Extracellular Membrane Vesicles of Escherichia coli Induce Apoptosis of CT26 Colon Carcinoma Cells.

Escherichia coli (E. coli) is commonly utilized as a vehicle for anti-tumor therapy due to its unique tumor-targeting capabilities and ease of engineering modification. To further explore the role of E. coli in tumor treatment, we consider that E. coli outer membrane vesicles (E. coli-OMVs) play a crucial role in the therapeutic process. Firstly, E. coli-OMVs were isolated and partially purified by filtration and ultracentrifugation, and were characterized using techniques such as nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM) and Western Blot (WB). The obtained extracellular nanoparticles, containing OMVs, were found to inhibited the growth of CT26 tumor in mice, while the expression of Bax protein was increased and the expression of Bcl-2 protein decreased. In vitro experiments showed that E. coli-OMVs entered CT26 cells and inhibited cell proliferation, invasion and migration. In addition, in the presence of E. coli-OMVs, we observed an increase in apoptosis rate and a decrease in the ratio of Bcl-2/Bax. These data indicate that E. coli-OMVs inhibits the growth of CT26 colon cancer by inducing apoptosis of CT26 cells. These findings propose E. coli-OMVs as a promising therapeutic drug for colorectal cancer (CRC), providing robust support for further research in related fields.

Application of 99mTc-Labeled WL12 Peptides as a Tumor PD-L1-Targeted SPECT Imaging Agent: Kit Formulation, Preclinical Evaluation, and Study on the Influence of Coligands.

With the development of PD-1/PD-L1 immune checkpoint inhibitor therapy, the ability to monitor PD-L1 expression in the tumor microenvironment is important for guiding therapy. This study was performed to develop a novel radiotracer with optimal pharmacokinetic properties to reflect PD-L1 expression in vivo via single-photon emission computed tomography (SPECT) imaging. [99mTc]Tc-HYNIC-WL12-tricine/M (M = TPPTS, PDA, ISONIC, 4-PSA) complexes with high radiochemical purity (>97%) and suitable molar activity (from 100.5 GBq/µmol to 300 GBq/µmol) were prepared through a kit preparation process. All 99mTc-labeled HYNIC-WL12 radiotracers displayed good in vitro stability for 4 h. The affinity and specificity of the four radiotracers for PD-L1 were demonstrated both in vitro and in vivo. The results of biodistribution studies displayed that the pharmacokinetics of the 99mTc-HYNIC-conjugated radiotracers were significantly influenced by the coligands of the radiotracers. Among them, [99mTc]Tc-HYNIC-WL12-tricine/ISONIC exhibited the optimal pharmacokinetic properties (t1/2α = 8.55 min, t1/2ß = 54.05 min), including the fastest clearance in nontarget tissues, highest tumor-to-background contrast (e.g., tumor-to-muscle ratio, tumor-to-blood ratio: 40.42 ± 1.59, 14.72 ± 2.77 at 4 h p.i., respectively), and the lowest estimated radiation absorbed dose, highlighting its potential as a clinical SPECT imaging probe for tumor PD-L1 detection.

Next-Gen Medical Imaging: U-Net Evolution and the Rise of Transformers.

The advancement of medical imaging has profoundly impacted our understanding of the human body and various diseases. It has led to the continuous refinement of related technologies over many years. Despite these advancements, several challenges persist in the development of medical imaging, including data shortages characterized by low contrast, high noise levels, and limited image resolution. The U-Net architecture has significantly evolved to address these challenges, becoming a staple in medical imaging due to its effective performance and numerous updated versions. However, the emergence of Transformer-based models marks a new era in deep learning for medical imaging. These models and their variants promise substantial progress, necessitating a comparative analysis to comprehend recent advancements. This review begins by exploring the fundamental U-Net architecture and its variants, then examines the limitations encountered during its evolution. It then introduces the Transformer-based self-attention mechanism and investigates how modern models incorporate positional information. The review emphasizes the revolutionary potential of Transformer-based techniques, discusses their limitations, and outlines potential avenues for future research.

ct2vl: A Robust Public Resource for Converting SARS-CoV-2 Ct Values to Viral Loads.

