Computed Tomography Effective Dose and Image Quality in Deep Learning Image Reconstruction in Intensive Care Patients Compared to Iterative Algorithms.

Deep learning image reconstruction (DLIR) algorithms employ convolutional neural networks (CNNs) for CT image reconstruction to produce CT images with a very low noise level, even at a low radiation dose. The aim of this study was to assess whether the DLIR algorithm reduces the CT effective dose (ED) and improves CT image quality in comparison with filtered back projection (FBP) and iterative reconstruction (IR) algorithms in intensive care unit (ICU) patients. We identified all consecutive patients referred to the ICU of a single hospital who underwent at least two consecutive chest and/or abdominal contrast-enhanced CT scans within a time period of 30 days using DLIR and subsequently the FBP or IR algorithm (Advanced Modeled Iterative Reconstruction [ADMIRE] model-based algorithm or Adaptive Iterative Dose Reduction 3D [AIDR 3D] hybrid algorithm) for CT image reconstruction. The radiation ED, noise level, and signal-to-noise ratio (SNR) were compared between the different CT scanners. The non-parametric Wilcoxon test was used for statistical comparison. Statistical significance was set at p < 0.05. A total of 83 patients (mean age, 59 ± 15 years [standard deviation]; 56 men) were included. DLIR vs. FBP reduced the ED (18.45 ± 13.16 mSv vs. 22.06 ± 9.55 mSv, p < 0.05), while DLIR vs. FBP and vs. ADMIRE and AIDR 3D IR algorithms reduced image noise (8.45 ± 3.24 vs. 14.85 ± 2.73 vs. 14.77 ± 32.77 and 11.17 ± 32.77, p < 0.05) and increased the SNR (11.53 ± 9.28 vs. 3.99 ± 1.23 vs. 5.84 ± 2.74 and 3.58 ± 2.74, p < 0.05). CT scanners employing DLIR improved the SNR compared to CT scanners using FBP or IR algorithms in ICU patients despite maintaining a reduced ED.

Potential Benefits of Photon-Counting CT in Dental Imaging: A Narrative Review.

Background/Objectives: Advancements in oral imaging technology are continually shaping the landscape of dental diagnosis and treatment planning. Among these, photon-counting computed tomography (PCCT), introduced in 2021, has emerged as a promising, high-quality oral technology. Dental imaging typically requires a resolution beyond the standard CT systems achievable with the specialized cone-beam CT. PCCT can offer up to 100 µm resolution, improve soft-tissue contrast, and provide faster scanning times, which are crucial for detailed dental diagnosis and treatment planning. Using semiconductor detectors, PCCT produces sharper images and can potentially reduce the number of scans required, thereby decreasing patient radiation exposure. This review aimed to explore the potential benefits of PCCT in dental imaging. Methods: This review analyzed the literature on PCCT in dental imaging from January 2010 to February 2024, sourced from PubMed, Scopus, and Web of Science databases, focusing on high-resolution, patient safety, and diagnostic efficiency in dental structure assessment. We included English-language articles, case studies, letters, observational studies, and randomized controlled trials while excluding duplicates and studies unrelated to PCCT's application in dental imaging. Results: Studies have highlighted the superiority of PCCT in reducing artifacts, which are often problematic, compared to conventional CBCT and traditional CT scans, due to metallic dental implants, particularly when used with virtual monoenergetic imaging and iterative metal artifact reduction, thereby improving implant imaging. This review acknowledges limitations, such as the potential for overlooking other advanced imaging technologies, a narrow study timeframe, the lack of real-world clinical application data in this field, and costs. Conclusions: PCCT represents a promising advancement in dental imaging, offering high-resolution visuals, enhanced contrast, and rapid scanning with reduced radiation exposure.

Radiation Overuse in Intensive Care Units.

Radiological imaging is essential for acute patient management in Intensive Care Units (ICUs); however, it introduces the risk of exposure to ionizing radiation. This review synthesizes research on radiation exposure in ICU settings, highlighting its rise during the COVID-19 pandemic and the rise in repetitive imaging. Our analysis extends to radiation safety thresholds, revealing that some ICU patients exceed the diagnostic reference level, emphasizing the need to balance diagnostic utility against potential long-term risks, such as cancer. Prospective studies have demonstrated an increase in the median cumulative effective dose in patients with trauma over time, prompting calls for improved awareness and monitoring. Moreover, innovative dose-reduction strategies and optimized protocols, especially in neuro-ICUs, promise to mitigate these risks. This review highlights the essential but risky role of radiological imaging in critical care. It advocates for rigorous radiation management protocols to safeguard patient health while ensuring the continuity of high-quality medical care.

