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In an era of rapid technological progress, this Special Issue aims to provide a comprehensive overview of the state-of-the-art in tomographic imaging [...].

We studied the application of CT texture analysis in adrenal incidentalomas with baseline characteristics of benignity that are highly suggestive of adenoma to find whether there is a correlation between the extracted features and clinical data. Patients with hormonal hypersecretion may require medical attention, even if it does not cause any symptoms. A total of 206 patients affected by adrenal incidentaloma were retrospectively enrolled and divided into non-functioning adrenal adenomas (NFAIs, n = 115) and mild autonomous cortisol secretion (MACS, n = 91). A total of 136 texture parameters were extracted in the unenhanced phase for each volume of interest (VOI). Random Forest was used in the training and validation cohorts to test the accuracy of CT textural features and cortisol-related comorbidities in identifying MACS patients. Twelve parameters were retained in the Random Forest radiomic model, and in the validation cohort, a high specificity (81%) and positive predictive value (74%) were achieved. Notably, if the clinical data were added to the model, the results did not differ. Radiomic analysis of adrenal incidentalomas, in unenhanced CT scans, could screen with a good specificity those patients who will need a further endocrinological evaluation for mild autonomous cortisol secretion, regardless of the clinical information about the cortisol-related comorbidities.

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.

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.

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.

Background: The E-MIOT (Extension-Myocardial Iron Overload in Thalassemia) project is an Italian Network assuring high-quality quantification of tissue iron overload by magnetic resonance imaging (MRI). We evaluated the impact of the COVID-19 pandemic on E-MIOT services., Methods: The activity of the E-MIOT Network MRI centers in the year 2020 was compared with that of 2019. A survey evaluated whether the availability of MRI slots for patients with hemoglobinopathies was reduced and why., Results: The total number of MRI scans was 656 in 2019 and 350 in 2020, with an overall decline of 46.4% (first MRI: 71.7%, follow-up MRI: 36.9%), a marked decline (86.9%) in the period March-June 2020, and a reduction in the gap between the two years in the period July-September. A new drop (41.4%) was recorded in the period October-December for two centers, due to the general reduction in the total amount of MRIs/day for sanitization procedures. In some centers, patients refused MRI scans for fear of getting COVID. Drops in the MRI services >80% were found for patients coming from a region without an active MRI site., Conclusions: The COVID-19 pandemic had a strong negative impact on MRI multi-organ iron quantification, with a worsening in the management of patients with hemoglobinopathies.

Radiomics is a promising research field that combines big data analysis (from tissue texture analysis) with clinical questions. We studied the application of CT texture analysis in adrenal pheochromocytomas (PCCs) to define the correlation between the extracted features and the secretory pattern, the histopathological data, and the natural history of the disease. A total of 17 patients affected by surgically removed PCCs were retrospectively enrolled. Before surgery, all patients underwent contrast-enhanced CT and complete endocrine evaluation (catecholamine secretion and genetic evaluation). The pheochromocytoma adrenal gland scaled score (PASS) was determined upon histopathological examination. After a resampling of all CT images, the PCCs were delineated using LifeX software in all three phases (unenhanced, arterial, and venous), and 58 texture parameters were extracted for each volume of interest. Using the Mann-Whitney test, the correlations between the hormonal hypersecretion, the malignancy score of the lesion (PASS > 4), and texture parameters were studied. The parameters DISCRETIZED&#95;HUpeak and GLZLM&#95;GLNU in the unenhanced phase and GLZLM&#95;SZE, CONVENTIONAL&#95;HUmean, CONVENTIONAL&#95;HUQ3, DISCRETIZED&#95;HUmean, DISCRETIZED&#95;AUC&#95;CSH, GLRLM&#95;HGRE, and GLZLM&#95;SZHGE in the venous phase were able to differentiate secreting PCCs ( p < 0.01), and the parameters GLZLM&#95;GLNU in the unenhanced phase and GLRLM&#95;GLNU and GLRLM&#95;RLNU in the venous differentiated tumors with low and high PASS. CT texture analysis of adrenal PCCs can be a useful tool for the early identification of secreting or malignant tumors.

