Chest CT opportunistic biomarkers for phenotyping high-risk COVID-19 patients: a retrospective multicentre study.

OBJECTIVE: To assess the value of opportunistic biomarkers derived from chest CT performed at hospital admission of COVID-19 patients for the phenotypization of high-risk patients. METHODS: In this multicentre retrospective study, 1845 consecutive COVID-19 patients with chest CT performed within 72 h from hospital admission were analysed. Clinical and outcome data were collected by each center 30 and 80 days after hospital admission. Patients with unknown outcomes were excluded. Chest CT was analysed in a single core lab and behind pneumonia CT scores were extracted opportunistic data about atherosclerotic profile (calcium score according to Agatston method), liver steatosis (≤ 40 HU), myosteatosis (paraspinal muscle F < 31.3 HU, M < 37.5 HU), and osteoporosis (D12 bone attenuation < 134 HU). Differences according to treatment and outcome were assessed with ANOVA. Prediction models were obtained using multivariate binary logistic regression and their AUCs were compared with the DeLong test. RESULTS: The final cohort included 1669 patients (age 67.5 [58.5-77.4] yo) mainly men 1105/1669, 66.2%) and with reduced oxygen saturation (92% [88-95%]). Pneumonia severity, high Agatston score, myosteatosis, liver steatosis, and osteoporosis derived from CT were more prevalent in patients with more aggressive treatment, access to ICU, and in-hospital death (always p < 0.05). A multivariable model including clinical and CT variables improved the capability to predict non-critical pneumonia compared to a model including only clinical variables (AUC 0.801 vs 0.789; p = 0.0198) to predict patient death (AUC 0.815 vs 0.800; p = 0.001). CONCLUSION: Opportunistic biomarkers derived from chest CT can improve the characterization of COVID-19 high-risk patients. CLINICAL RELEVANCE STATEMENT: In COVID-19 patients, opportunistic biomarkers of cardiometabolic risk extracted from chest CT improve patient risk stratification. KEY POINTS: • In COVID-19 patients, several information about patient comorbidities can be quantitatively extracted from chest CT, resulting associated with the severity of oxygen treatment, access to ICU, and death. • A prediction model based on multiparametric opportunistic biomarkers derived from chest CT resulted superior to a model including only clinical variables in a large cohort of 1669 patients suffering from SARS- CoV2 infection. • Opportunistic biomarkers of cardiometabolic comorbidities derived from chest CT may improve COVID-19 patients' risk stratification also in absence of detailed clinical data and laboratory tests identifying subclinical and previously unknown conditions.

Unsupervised segmentation and quantification of COVID-19 lesions on computed Tomography scans using CycleGAN.

BACKGROUND: Lesion segmentation is a critical step in medical image analysis, and methods to identify pathology without time-intensive manual labeling of data are of utmost importance during a pandemic and in resource-constrained healthcare settings. Here, we describe a method for fully automated segmentation and quantification of pathological COVID-19 lung tissue on chest Computed Tomography (CT) scans without the need for manually segmented training data. METHODS: We trained a cycle-consistent generative adversarial network (CycleGAN) to convert images of COVID-19 scans into their generated healthy equivalents. Subtraction of the generated healthy images from their corresponding original CT scans yielded maps of pathological tissue, without background lung parenchyma, fissures, airways, or vessels. We then used these maps to construct three-dimensional lesion segmentations. Using a validation dataset, Dice scores were computed for our lesion segmentations and other published segmentation networks using ground truth segmentations reviewed by radiologists. RESULTS: The COVID-to-Healthy generator eliminated high Hounsfield unit (HU) voxels within pulmonary lesions and replaced them with lower HU voxels. The generator did not distort normal anatomy such as vessels, airways, or fissures. The generated healthy images had higher gas content (2.45 ± 0.93 vs 3.01 ± 0.84 L, P < 0.001) and lower tissue density (1.27 ± 0.40 vs 0.73 ± 0.29 Kg, P < 0.001) than their corresponding original COVID-19 images, and they were not significantly different from those of the healthy images (P < 0.001). Using the validation dataset, lesion segmentations scored an average Dice score of 55.9, comparable to other weakly supervised networks that do require manual segmentations. CONCLUSION: Our CycleGAN model successfully segmented pulmonary lesions in mild and severe COVID-19 cases. Our model's performance was comparable to other published models; however, our model is unique in its ability to segment lesions without the need for manual segmentations.