Introduction to Special Issue Imaging in Cancer Diagnosis.

In the field of oncology, the precision of cancer imaging is the cornerstone of oncological patient care [...].

New Trends and Advances in MRI and PET Hybrid Imaging in Diagnostics.

Imaging holds an irreplaceable role in routine clinical practice [...].

New Frontiers in Oncological Imaging.

The more that advances in the medical field are capable of targeted treatments, the more imaging should be tailored to patients [...].

Medical Radiology: Current Progress.

Recently, medical radiology has undergone significant improvements in patient management due to advancements in image acquisition by the last generation of machines, data processing, and the integration of artificial intelligence. In this way, cardiovascular imaging is one of the fastest-growing radiological subspecialties. In this study, a compressive review was focused on addressing how and why CT and MR have gained a I class indication in most cardiovascular diseases, and the potential impact of tissue and functional characterization by CT photon counting, quantitative MR mapping, and 4-D flow. Regarding rectal imaging, advances in cancer imaging using diffusion-weighted MRI sequences for identifying residual disease after neoadjuvant chemoradiotherapy and [18F] FDG PET/MRI were provided for high-resolution anatomical and functional data in oncological patients. The results present a large overview of the approach to the imaging of diffuse and focal liver diseases by US elastography, contrast-enhanced US, quantitative MRI, and CT for patient risk stratification. Italy is currently riding the wave of these improvements. The development of large networks will be crucial to create high-quality databases for patient-centered precision medicine using artificial intelligence. Dedicated radiologists with specific training and a close relationship with the referring clinicians will be essential human factors.

Advantages of Photon-Counting Detector CT in Aortic Imaging.

Photon-counting Computed Tomography (PCCT) is a promising imaging technique. Using detectors that count the number and energy of photons in multiple bins, PCCT offers several advantages over conventional CT, including a higher image quality, reduced contrast agent volume, radiation doses, and artifacts. Although PCCT is well established for cardiac imaging in assessing coronary artery disease, its application in aortic imaging remains limited. This review summarizes the available literature and provides an overview of the current use of PCCT for the diagnosis of aortic imaging, focusing mainly on endoleaks detection and characterization after endovascular aneurysm repair (EVAR), contrast dose volume, and radiation exposure reduction, particularly in patients with chronic kidney disease and in those requiring follow-up CT.

Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers.

Background: The purpose of the study was to determine whether contrast-enhanced CT texture features relate to, and can predict, the presence of specific genetic mutations involved in CRC carcinogenesis. Materials and methods: This retrospective study analyzed the pre-operative CT in the venous phase of patients with CRC, who underwent testing for mutations in the KRAS, NRAS, BRAF, and MSI genes. Using a specific software based on CT images of each patient, for each slice including the tumor a region of interest was manually drawn along the margin, obtaining the volume of interest. A total of 56 texture parameters were extracted that were compared between the wild-type gene group and the mutated gene group. A p-value of <0.05 was considered statistically significant. Results: The study included 47 patients with stage III-IV CRC. Statistically significant differences between the MSS group and the MSI group were found in four parameters: GLRLM RLNU (area under the curve (AUC) 0.72, sensitivity (SE) 77.8%, specificity (SP) 65.8%), GLZLM SZHGE (AUC 0.79, SE 88.9%, SP 65.8%), GLZLM GLNU (AUC 0.74, SE 88.9%, SP 60.5%), and GLZLM ZLNU (AUC 0.77, SE 88.9%, SP 65.8%). Conclusions: The findings support the potential role of the CT texture analysis in detecting MSI in CRC based on pre-treatment CT scans.

Predictors of Metastatic Lymph Nodes at Preoperative Staging CT in Gastric Adenocarcinoma.