Ultrasonic contrast agents are used routinely to aid clinical diagnosis. All premium- and mid-range scanners utilise contrast-specific imaging techniques to preferentially isolate and display the nonlinear signals generated from the microbubbles when insonated with a series of ultrasound pulses. In this manuscript the abilities of four premium ultrasound scanners to detect and display the ultrasound signal from two commercially available contrast agents-SonoVue and DEFINITY ® -are compared. A flow phantom was built using tubes with internal diameters of 1.6 mm and 3.2 mm, suspended at depths of 1, 5 and 8 cm and embedded in tissue-mimicking material. Dilute solutions of SonoVue and DEFINITY ® were pumped through the phantom at 0.25 mL/s and 1.5 mL/s. Four transducers were used to scan the tubes-a GE Logiq E9 (C2-9) curvilinear probe, a Philips iU22 L9-3 linear array probe, an Esaote MyLab Twice linear array LA523 (4-13 MHz) and a Fujifilm VisualSonics Vevo3100 MX250 (15-30 MHz) linear array probe. We defined a new parameter to compare the ability of the ultrasound scanners to display the contrast enhancement. This was defined as the ratio of grey-scale intensity ratio in contrast-specific imaging mode relative to the B-mode intensity from the same region-of-interest within the corresponding B-mode image. The study demonstrated that the flow rates used in this study had no effect on the contrast-specific imaging mode to B-mode (CSIM-BM) ratio for the three clinical scanners studied, with SonoVue demonstrating broadly similar CSIM-BM ratios across all 3 clinical scanners. DEFINITY ® also displayed similar results to SonoVue except when insonated with the Esaote MyLab Twice LA523 transducer, where it demonstrated significantly higher CSIM-BM ratios at superficial depths.

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.

Purpose: To assess the diagnostic accuracy of traditional chest X-ray (CXR) and digital tomosynthesis (DTS) compared to computed tomography (CT) in detecting pulmonary interstitial changes in patients having recovered from severe COVID-19., Materials and Methods: This was a retrospective observational study, and received local ethics committee approval. Patients suspected of having COVID-19 pneumonia upon emergency department admission between 1 March and 31 August 2020, and who underwent CXR followed by DTS and CT, were considered. Inclusion criteria were as follows: (1) patients with previous SARS-CoV-2 infection proven by a positive RT-PCR on nasopharyngeal swabs performed upon admission to the hospital, and with complete clinical recovery; (2) a diagnosis of SARS-CoV-2-related ARDS, according to the Berlin criteria, during hospitalization; (3) no recent history of other lung disease; and (4) complete imaging follow-up by CXR, DTS, and CT for at least 6 months and up to one year. Analysis of DTS images was carried out independently by two radiologists with 16 and 10 years of experience in chest imaging, respectively. The following findings were evaluated: (1) ground-glass opacities (GGOs); (2) air-space consolidations with or without air bronchogram; (3) reticulations; and (4) linear consolidation. Indicators of diagnostic performance of RX and digital tomosynthesis were calculated using CT as a reference. All data were analyzed using R statistical software (version 4.0.2, 2020)., Results: Out of 44 patients initially included, 25 patients (17 M/8 F), with a mean age of 64 years (standard deviation (SD): 12), met the criteria and were included. The overall average numbers of findings confirmed by CT were GGOs in 11 patients, lung consolidations in 8 patients, 7 lung interstitial reticulations, and linear consolidation in 20 patients. DTS showed a significantly higher diagnostic accuracy compared to CXR in recognizing interstitial lung abnormalities-especially GGOs ( p = 0.0412) and linear consolidations ( p = 0.0009). The average dose for chest X-ray was 0.10 mSv (0.07-0.32), for DTS was 1.03 mSv (0.74-2.00), and for CT scan was 3 mSv., Conclusions: According to our results, DTS possesses a high diagnostic accuracy, compared with CXR, in revealing lung fibrotic changes in patients who have recovered from COVID-19 pneumonia.

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.

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.

Infectious and inflammatory pulmonary diseases are a leading cause of morbidity and mortality worldwide. Although infrequently used in this setting, molecular imaging may significantly contribute to their diagnosis using techniques like single photon emission tomography (SPET), positron emission tomography (PET) with computed tomography (CT) or magnetic resonance imaging (MRI) with the support of specific or unspecific radiopharmaceutical agents. 18 F-Fluorodeoxyglucose ( 18 F-FDG), mostly applied in oncological imaging, can also detect cells actively involved in infectious and inflammatory conditions, even if with a low specificity. SPET with nonspecific (e.g., 67 Gallium-citrate ( 67 Ga citrate)) and specific tracers (e.g., white blood cells radiolabeled with 111 Indium-oxine ( 111 In) or 99m Technetium ( 99m Tc)) showed interesting results for many inflammatory lung diseases. However, 67 Ga citrate is unfavorable by a radioprotection point of view while radiolabeled white blood cells scan implies complex laboratory settings and labeling procedures. Radiolabeled antibiotics (e.g., ciprofloxacin) have been recently tested, although they seem to be quite unspecific and cause antibiotic resistance. New radiolabeled agents like antimicrobic peptides, binding to bacterial cell membranes, seem very promising. Thus, the aim of this narrative review is to provide a comprehensive overview about techniques, including PET/MRI, and tracers that can guide the clinicians in the appropriate diagnostic pathway of infectious and inflammatory pulmonary diseases.