Skeletal muscle wasting and long-term prognosis in patients undergoing rectal cancer surgery without neoadjuvant therapy.

BACKGROUND: Derangement of body composition has been associated with dismal long-term survival in several gastrointestinal cancers including rectal tumors treated with neoadjuvant therapies. The role of specific preoperative anthropometric indexes on the oncologic outcomes of patients undergoing upfront surgery for rectal cancer has not been investigated. The aim of the study is to evaluate the association of body composition and overall survival in this specific cohort. METHODS: Lumbar computed tomography images, obtained within the 30 days previous to surgery, between January 2009 and December 2016, were used to calculate population-specific thresholds of muscle mass (sarcopenia), subcutaneous and visceral adiposity, visceral obesity, sarcopenic obesity, and myosteatosis. These body composition variables were related with overall survival (OS), tumor-specific survival (TSS), and disease-free survival (DFS). OS, TSS, and DFS were evaluated by the Kaplan-Meier method. Cox regression analysis was used to identify independent predictors of mortality, tumor-specific mortality, and recurrence, and data were presented as hazard ratio (HR) and 95% confidence interval (CI). RESULTS: During the study period, 411 patients underwent rectal resection for cancer, and among these, 129 were without neoadjuvant chemoradiation. The median follow-up was 96.7 months. At the end of the follow-up, 41 patients (31.8%) had died; of these, 26 (20.1%) died for tumor-related reasons, and 36 (27.1%) experienced disease recurrence. One-, three-, and five-year OS was 95.7%, 86.0%, and 76.8% for non-sarcopenic patients versus 82.4%, 58.8%, and 40.0% for sarcopenic ones respectively (p < 0.001). Kaplan-Meier survival curves comparing sarcopenic and non-sarcopenic patients showed a significant difference in terms of OS (log-rank < 0.0001). Through multivariate Cox regression, overall mortality risk was associated only with sarcopenia (HR 1.96; 95%CI 1.03-3.74; p = 0.041). Disease stage IV and III (HR 13.75; 95% CI 2.89-65.6; p < 0.001 and HR 4.72; 95% CI 1.06-21.1; p = 0.043, respectively) and sarcopenia (HR 2.62; 95% CI 1.22-5.6; p = 0.013) were independently associated with TSS. The other body composition indexes investigated showed no significant association with prognosis. CONCLUSIONS: These results support the inclusion of body composition assessment for prognostic stratification of rectal cancer patients undergoing upfront resection.

AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients.

PURPOSE: To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification. MATERIAL AND METHODS: In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT. The outcome was survival. A rigorous AI model selection framework was adopted for models selection and automatic CT data extraction. Model performances were compared in terms of AUC. A web-mobile interface was developed using Microsoft PowerApps environment. The platform was externally validated on 213 COVID-19 adults prospectively enrolled during wave 2 (October 14-December 31, 2020). RESULTS: The final cohort included 1125 patients (292 non-survivors, 26%) and 24 variables. Logistic showed the best performance on the complete set of variables (AUC = 0.839 ± 0.009) as in models including a limited set of 13 and 5 variables (AUC = 0.840 ± 0.0093 and AUC = 0.834 ± 0.007). For non-inferior performance, the 5 variables model (age, sex, saturation, well-aerated lung parenchyma and cardiothoracic vascular calcium) was selected as the final model and the extraction of CT-derived parameters was fully automatized. The fully automatic model showed AUC = 0.842 (95% CI: 0.816-0.867) on wave 1 and was used to build a 0-100 scale risk score (AI-SCoRE). The predictive performance was confirmed on wave 2 (AUC 0.808; 95% CI: 0.7402-0.8766). CONCLUSIONS: AI-SCoRE is an effective and reliable platform for automatic risk stratification of COVID-19 patients based on a few unbiased clinical data and CT automatic analysis.

Whole-body low-dose computed tomography (WBLDCT) in staging and re-staging of multiple myeloma.