The amount of SARS-CoV-2 in a sample is often measured using Ct values. However, the same Ct value may correspond to different viral loads on different platforms and assays, making them difficult to compare from study to study. To address this problem, we developed ct2vl, a Python package that converts Ct values to viral loads for any RT-qPCR assay/platform. The method is novel in that it is based on determining the maximum PCR replication efficiency, as opposed to fitting a sigmoid (S-shaped) curve relating signal to cycle number. We calibrated ct2vl on two FDA-approved platforms and validated its performance using reference-standard material, including sensitivity analysis. We found that ct2vl-predicted viral loads were highly accurate across five orders of magnitude, with 1.6-fold median error (for comparison, viral loads in clinical samples vary over 10 orders of magnitude). The package has 100% test coverage. We describe installation and usage both from the Unix command-line and from interactive Python environments. ct2vl is freely available via the Python Package Index (PyPI). It facilitates conversion of Ct values to viral loads for clinical investigators, basic researchers, and test developers for any RT-qPCR platform. It thus facilitates comparison among the many quantitative studies of SARS-CoV-2 by helping render observations in a natural, universal unit of measure.

Development of Acceptable Quality Dose (AQD) and image quality-related diagnostic reference levels for common computed tomography investigations in a tertiary care public sector hospital of Khyber Pakhtunkhwa, Pakistan.

PURPOSE: To describe the first experience of patient dose optimization in developing AQD, SSDE and image quality-related DRLs for common CT examinations in the adult age group using the concept of AQD. MATERIALS AND METHODS: The recent published IQSC from 0 to 4 were used by radiologists for the assessment of image quality. The entire data were collected for five types (brain CT, chest CT, chest HRCT, abdomen KUB CT and abdomen + pelvic CT) CT investigations based on anatomic region (head, chest and abdomen + pelvic). The entire datasets of 264 patients were categorized into three groups based on their weights: group-1 (41-60 kg), group-2 (61-80 kg) and group-3 (81-100 kg). Only score-3 images were considered to assess median and 75th percentile values of CTDIvol and DLP to obtain AQDs and DRLs, respectively. RESULTS: Following the practical training of four radiologists on image quality scoring criteria for CT images, 264 (92%) out of 288 patient images were clinically acceptable as per IQSC for the study. The AQD (median) values in terms of CTDIvol for the mentioned weight groups were 25.8, 2.7, and 30.6 mGy, while the median DLP values for these groups were 496, 510 and 557 mGycm, respectively, for brain CT. The 75th percentile values in terms of CTDIvol were 30.2, 35.3 and 36.2 mGy, while in terms of DLP, they were 583, 619 and 781 mGycm for brain CT, respectively. Similar results are presented for the above-mentioned procedures, as well as in terms of SSDE. CONCLUSION: The first ever experience in obtaining AQD, SSDE and DRLs values for specific CT procedures couples image quality with dose indices, showing comparable values with other relevant studies. Hence, it will provide a baseline for comparison within the facility for future studies and facilitate dose optimization for other facilities aiming for improvement.

Preclinical characterization of endotoxin-induced uveitis models using OCT, PET/CT and proteomics.

Uveitis is a group of inflammatory ocular pathologies. Endotoxin-Induced Uveitis (EIU) model represent a well-known model induced by administration of Lipopolysaccharide (LPS). The aim is to characterize two models of EIU through two routes of administration with novel noninvasive imaging techniques. 29 rats underwent Intraocular Pressure (IOP) measurements, Optical Coherence Tomography (OCT), proteomic analysis, and Positron Emission Tomography and Computed Tomography (PET/CT). Groups included healthy controls (C), BSS administered controls (Ci), systemically induced EIU with LPS (LPSs), and intravitreally induced EIU with LPS (LPSi) for IOP, OCT, and proteomic studies. For 18F-FDG PET/CT study, animals were divided into FDG-C, FDG-LPSs and FDG-LPSi groups and scanned using a preclinical PET/CT system. LPSi animals exhibited higher IOP post-induction compared to C and LPSs groups. LPSi showed increased cellular infiltrate, fibrotic membranes, and iris inflammation. Proinflammatory proteins were more expressed in EIU models, especially LPSi. PET/CT indicated higher eye uptake in induced models compared to FDG-C. FDG-LPSi showed higher eye uptake than FDG-LPSs but systemic uptake was higher in FDG-LPSs due to generalized inflammation. OCT is valuable for anterior segment assessment in experimental models. 18F-FDG PET/CT shows promise as a noninvasive biomarker for ocular inflammatory diseases. Intravitreal induction leads to higher ocular inflammation. These findings offer insights for future inflammatory disease research and drug studies.

