and "Ultrasound examination". In total, 257 records underwent screening, resulting in 22 studies meeting the criteria for inclusion after the process of revision. Data heterogeneity prevents synthesis and consistent conclusions. The results showed that advanced US imaging holds promise as a crucial tool to perform an US examination of ankle retinacula, offering static and dynamic insights into ankle retinacula pathology. Understanding normal anatomy and US imaging is essential for accurately identifying injuries. Future research should focus on clinical trials to validate parameters and ensure their reliability in clinical practice.

Anterior cruciate ligament (ACL) tears are prevalent knee injures, particularly among active individuals. Accurate and timely diagnosis is essential for determining the optimal treatment strategy and assessing patient prognosis. Various previous studies have demonstrated the successful application of deep learning techniques in the field of medical image analysis. This study aimed to develop a deep learning model for detecting ACL tears in knee magnetic resonance Imaging (MRI) to enhance diagnostic accuracy and efficiency. The proposed model consists of three main modules: a Dual-Scale Data Augmentation module (DDA) to enrich the training data on both the spatial and layer scales; a selective group attention module (SG) to capture relationships across the layer, channel, and space scales; and a fusion module to explore the inter-relationships among various perspectives to achieve the final classification. To ensure a fair comparison, the study utilized a public dataset from MRNet, comprising knee MRI scans from 1250 exams, with a focus on three distinct views: axial, coronal, and sagittal. The experimental results demonstrate the superior performance of the proposed model, termed SGNET, in ACL tear detection compared with other comparison models, achieving an accuracy of 0.9250, a sensitivity of 0.9259, a specificity of 0.9242, and an AUC of 0.9747.

The concept of 'brain age', derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transformed the field, providing advanced models for brain age estimation. However, achieving precise brain age prediction across all ages remains a significant analytical challenge. This comprehensive review scrutinizes advancements in ML- and DL-based brain age prediction, analyzing 52 peer-reviewed studies from 2020 to 2024. It assesses various model architectures, highlighting their effectiveness and nuances in lifespan brain age studies. By comparing ML and DL, strengths in forecasting and methodological limitations are revealed. Finally, key findings from the reviewed articles are summarized and a number of major issues related to ML/DL-based lifespan brain age prediction are discussed. Through this study, we aim at the synthesis of the current state of brain age prediction, emphasizing both advancements and persistent challenges, guiding future research, technological advancements, and improving early intervention strategies for neurodegenerative diseases.