The objective of this study is to evaluate the prognostic features of multiple myeloma (MM) using whole-body low-dose computed tomography (WBLDCT). One hundred three patients with biopsy-proven MM who underwent WBLDCT were retrospectively enrolled. The evolution of osteolytic lesions overtime was performed by measuring the maximum axial diameter at the baseline (T0) and the end of follow-up (Te), by using a cut-off value of 10 mm. The location and dimension of up to three lesions were registered. The time-to-fracture (TTF) was recorded. Sixty-three percent of patients presented a focal pattern, 22% a diffuse pattern, and 15% a combined one. Seventy-two percent of patients with lesions ≤ 10 mm presented stability, 27% a dimensional increase, and 1% a decrease. Patients with lesions >10 mm showed a statistically significant difference regarding the mean difference of axial diameter between T0 and Te (p = 0.015). Patients with lesions >10 mm showed an odds ratio (OR) of 29.8 (95%CIs 3.8-230.5) to develop at least one fracture. Mean TTF was significantly lower in patients with lesions >10 mm in comparison with lesions ≤ 10 mm (9 ± 3 vs 23 ± 7 months, respectively, p = 0.011). WBLDCT represents a reliable imaging-based tool for proper management of MM patients, showing that diffuse form or small lytic lesions may deserve a less frequent follow-up.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia.

OBJECTIVES: To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes. METHODS: All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated. RESULTS: A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05). CONCLUSION: The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation. KEY POINTS: • Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.

Chest CT-derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy.

OBJECTIVES: Enlarged main pulmonary artery diameter (MPAD) resulted to be associated with pulmonary hypertension and mortality in a non-COVID-19 setting. The aim was to investigate and validate the association between MPAD enlargement and overall survival in COVID-19 patients. METHODS: This is a cohort study on 1469 consecutive COVID-19 patients submitted to chest CT within 72 h from admission in seven tertiary level hospitals in Northern Italy, between March 1 and April 20, 2020. Derivation cohort (n = 761) included patients from the first three participating hospitals; validation cohort (n = 633) included patients from the remaining hospitals. CT images were centrally analyzed in a core-lab blinded to clinical data. The prognostic value of MPAD on overall survival was evaluated at adjusted and multivariable Cox's regression analysis on the derivation cohort. The final multivariable model was tested on the validation cohort. RESULTS: In the derivation cohort, the median age was 69 (IQR, 58-77) years and 537 (70.6%) were males. In the validation cohort, the median age was 69 (IQR, 59-77) years with 421 (66.5%) males. Enlarged MPAD (≥ 31 mm) was a predictor of mortality at adjusted (hazard ratio, HR [95%CI]: 1.741 [1.253-2.418], p < 0.001) and multivariable regression analysis (HR [95%CI]: 1.592 [1.154-2.196], p = 0.005), together with male gender, old age, high creatinine, low well-aerated lung volume, and high pneumonia extension (c-index [95%CI] = 0.826 [0.796-0.851]). Model discrimination was confirmed on the validation cohort (c-index [95%CI] = 0.789 [0.758-0.823]), also using CT measurements from a second reader (c-index [95%CI] = 0.790 [0.753;0.825]). CONCLUSION: Enlarged MPAD (≥ 31 mm) at admitting chest CT is an independent predictor of mortality in COVID-19. KEY POINTS: • Enlargement of main pulmonary artery diameter at chest CT performed within 72 h from the admission was associated with a higher rate of in-hospital mortality in COVID-19 patients. • Enlargement of main pulmonary artery diameter (≥ 31 mm) was an independent predictor of death in COVID-19 patients at adjusted and multivariable regression analysis. • The combined evaluation of clinical findings, lung CT features, and main pulmonary artery diameter may be useful for risk stratification in COVID-19 patients.

Helmet CPAP to treat hypoxic pneumonia outside the ICU: an observational study during the COVID-19 outbreak.