Giant Aortic Arch Aneurysm Presenting as Ortner's Syndrome in Polycystic Kidney Disease: A Radiological Perspective.

Polycystic kidney disease (PKD) is a genetic disease characterized by the formation of multiple cysts in bilateral kidneys. While renal complications are predominant, cardiovascular manifestations such as aortic aneurysms can also occur. Although there are a few case reports of giant aortic arch aneurysms, to the best of our knowledge, this has been rarely reported in patients with PKD. Additionally, the clinical presentation of the index case is unique.

Clinical and imaging features of pulmonary mixed squamous cell and glandular papilloma: a case report and literature review.

Pulmonary mixed squamous cell and glandular papilloma (MSGP) is a rare benign lung tumor with both squamous and glandular epithelial components. Reports on primary lung MSGP are few, and the aim of this study is to describe the imaging, including computed tomography (CT) and positron emission tomography (PET) findings, and histopathological characteristics of a case of MSGP in our hospital. A 53-year-old woman with no smoking history who underwent a chest CT scan revealed a nodule in the upper lobe of the left lung. The solid nodule showed no lobulation or spiculation but demonstrated significant enhancement on contrast-enhanced CT and increased fluorine-18 fluorodeoxyglucose (18F-FDG) uptake on PET. Moreover, a literature review identified 19 cases of lung MSGPs involving imaging findings, including CT and/or PET imaging. Except for one patient with a ground glass nodule, the rest were solid and ranged in size from 0.7 to 8.2 cm, which can present as a mildly to significantly increased 18F-FDG uptake on PET. MSGP is a rare benign tumor entity, and understanding its imaging findings and pathological immunohistochemical characteristics will help to improve the accurate diagnosis of MSGP so as to avoid unnecessary lobectomy and mediastinal lymph node dissection.

Value of High-output Pace-mapping of the Right Phrenic Nerve for Enabling Safe Radiofrequency Ablation of Atrial Fibrillation: Insights from Three-dimensional CT Segmentation.

BACKGROUND: Right phrenic nerve (RPN) injury is a disabling but uncommon complication of atrial fibrillation (AF) radiofrequency ablation. Pace-mapping is widely used to infer RPN's course, for limiting the risk of palsy by avoiding ablation at capture sites. However, information is lacking regarding the distance between the endocardial sites of capture and the actual anatomic RPN location. OBJECTIVE: To determine the distance between endocardial sites of capture and anatomic CT location of the RPN, depending on the capture threshold. METHODS: In consecutive patients undergoing AF radiofrequency ablation, we defined the course of the RPN on the electroanatomical map with high-output pacing at up to 50mA/2ms, and assessed RPN capture threshold (RPN-t). The true anatomic course of the RPN was delineated and segmented using CT scan, then merged with the electroanatomical map. The distance between pacing sites and the RPN was assessed. RESULTS: In 45 patients, 1033 pacing sites were analyzed. Distances from pacing sites to RPN ranged from 7.5±3.0mm (min 1) when RPN-t was ≤10mA, to 19.2±6.5mm (min 9.4) in cases of non-capture at 50mA. A distance to the phrenic nerve > 10mm was predicted by RPN-t with a ROC curve area of 0.846 [0.821-0.870] (p<0.001), with Se=80.8% and Sp=77.5% if RPN-t >20mA, Se=68.0% and Sp=91.6% if RPN-t >30mA, and Se=42.4% and Sp=97.6% if non-capture at 50mA. CONCLUSION: This data emphasize the utility of high output pace-mapping of the RPN. Non-capture at 50mA/2ms demonstrated very high specificity for predicting a distance to the RPN >10mm, ensuring safe radiofrequency delivery.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma with extranodal involvement.