Background. The aim of this study was to identify the most accurate computed-tomography (CT) dimensional criteria of loco-regional lymph nodes (LNs) for detecting nodal metastases in gastric cancer (GC) patients. Methods. Staging CTs of surgically resected GC were jointly reviewed by two radiologists, considering only loco-regional LNs with a long axis (LA) ≥ 5 mm. For each nodal group, the short axis (SA), volume and SA/LA ratio of the largest LN, the sum of the SAs of all LNs, and the mean of the SA/LA ratios were plotted in ROC curves, taking the presence/absence of metastases at histopathology for reference. On a per-patient basis, the sums of the SAs of all LNs, and the sums of the SAs, volumes, and SA/LA ratios of the largest LNs in all nodal groups were also plotted, taking the presence/absence of metastatic LNs in each patient for reference. Results. Four hundred and forty-three nodal groups were harvested during surgery from 107 patients with GC, and 173 (39.1%) were metastatic at histopathology. By nodal group, the sum of the SAs showed the best Area Under the Curve (AUC), with a sensitivity/specificity of 62.4/72.6% using Youden's index with a >8 mm cutoff. In the per-patient analysis, the sum of the SAs of all LNs in the loco-regional nodal groups showed the best AUC with a sensitivity/specificity of 65.6%/83.7%, using Youden's index with a >39 mm cutoff. Conclusion. In patients with GC, the sum of the SAs of all the LNs at staging CT is the best predictor among dimensional LNs criteria of both metastatic invasion of the nodal group and the presence of metastatic LNs.

Tumor Diagnosis and Treatment: Imaging Assessment.

At present, oncologic imaging is crucial for clinical decision-making [...].

Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review.

Adrenal incidentalomas (AIs) are incidentally discovered adrenal neoplasms. Overt endocrine secretion (glucocorticoids, mineralocorticoids, and catecholamines) and malignancy (primary or metastatic disease) are assessed at baseline evaluation. Size, lipid content, and washout characterise benign AIs (respectively, <4 cm, <10 Hounsfield unit, and rapid release); nonetheless, 30% of adrenal lesions are not correctly indicated. Recently, image-based texture analysis from computed tomography (CT) may be useful to assess the behaviour of indeterminate adrenal lesions. We performed a systematic review to provide the state-of-the-art of texture analysis in patients with AI. We considered 9 papers (from 70 selected), with a median of 125 patients (range 20-356). Histological confirmation was the most used criteria to differentiate benign from the malignant adrenal mass. Unenhanced or contrast-enhanced data were available in all papers; TexRAD and PyRadiomics were the most used software. Four papers analysed the whole volume, and five considered a region of interest. Different texture features were reported, considering first- and second-order statistics. The pooled median area under the ROC curve in all studies was 0.85, depicting a high diagnostic accuracy, up to 93% in differentiating adrenal adenoma from adrenocortical carcinomas. Despite heterogeneous methodology, texture analysis is a promising diagnostic tool in the first assessment of patients with adrenal lesions.

[18F]FDG PET/MRI in the follow-up of hepatocellular carcinoma after liver transplantation.

BACKGROUND: There is limited evidence regarding the application of [18F] fluorodeoxyglucose (FDG)-PET/MRI in patients with a suspected clinical recurrence, who underwent liver transplantation for hepatocellular carcinoma (HCC). Therefore, we compared the accuracy of PET/MR and standard-of-care (SOC) imaging in these patients. METHODS: We retrospectively reviewed 26 patients, whose liver were transplanted for HCC and were suspected of disease relapse based on biochemical analysis or SOC follow-up imaging, and carried out PET/MRI with diffusion-weighted imaging sequences on them. All patients underwent SOC imaging within the 2 months prior to the PET/MRI examination and had follow-up data for at least 12 months after. Reference standards were histopathology, clinical and imaging follow-up data. RESULTS: Sensitivity, specificity, positive predictive value, negative predictive value and accuracy for PET/MRI were 100, 94, 91, 100 and 96%, whereas for SOC imaging were 80, 69, 61, 85 and 73%. The accuracy of PET/MRI was higher with respect to SOC imaging, although not significantly. CONCLUSIONS: PET/MRI is useful for oncological surveillance of patients who have undergone liver transplantation for HCC, particularly in cases of allergy to contrast media, renal failure or persistently elevated alpha-fetoprotein levels, and with no identification of metastatic/relapsing foci at standard-of-care imaging.