BACKGROUND: Respiratory failure due to COVID-19 pneumonia is associated with high mortality and may overwhelm health care systems, due to the surge of patients requiring advanced respiratory support. Shortage of intensive care unit (ICU) beds required many patients to be treated outside the ICU despite severe gas exchange impairment. Helmet is an effective interface to provide continuous positive airway pressure (CPAP) noninvasively. We report data about the usefulness of helmet CPAP during pandemic, either as treatment, a bridge to intubation or a rescue therapy for patients with care limitations (DNI). METHODS: In this observational study we collected data regarding patients failing standard oxygen therapy (i.e., non-rebreathing mask) due to COVID-19 pneumonia treated with a free flow helmet CPAP system. Patients' data were recorded before, at initiation of CPAP treatment and once a day, thereafter. CPAP failure was defined as a composite outcome of intubation or death. RESULTS: A total of 306 patients were included; 42% were deemed as DNI. Helmet CPAP treatment was successful in 69% of the full treatment and 28% of the DNI patients (P < 0.001). With helmet CPAP, PaO2/FiO2 ratio doubled from about 100 to 200 mmHg (P < 0.001); respiratory rate decreased from 28 [22-32] to 24 [20-29] breaths per minute, P < 0.001). C-reactive protein, time to oxygen mask failure, age, PaO2/FiO2 during CPAP, number of comorbidities were independently associated with CPAP failure. Helmet CPAP was maintained for 6 [3-9] days, almost continuously during the first two days. None of the full treatment patients died before intubation in the wards. CONCLUSIONS: Helmet CPAP treatment is feasible for several days outside the ICU, despite persistent impairment in gas exchange. It was used, without escalating to intubation, in the majority of full treatment patients after standard oxygen therapy failed. DNI patients could benefit from helmet CPAP as rescue therapy to improve survival. TRIAL REGISTRATION: NCT04424992.

Influence of injection rate in determining the development of artifacts during the acquisition of dynamic arterial phase in Gd-EOB-DTPA MRI studies.

OBJECTIVE: To assess whether different Gd-EOB-DTPA injection rates could influence the development of artifacts during the arterial phase of liver MRI studies. MATERIALS AND METHODS: All Gd-EOB-DTPA liver MRI studies performed for different clinical indications at a single tertiary referral center were retrospectively evaluated. Each examination was acquired on a 1.5 T scanner with T1 In- and Out-of-Phase, T2 with and without fat-saturation, DWI, and 3D-T1 fat-sat dynamic sequences. Patients were divided into two groups according to the injection rate (1 ml/s and 1.5 ml/s). A single radiologist recorded the presence or absence of artifacts during different acquisition phases, respectively: (1) all examination; (2) only during the arterial phase; (3) only during the portal-venous phase; (4) both in arterial and portal-venous phases. From a total of 748 MRI studies performed, 229 were excluded due to the presence of artifacts during the entire examination. The remaining 519 MRI studies were divided into two groups according to the injection rate. RESULTS: The first group (flow rate = 1 ml/s) was composed by 312 (60.1%) patients and the second group (flow rate = 1.5 ml/s) by 207 (39.9%) patients. In the first group, 2 (0.6%) patients showed artifacts in all dynamic sequences; 13 (4%) only in the arterial phase, 16 (5%) only in the portal-venous phase, and 38 (12%) both in arterial and portal-venous phases; a total of 243 (78%) showed no artifacts. In the second group, 3 (1.5%) patients had artifacts in all dynamic sequences, 82 (40%) only in the arterial phase, 20 (10%) only in the portal-venous phase, and 53 (25%) both in arterial and portal-venous phases; a total of 49 (23.5%) showed no artifacts. A significant difference between the two groups regarding the absence of artifacts in all examination and the presence of artifacts only during the arterial phase was found (p < 0.001). CONCLUSION: The development of artifacts during the arterial phase of Gd-EOB-DTPA liver MRI studies could be related to the injection rate and its reduction may help to decrease the incidence of artifacts.

Acute pulmonary embolism in hospitalized patients with SARS-CoV-2-related pneumonia: multicentric experience from Italian endemic area.