PURPOSE: The objective of this investigation is to explore the capability of baseline 18F-FDG PET/CT radiomics to predict the prognosis of diffuse large B-cell lymphoma (DLBCL) with extranodal involvement (ENI). METHODS: 126 patients diagnosed with DLBCL with ENI were included in the cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to refine the optimum subset from the 1328 features. Cox regression analyses were employed to discern significant clinical variables and conventional PET parameters, which were then employed with radiomics score to develop combined model for predicting both progression-free survival (PFS) and overall survival (OS). The fitness and the predictive capability of the models were assessed via the Akaike information criterion (AIC) and concordance index (C-index). RESULTS: 62 patients experienced disease recurrence or progression and 28 patients ultimately died. The combined model exhibited a lower AIC value compared to the radiomics model and SDmax/clinical variables for both PFS (507.101 vs. 510.658 vs. 525.506) and OS (215.667 vs. 230.556 vs. 219.313), respectively. The C-indices of the combined model, radiomics model, and SDmax/clinical variables were 0.724, 0.704, and 0.615 for PFS, and 0.842, 0.744, and 0.792 for OS, respectively. Kaplan--Meier curves showed significantly higher rates of relapse and mortality among patients classified as high-risk compared to those classified as low-risk (all P < 0.05). CONCLUSIONS: The combined model of clinical variables, conventional PET parameters, and baseline PET/CT radiomics features demonstrates a higher accuracy in predicting the prognosis of DLBCL with ENI.

Impact of HER2-targeted PET/CT imaging in patients with breast cancer and therapeutic response monitoring.

BACKGROUND: Patients with breast cancer exhibit heterogeneity in the expression of the human epithelial growth factor receptor 2 (HER2). Clinically, re-biopsying recurrent or metastatic lesions presents substantial challenges. This study aimed to evaluate the efficacy of HER2-targeted PET/CT imaging in identifying HER2 expression in breast cancer lesions and monitoring therapeutic responses. PATIENTS AND METHODS: This exploratory analysis used data from a prospective study that included adult patients with breast cancer who underwent both Al18F-NOTA-HER2-BCH and 18F-FDG PET/CT imaging at Beijing Cancer Hospital between June 2020 and July 2023 (NCT04547309). RESULTS: Fifty-nine participants, with a median age of 55 years, were analyzed. Lesions imaged with HER2-targeted PET/CT before anti-HER2 therapy exhibited higher SUVmax values than after therapy in HER2 immunohistochemistry (IHC) 3 + lesions (19.9, 95% CI: 15.7-25.3 vs 9.8, 95% CI: 5.6-14.7; P = .006). A significant positive correlation was observed between SUVmax on HER2-targeted PET/CT and IHC before therapy (P = .034), with higher SUVmax values noted in lesions with positive HER2 pathology compared to those with negative HER2 status (17.9 ±â€…13.2 vs 1.1 ±â€…0.3; P = .007). HER2 expression heterogeneity was confirmed both between primary and metastatic lesions (22.9%) and among different metastatic sites (26.7%) as assessed by HER2-targeted PET/CT. A superior therapeutic response correlated with higher pretreatment SUVmax values. The HER2-targeted PET/CT procedure was well-tolerated by all patients. CONCLUSION: HER2-targeted PET/CT imaging offers a practical, non-invasive, and quantitative approach for assessing HER2 status in breast cancer patients, facilitating the optimization and personalization of therapeutic strategies by oncologists.

Efficacity of CT-guided intra-articular cervical facet steroid injection for cervical radiculopathy.