PURPOSE: To analyze pulmonary embolism (PE) on chest computed tomography pulmonary angiography (CTPA) in hospitalized patients affected by SARS-CoV-2, according to the severity of lung disease based both on temporal CT features changes and on CT-severity lung involvement (CT-severity score), along with the support of clinical and laboratory findings. METHODS: We retrospectively enrolled a total of 170 patients with confirmed SARS-CoV-2 infection who underwent CTPA examination for PE suspicion. Pulmonary arteries diameters, right ventricle/left ventricle (RV/LV) ratio, presence, absence, and distribution of PE, pulmonary artery obstructive index (PAO index), and lobe involvement were recorded. All CT scans were reviewed to assess temporal CT changes and the COVID CT-severity score. RESULTS: A total of 76 out of 170 patients (44.7%) developed PE without having any major risk factors for venous thromboembolism. The most severe pulmonary arteries involvement, expressed in terms of PAO Index, occurred in those patients with markedly elevated D-dimer and C-reactive protein (CRP) values and those patients with an advanced temporal stage of lung disease. The majority PE-positive patients were hospitalized in non-intensive wards. PE-positive patients showed a slightly higher hospitalization time in comparison with PE-negative ones. In the three months of study, overall 85.9% of patients were discharged while 14.1% died, of whom 13 PE-positive (54.2%). CONCLUSIONS: Patients hospitalized for SARS-CoV-2 infection present a higher cumulative incidence of PE compared to the general population of hospitalized patients, regardless of the severity of lung inflammation or the temporal stage of the disease.

Chest CT in the emergency department for suspected COVID-19 pneumonia.

PURPOSE: In overwhelmed emergency departments (EDs) facing COVID-19 outbreak, a swift diagnosis is imperative. CT role was widely debated for its limited specificity. Here we report the diagnostic role of CT in two EDs in Lombardy, epicenter of Italian outbreak. MATERIAL AND METHODS: Admitting chest CT from 142 consecutive patients with suspected COVID-19 were retrospectively analyzed. CT scans were classified in "highly likely," "likely," and "unlikely" COVID-19 pneumonia according to the presence of typical, indeterminate, and atypical findings, or "negative" in the absence of findings, or "alternative diagnosis" when a different diagnosis was found. Nasopharyngeal swab results, turnaround time, and time to positive results were collected. CT diagnostic performances were assessed considering RT-PCR as reference standard. RESULTS: Most of cases (96/142, 68%) were classified as "highly likely" COVID-19 pneumonia. Ten (7%) and seven (5%) patients were classified as "likely" and "unlikely" COVID-19 pneumonia, respectively. In 21 (15%) patients a differential diagnosis was provided, including typical pneumonia, pulmonary edema, neoplasia, and pulmonary embolism. CT was negative in 8/142 (6%) patients. Mean turnaround time for the first COVID-19 RT-PCR was 30 ± 13 h. CT diagnostic accuracy in respect of the first test swab was 79% and increased to 91.5% after repeated swabs and/or BAL, for 18 false-negative first swab. CT performance was good with 76% specificity, 99% sensitivity, 90% positive predictive value and 97% negative predictive value. CONCLUSION: Chest CT was useful to streamline patients' triage while waiting for RT-PCR in the ED, supporting the clinical suspicion of COVID-19 or providing alternative diagnosis.

Computed Tomography Angiography Combined With Knowledge-Based Iterative Algorithm for Transcatheter Aortic Valve Implantation Planning: Image Quality and Radiation Dose Exposure With Low-kV and Low-Contrast-Medium Protocol.

OBJECTIVE: To evaluate image quality and radiation dose exposure of low-kV setting and low-volume contrast medium (CM) computed tomography angiography (CTA) protocol for transcatheter aortic valve implantation (TAVI) planning in comparison with standard CTA protocol. METHODS: Sixty-patients were examined with 256-row MDCT for TAVI planning: 32 patients (study group) were evaluated using 80-kV electrocardiogram-gated protocol with 60 mL of CM and IMR reconstruction; 28 patients underwent a standard electrocardiogram-gated CTA study (100 kV; 80 mL of CM; iDose4 reconstruction). Subjective and objective image quality was evaluated in each patient at different aortic levels. Finally, we collected radiation dose exposure data (CT dose index and dose-length product) of both groups. RESULTS: In study protocol, significant higher mean attenuation values were achieved in all measurements compared with the standard protocol. There were no significant differences in the subjective image quality evaluation in both groups. Mean dose-length product of study group was 56% lower than in the control one (P < 0.0001). CONCLUSION: Low-kV and low-CM volume CTA, combined with IMR, allows to correctly performing TAVI planning with high-quality images and significant radiation dose reduction compared with standard CTA protocol.