Background: Traditionally, transforaminal steroid injection is performed in the management of cervical radiculopathy in medical failure treatment but carried a true risk of catastrophic complication. Another approach currently used is to perform intra-articular facet steroid injection to reach the epidural space. Purpose: The aim of this study was to describe the evolution of symptoms following intra-articular facet steroid injection in cervical radiculopathy. Material and methods: We conducted a retrospective study. We assessed all patients who had a CT-guided intra-articular facet steroid injection in our center (xx, xx, xx) from December 2015 to February 2021. Cervical MR pretherapeutic images were analyzed and classified according to cervical pain etiology: uncodiscarthrosis, disk herniation or congestive cervical posterior osteo-arthritis. All patients had clinical initial evaluation and then follow-up at 1 and 6 months. Pain severity was rated on a visual analog scale and expressed as a percentage of improvement. Results: Ninety-three patients were included. There were 56 patients with uncodiscarthrosis, 29 with a disk herniation and 8 with a cervical posterior congestive osteoarthritis. A significant improvement of the visual analog scale percentage was found for all patient at 1 and 6 months (p < 0.01). Visual analog scale percentage improvement was about 50 % for all etiologies. For all patients, no severe complications were reported. Conclusion: Intra-articular facet steroid injection may be considered for the treatment of cervical radiculopathy when other medical treatments have failed.

Comparison of Cardiac Activated Fibroblast Imaging and Magnetic Resonance Imaging in Patients with COVID-19-Related Myocarditis.

Background: This study aimed to explore the association between cardiac fibroblast activation and cardiac magnetic resonance (CMR) imaging parameters in patients with myocarditis following infection with coronavirus 2019 (COVID-19). Methods: In this prospective study, four patients with COVID-19-related myocarditis underwent 99mTc-labeled-hydrazinonicotinamide-fibroblast activation protein inhibitor-04 (99mTc-HFAPi) single photon emission computed tomography/computed tomography (SPECT/CT) and CMR imaging. Segmental 99mTc-HFAPi activity was quantified as the percentage of average segmental myocardial count × global left ventricular target-to-background ratio. T1/T2 values, extracellular volume (ECV), and late gadolinium enhancement (LGE) were analyzed by CMR. The consistency between myocardial 99mTc-HFAPi activity and CMR parameters was explored. Results: In patients with myocarditis, the proportion of segments with abnormal 99mTc-HFAPi activity was significantly higher than in those with abnormal LGE (81.25% vs. 60.93%, p = 0.011), abnormal T2 (81.25% vs. 50.00%, p < 0.001), and abnormal ECV (81.25% vs. 59.38%, p = 0.007); however, they were similar in those with abnormal native T1 (81.25% vs. 73.43%, p = 0.291). Meanwhile, 99mTc-HFAPi imaging exhibited good consistency with native T1 (kappa = 0.69). Conclusions: Increased cardiac 99mTc-HFAPi activity is present in COVID-19-related myocarditis, which is correlated with the native T1 values in CMR.

Development of a deep learning model for the automated detection of green pixels indicative of gout on dual energy CT scan.

Background: Dual-energy CT (DECT) is a non-invasive way to determine the presence of monosodium urate (MSU) crystals in the workup of gout. Color-coding distinguishes MSU from calcium following material decomposition and post-processing. Most software labels MSU as green and calcium as blue. There are limitations in the current image processing methods of segmenting green-encoded pixels. Additionally, identifying green foci is tedious, and automated detection would improve workflow. This study aimed to determine the optimal deep learning (DL) algorithm for segmenting green-encoded pixels of MSU crystals on DECTs. Methods: DECT images of positive and negative gout cases were retrospectively collected. The dataset was split into train (N = 28) and held-out test (N = 30) sets. To perform cross-validation, the train set was split into seven folds. The images were presented to two musculoskeletal radiologists, who independently identified green-encoded voxels. Two 3D Unet-based DL models, Segresnet and SwinUNETR, were trained, and the Dice similarity coefficient (DSC), sensitivity, and specificity were reported as the segmentation metrics. Results: Segresnet showed superior performance, achieving a DSC of 0.9999 for the background pixels, 0.7868 for the green pixels, and an average DSC of 0.8934 for both types of pixels, respectively. According to the post-processed results, the Segresnet reached voxel-level sensitivity and specificity of 98.72 % and 99.98 %, respectively. Conclusion: In this study, we compared two DL-based segmentation approaches for detecting MSU deposits in a DECT dataset. The Segresnet resulted in superior performance metrics. The developed algorithm provides a potential fast, consistent, highly sensitive and specific computer-aided diagnosis tool. Ultimately, such an algorithm could be used by radiologists to streamline DECT workflow and improve accuracy in the detection of gout.

A case report of a retrosplenic colonic interposition: Preoperative computed tomography is essential for safe colonic resection.

Retrosplenic colonic interposition is a rare anatomical variant which involves an aberrant positioning of the colon between the spleen and the left hemidiaphragm. Cross-sectional imaging, particularly preoperative computed tomography, plays a critical role in identifying this variant. Recognition of a retrosplenic colonic interposition is essential in certain surgical procedures for ensuring appropriate management tailored to individual patient anatomy and minimizing complications. To our knowledge, this is the first case report describing retrosplenic colonic interposition during colonic resection.

Urgent Direct Access to Diagnostic Services for General Practitioners: Bridging the Gap in Cancer Diagnosis.

Urgent direct access to diagnostic services for general practitioners (GPs) is a new pathway to capture any cancer diagnoses that may have been missed due to vague symptom presentations. Hence, GPs should look out for the key symptoms mentioned by NHS England that should prompt urgent direct access referrals for chest X-ray (CXR), computed tomography (CT) chest, MRI brain, ultrasound (US) abdomen and pelvis, and CT abdomen and pelvis. By implementing this approach, we can significantly reduce the time to diagnosis, while minimizing the number of visits to GP and specialist appointments prior to initiating investigations. However, the use of this pathway can only improve if access to diagnostic scans is improved. This needs to be done by ensuring all GPs in the country have access to directly request MRI brains, CT chest, abdomen, and pelvis. Further research into the impact of the urgent direct access pathway as well as investigating the number of GPs without access to these vital diagnostic services is required to fully improve and measure the progress of this referral pathway.

Risk factors for nonidiopathic and idiopathic facial nerve palsies: findings of a retrospective study.

BACKGROUND: Idiopathic (IF) and nonidiopathic facial (NIF) nerve palsies are the most common forms of peripheral facial nerve palsies. Various risk factors for IF palsies, such as weather, have been explored, but such associations are sparse for NIF palsies, and it remains unclear whether certain diagnostic procedures, such as contrast agent-enhanced cerebral magnetic resonance imaging (cMRI), are helpful in the differential diagnosis of NIF vs. IF. METHODS: In this retrospective, monocentric study over a five-year period, the medical reports of 343 patients with peripheral facial nerve palsy were analysed based on aetiology, sociodemographic factors, cardiovascular risk factors, consultation time, diagnostic procedures such as cMRI, and laboratory results. We also investigated whether weather conditions and German Google Trends data were associated with the occurrence of NIF. To assess the importance of doctors' clinical opinions, the documented anamneses and clinical examination reports were presented and rated in a blinded fashion by five neurology residents to assess the likelihood of NIF. RESULTS: A total of 254 patients (74%) had IF, and 89 patients (26%) had NIF. The most common aetiology among the NIF patients was the varicella zoster virus (VZV, 45%). Among the factors analysed, efflorescence (odds ratio (OR) 17.3) and rater agreement (OR 5.3) had the highest associations with NIF. The day of consultation (Friday, OR 3.6) and the cMRI findings of contrast enhancement of the facial nerve (OR 2.3) were also risk factors associated with NIF. In contrast, the local weather, Google Trends data, and cardiovascular risk factors were not associated with NIF. CONCLUSION: The findings of this retrospective study highlight the importance of patient history and careful inspections to identify skin lesions for the differential diagnosis of acute facial nerve palsy. Special caution is advised for hospital physicians during the tick season, as a surge in NIF cases can lead to a concomitant increase in IF cases, making it challenging to choose adequate diagnostic methods.

Study on the consistency between CT hounsfield units and MRI evaluation of preoperative cervical paraspinal muscular fat infiltration in patients undergoing ACDF.