Diagnostic accuracy of multiparametric magnetic resonance imaging combined with clinical parameters in the detection of clinically significant prostate cancer: A novel diagnostic model.

OBJECTIVES: To evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging in the detection of prostate cancer, according to Prostate Imaging Reporting and Data System, and the usefulness of combining clinical parameters to improve patients' risk assessment. METHODS: Overall, 201 patients underwent multiparametric magnetic resonance imaging investigation with a 3-T magnet and a 32-channel body coil based on triplanar high-resolution T2-weighted, diffusion-weighted and T1-weighted dynamic contrast-enhanced imaging before, during and after intravenous administration of paramagnetic contrast agent. Random transrectal ultrasound-guided biopsy was carried out for all eligible patients. If a Prostate Imaging Reporting and Data System ≥3 lesion was present, a targeted biopsy with magnetic resonance imaging-transrectal ultrasound fusion-guided system was carried out. RESULTS: Sensitivity, specificity, positive predictive value and negative predictive value of Prostate Imaging Reporting and Data System ≥3 lesions for the detection of prostate cancer were 65.1%, 54.9%, 43.1% and 75.0% respectively, with an accuracy of 64.2% (55.1-72.7%). At uni- and multivariate analysis, age ≥70 years and prostate-specific antigen density ≥0.15 ng/mL/mL were significantly associated with prostate cancer. A new risk model named "modified Prostate Imaging Reporting and Data System" was created considering age and prostate-specific antigen density in addition to the Prostate Imaging Reporting and Data System score showing an improved correlation with prostate cancer compared with the Prostate Imaging Reporting and Data System alone (area under curve 71.4%, 95% confidence interval 62.2-80.5 vs area under curve 62.6%, 95% confidence interval 52.1-73; P ≤ 0.0001). CONCLUSIONS: The accuracy of Prostate Imaging Reporting and Data System alone in the diagnosis of prostate cancer might be suboptimal, whereas a novel risk model based on the combination of multiparametric magnetic resonance imaging data with clinical parameters could offer higher discrimination and improve the ability of diagnosing clinically significant disease.

Characterization of the arterial enhancement pattern of focal liver lesions by multiple arterial phase magnetic resonance imaging: comparison between hepatocellular carcinoma and focal nodular hyperplasia.

PURPOSE: To evaluate the features of arterial enhancement pattern of focal nodular hyperplasia (FNH) and hepatocellular carcinoma (HCC) by triple-phase arterial magnetic resonance imaging (MRI). METHODS: Data were retrospectively collected from 52 consecutive patients who underwent triple-phase arterial MRI using hepatocyte-specific contrast agents (Gd-EOB-DTPA) from January 2017 to October 2017, with a MR imaging diagnosis of HCC or FNH. The images were independently assessed by two blinded readers. Contrast enhancement ratio (CER) and liver-to-lesion contrast ratio (LLCR) were calculated. The lesions were classified visually and also based on the peak of LLCR into the following groups: (1) early arterial, (2) middle arterial and (3) late arterial. Data were eventually analysed using nonparametric tests. RESULTS: The CER analysis showed no significant difference between HCC and FNH patients (p > 0.05). LLCRFNH were significantly higher than LLCRHCC in the early arterial (p = 0.01), but not in the middle and late arterial phases (p = 0.20 and p = 0.82, respectively). LLCRHCC presented a meaningful increase from early to middle arterial phase (p = 0.009), whereas LLCRFNH showed a decrease from middle to late arterial phase (p = 0.004). Based on the peak of LLCR, 17 (55%) FNHs were classified into early, 11 (35%) in middle and only 3 (10%) in late arterial phase groups. Similarly, 14 (34%) HCCs were categorized into early, 13 (32%) in middle and 14 (33%) in late arterial phase groups. There was a good agreement between qualitative analysis and LLCR in 85% of cases. CONCLUSION: The optimal visualization of FNH has been detected in early and middle arterial phases while HCC has been best observed during middle and late arterial phases.

Micro-computed tomography: a new diagnostic tool in postmortem assessment of brain anatomy in small fetuses.

PURPOSE: The aim of our study was to evaluate the postmortem micro-CT anatomy of early fetal human fetal brains, either in situ or isolated. METHODS: We studied 12 ex vivo specimens, 9 whole human fetuses (9-18 GW), and 3 isolated samples (16-26 GW). Specimens were fixed in formalin, then immersed in Lugol solution. Images were evaluated by two neuroradiologists. The depiction of CNS structures was defined based on the comparison between micro-CT images and a reference histologic anatomical Atlas of human brain development. RESULTS: Micro-CT provided informative high-resolution brain images in all cases, with the exception of one case (9 weeks) due to advanced maceration. All major CNS structures (i.e., brain hemispheres, layering, ventricles, germinal neuroepithelium, basal ganglia, corpus callosum, major cranial nerves, and structures of the head and neck) were recognizable. CONCLUSIONS: Micro-CT imaging of the early fetal brain is feasible and provides high-quality images that correlate with the histological Atlas of the human brain, offering multiplanar and volumetric images that can be stored and shared for clinical, teaching, and research purposes.

Diagnostic Value of Quantitative Perfusion Computed Tomography Technique in the Assessment of Tumor Response to Sorafenib in Patients With Advanced Hepatocellular Carcinoma.

AIM: The aim of this study was to assess the role of dynamic contrast-enhanced perfusion computed tomography (pCT) imaging in the early detection of blood flow changes related to antiangiogenic treatment with sorafenib, in patients with advanced hepatocellular carcinoma (HCC), being the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria the standard of reference. METHODS: Between 2012 and 2016, 43 cirrhotic patients (male, n = 39; female, n = 4) with biopsy-proven multifocal HCC underwent multi-detector-row computed tomography, and pCT examinations were performed before and every 2 months after sorafenib administration. Perfusion CT technique is based on the acquisition of 16 dynamic slices/scan per 40 scans, performed on a 256-slice multi-detector-row computed tomography scanner, after intravenous bolus injection of 50 mL of iodinated contrast agent (350 mg I/mL) at a flow rate of 5 mL/s. According to mRECIST, patients were stratified into complete (CR) or partial response (PR) and stable (SD) or progressive disease (PD). The following pCT parameters were calculated: hepatic perfusion (mL/s per 100 g), time to peak (seconds), arterial perfusion (mL/s), and hepatic perfusion index (%). Perfusion CT values at baseline and first follow-up were reported for all mRECIST groups and then compared between the nonprogressor (CR, PR, SD) and progressor groups (PD). RESULTS: Most pCT values were significantly higher (P < 0.01) between baseline and follow-up in the CR and PR groups, whereas nonsignificant differences were found among SD patients, and a nonsignificant trend (P > 0.05) toward increase was observed among PD patients. Moreover, pCT values were significantly higher (P = 0.05) at baseline in the nonprogressor group compared with the progressor. CONCLUSION: Preliminary results suggest that pCT adds quantitative data of vascularization, thus demonstrating its usefulness in the assessment of therapeutic response to sorafenib in advanced HCC, in line with mRECIST criteria, offering 1-step information on tissue cellularity and vascularization.

Perfusion-CT analysis for assessment of hepatocellular carcinoma lesions: diagnostic value of different perfusion maps.

BACKGROUND: Computed tomography liver perfusion (CTLP) has been improved in recent years, offering a variety of perfusion-parametric maps. A map that better discriminates hepatocellular carcinoma (HCC) is still to be found. PURPOSE: To compare different CTLP maps, regarding their ability to differentiate cirrhotic or non-cirrhotic parenchyma from malignant HCC. MATERIAL AND METHODS: Twenty-six patients (11 cirrhotic) with 50 diagnosed HCC lesions, underwent CTLP on a 128-row dual-energy CT system. Nine different maps were generated. Regions of interest (ROIs) were positioned on non-tumorous parenchyma and on HCCs found on previous magnetic resonance imaging. Perfusion parameters for non-cirrhotic and cirrhotic livers were compared. Receiver operating characteristic (ROC) analysis was employed to evaluate each map's ability to discriminate HCCs from non-tumorous livers. Comparison of ROC curves was performed to evaluate statistical significance of differences in the discriminating efficiency of derived perfusion maps. RESULTS: Perfusion parameters for non-tumorous liver and HCCs recorded in cirrhotic patients did not significantly differ from corresponding values recorded in non-cirrhotic patients ( P > 0.05). The highest power for HCC discrimination was found for the maximum-slope-of-increase (MSI) parametric map, with estimated the area under ROC curve of 0.997. An MSI cut-off criterion of 2.2 HU/s was found to provide 96% sensitivity and 100% specificity. Time to peak, blood flow, and transit time to peak were also found to have high discriminating power. CONCLUSION: Among available CTLP-derived perfusion parameters, MSI was found to provide the highest diagnostic accuracy in discriminating HCCs from non-tumorous parenchyma. Perfusion parameters for non-tumorous livers and HCCs were not found to significantly differ between cirrhotic and non-cirrhotic patients.