OBJECTIVE: To explore the feasibility of applying CT Hounsfield Units (HUs) for the assessment of preoperative paraspinal muscle fat infiltration (FI) in different segments in patients who underwent anterior cervical discectomy and fusion (ACDF). To compare the consistency of preoperative paraspinal muscle FI evaluations using MRI and those via CT HUs in patients who underwent ACDF surgery. METHODS: Ninety-five patients (45 males and 50 females, aged 37‒71 years) who received CT and MRI examinations and underwent ACDF surgery were retrospectively analyzed. In the axial T2-weighted MR images at the median level of the C3/4, C4/5, and C5/6 segments, regions of interests (ROIs) were delineated along the boundaries of the cervical multifidus (MF) and semispinalis cervicis (Scer) muscles. Using the threshold tool in ImageJ software, areas of fat tissue and intermuscular septa within the ROI were quantified. The effective cross-sectional area (ECSA) for each side was obtained by subtracting the areas of fat tissue and intermuscular septa from the total ROI area. The ratio of the fat tissue area to the CSA was then calculated to determine the initial FI value. The depth of subcutaneous fat from the midline spinous process to the epidermis at the median plane of the C4/5 intervertebral disc was measured. The initial FI values were then divided by the depth of fat to determine the post-correction FI value. Using the Picture Archiving and Communication System (PACS), at identical segments and planes, ROIs were delineated using the same method as in MRI under a standard soft tissue window (width of 500 HU, level of 60 HU). The CT HU values were measured within these defined areas. The CT HU values from both sides are summed to obtain the total HU value for the segment. According to whether the measurement results of two sets of data follow a normal distribution, Pearson's test or Sperman's test was used to analyze the correlation. RESULTS: On MRI, a statistically significant difference was observed in the post-correction FI only at the C3/4 segment compared to the other two segments (P < 0.05). No significant difference in the post-correction FI between the C4/5 and C5/6 segments was noted (P > 0.05). The CT HU results showed a substantial discrepancy between C3/4 and C4/5 segments and between C3/4 and C5/6 segments (P < 0.05), whereas no statistically significant difference was found in the CT HU value between the C4/5 and C5/6 segments (P > 0.05). The consistency analysis revealed a relatively strong correlation between the post-correction FI and CT HU values of the C3/4 and C4/5 segments. Furthermore, a strong correlation was detected in the variations in the measurement outcomes at the C5/6 segment. CONCLUSION: Patients requiring surgical treatment for the cervical spine exhibit varying degrees of FI in paraspinal muscles across different locations and segments. Evaluating the degree of FI in the paraspinal muscles of the cervical spine through CT HU values is feasible. There is considerable consistency between the post-correction FI assessed under MRI and the measurements of CT HU values in evaluating the FI of paraspinal muscles in the cervical spine.

18F-Fluorodeoxyglucose Positron Emission Tomography-Based Risk Score Model for Prediction of Five-Year Survival Outcome after Curative Resection of Non-Small-Cell Lung Cancer.

The aim of our retrospective study is to develop and assess an imaging-based model utilizing 18F-FDG PET parameters for predicting the five-year survival in non-small-cell lung cancer (NSCLC) patients after curative surgery. A total of 361 NSCLC patients who underwent curative surgery were assigned to the training set (n = 253) and the test set (n = 108). The LASSO regression model was used to construct a PET-based risk score for predicting five-year survival. A hybrid model that combined the PET-based risk score and clinical variables was developed using multivariate logistic regression analysis. The predictive performance was determined by the area under the curve (AUC). The individual features with the best predictive performances were co-occurrence_contrast (AUC = 0.675) and SUL peak (AUC = 0.671). The PET-based risk score was identified as an independent predictor after adjusting for clinical variables (OR 5.231, 95% CI 1.987-6.932; p = 0.009). The hybrid model, which integrated clinical variables, significantly outperformed the PET-based risk score alone in predictive accuracy (AUC = 0.771 vs. 0.696, p = 0.022), a finding that was consistent in the test set. The PET-based risk score, especially when integrated with clinical variables, demonstrates good predictive ability for five-year survival in NSCLC patients following curative surgery.

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer.

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.