Use of Shear Wave Elastography in the Sonographic Triage of Thyroid Nodules: Feasibility Study in a Series of Lesions Already Selected for Fine Needle Aspiration.

OBJECTIVES: The aim of this study was to evaluate the application of shear wave elastography (SWE) in the routine management of thyroid nodules, as a possible additional tool to the standard sonographic triage. METHODS: A total of 248 consecutive patients scheduled for ultrasound-guided thyroid fine-needle aspiration were included in the study. The presence of a pure colloid lesion was an exclusion criterion. Absolute and relative SWE stiffness measurements on color-coded elastograms, expressed in kilopascals and meters per second, were correlated with radiologic and pathologic features. RESULTS: SWE values in thyroid nodules were significantly higher than normal thyroid tissue (P = .0001), proving the different elastic properties of the pathologic tissues. Regarding the radiologic characteristics of the nodules, SWE highest values were associated with the largest lesions (P = .0105) but independent from sonographic and Doppler findings. The SWE elasticity was not influenced by the characteristics of the biopsy smears. The final correlation between the SWE results and the pathologic diagnoses showed a trend in stiffness from tender tumors (follicular adenoma) to papillary thyroid carcinoma (P = .016). CONCLUSIONS: SWE allows the identification of nodules within normal parenchyma; however, the present study does not confirm the potential role in differentiating between benign and malignant thyroid nodules.

Evaluation of image quality and radiation dose saving comparing knowledge model-based iterative reconstruction on 80-kV CT pulmonary angiography (CTPA) with hybrid iterative reconstruction on 100-kV CT.

OBJECTIVES: To evaluate dose reduction and image quality of 80-kV CT pulmonary angiography (CTPA) reconstructed with knowledge model-based iterative reconstruction (IMR), and compared with 100-kV CTPA with hybrid iterative reconstruction (iDose4). MATERIALS AND METHODS: One hundred and fifty-one patients were prospectively investigated for pulmonary embolism; a study group of 76 patients underwent low-kV setting (80 kV, automated mAs) CTPA study, while a control group of 75 patients underwent standard CTPA protocol (100 kV; automated mAs); all patients were examined on 256 MDCT scanner (Philips iCTelite). Study group images were reconstructed using IMR while the control group ones with iDose4. CTDIvol, DLP, and ED were evaluated. Region of interests placed in the main pulmonary vessels evaluated vascular enhancement (HU); signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. RESULTS: Compared to iDose4-CTPA, low-kV IMR-CTPA presented lower CTDIvol (6.41 ± 0.84 vs 9.68 ± 3.5 mGy) and DLP (248.24 ± 3.2 vs 352.4 ± 3.59 mGy × cm), with ED of 3.48 ± 1.2 vs 4.93 ± 1.8 mSv. Moreover, IMR-CTPA showed higher values of attenuation (670.91 ± 9.09 HU vs 292.61 ± 15.5 HU) and a significantly higher SNR (p < 0.0001) and CNR (p < 0.0001).The subjective image quality of low-kV IMR-CTPA was also higher compared with iDose4-CTPA (p < 0.0001). CONCLUSIONS: Low-dose CTPA (80 kV and automated mAs modulation) reconstructed with IMR represents a feasible protocol for the diagnosis of pulmonary embolism in the emergency setting, achieving high image quality with low noise, and a significant dose reduction within adequate reconstruction times(≤ 120 s).