Is CT Radiomics Superior to Morphological Evaluation for pN0 Characterization? A Pilot Study in Colon Cancer.

The aim of this study was to compare CT radiomics and morphological features when assessing benign lymph nodes (LNs) in colon cancer (CC). This retrospective study included 100 CC patients (test cohort) who underwent a preoperative CT examination and were diagnosed as pN0 after surgery. Regional LNs were scored with a morphological Likert scale (NODE-SCORE) and divided into two groups: low likelihood (LLM: 0-2 points) and high likelihood (HLM: 3-7 points) of malignancy. The T-test and the Mann-Whitney test were used to compare 107 radiomic features extracted from the two groups. Radiomic features were also extracted from primary lesions (PLs), and the receiver operating characteristic (ROC) was used to test a LN/PL ratio when assessing the LN's status identified with radiomics and with the NODE-SCORE. An amount of 337 LNs were divided into 167 with LLM and 170 with HLM. Radiomics showed 15/107 features, with a significant difference (p < 0.02) between the two groups. The comparison of selected features between 81 PLs and the corresponding LNs showed all significant differences (p < 0.0001). According to the LN/PL ratio, the selected features recognized a higher number of LNs than the NODE-SCORE (p < 0.001). On validation of the cohort of 20 patients (10 pN0, 10 pN2), significant ROC curves were obtained for LN/PL busyness (AUC = 0.91; 0.69-0.99; 95% C.I.; and p < 0.001) and for LN/PL dependence entropy (AUC = 0.76; 0.52-0.92; 95% C.I.; and p = 0.03). The radiomics ratio between CC and LNs is more accurate for noninvasively discriminating benign LNs compared to CT morphological features.

Liver Magnetic Resonance Elastography: Focus on Methodology, Technique, and Feasibility.

Magnetic resonance elastography (MRE) is an imaging technique that combines low-frequency mechanical vibrations with magnetic resonance imaging to create visual maps and quantify liver parenchyma stiffness. As in recent years, diffuse liver diseases have become highly prevalent worldwide and could lead to a chronic condition with different stages of fibrosis. There is a strong necessity for a non-invasive, highly accurate, and standardised quantitative assessment to evaluate and manage patients with different stages of fibrosis from diagnosis to follow-up, as the actual reference standard for the diagnosis and staging of liver fibrosis is biopsy, an invasive method with possible peri-procedural complications and sampling errors. MRE could quantitatively evaluate liver stiffness, as it is a rapid and repeatable method with high specificity and sensitivity. MRE is based on the propagation of mechanical shear waves through the liver tissue that are directly proportional to the organ's stiffness, expressed in kilopascals (kPa). To obtain a valid assessment of the real hepatic stiffness values, it is mandatory to obtain a high-quality examination. To understand the pearls and pitfalls of MRE, in this review, we describe our experience after one year of performing MRE from indications and patient preparation to acquisition, quality control, and image analysis.

Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm.

OBJECTIVES: To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm. MATERIALS AND METHODS: Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-point Likert scale. RESULTS: Fifty patients (mean age: 70 ± 10 years, 23 men) were enrolled and 130 liver lesions (105 benign lesions, 25 metastases) were identified. DLIR_H achieved the highest SNR and CNR, comparable to ASiR-V 100% (p ≥ .051). DLIR_M returned the highest subjective image quality (score: 5; IQR: 4-5; p ≤ .001) and significant median increase (29%) in FOM (p < .001). Differences in detection were identified only for lesions ≤ 0.5 cm: 32/33 lesions were detected with DLIR_M and 26 lesions were detected with ASiR-V 50% (p = .031). Lesion accuracy of was 93.8% (95% CI: 88.1, 97.3; 122 of 130 lesions) for DLIR and 87.7% (95% CI: 80.8, 92.8; 114 of 130 lesions) for ASiR-V 50%. CONCLUSIONS: DLIR yields superior image quality and provides higher diagnostic accuracy compared to ASiR-V in the assessment of hypovascular liver lesions, in particular for lesions ≤ 0.5 cm. CLINICAL RELEVANCE STATEMENT: Deep learning image reconstruction algorithm demonstrates higher diagnostic accuracy compared to iterative reconstruction in the identification of hypovascular liver lesions, especially for lesions ≤ 0.5 cm. KEY POINTS: • Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction.

Radiomics applications in cardiac imaging: a comprehensive review.

Radiomics is a new emerging field that includes extraction of metrics and quantification of so-called radiomic features from medical images. The growing importance of radiomics applied to oncology in improving diagnosis, cancer staging and grading, and improved personalized treatment, has been well established; yet, this new analysis technique has still few applications in cardiovascular imaging. Several studies have shown promising results describing how radiomics principles could improve the diagnostic accuracy of coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) in diagnosis, risk stratification, and follow-up of patients with coronary heart disease (CAD), ischemic heart disease (IHD), hypertrophic cardiomyopathy (HCM), hypertensive heart disease (HHD), and many other cardiovascular diseases. Such quantitative approach could be useful to overcome the main limitations of CCTA and MRI in the evaluation of cardiovascular diseases, such as readers' subjectiveness and lack of repeatability. Moreover, this new discipline could potentially overcome some technical problems, namely the need of contrast administration or invasive examinations. Despite such advantages, radiomics is still not applied in clinical routine, due to lack of standardized parameters acquisition, inconsistent radiomic methods, lack of external validation, and different knowledge and experience among the readers. The purpose of this manuscript is to provide a recent update on the status of radiomics clinical applications in cardiovascular imaging.

Development and Validation of Artificial-Intelligence-Based Radiomics Model Using Computed Tomography Features for Preoperative Risk Stratification of Gastrointestinal Stromal Tumors.

BACKGROUND: preoperative risk assessment of gastrointestinal stromal tumors (GISTS) is required for optimal and personalized treatment planning. Radiomics features are promising tools to predict risk assessment. The purpose of this study is to develop and validate an artificial intelligence classification algorithm, based on CT features, to define GIST's prognosis as determined by the Miettinen classification. METHODS: patients with histological diagnosis of GIST and CT studies were retrospectively enrolled. Eight morphologic and 30 texture CT features were extracted from each tumor and combined to obtain three models (morphologic, texture and combined). Data were analyzed using a machine learning classification (WEKA). For each classification process, sensitivity, specificity, accuracy and area under the curve were evaluated. Inter- and intra-reader agreement were also calculated. RESULTS: 52 patients were evaluated. In the validation population, highest performances were obtained by the combined model (SE 85.7%, SP 90.9%, ACC 88.8%, and AUC 0.954) followed by the morphologic (SE 66.6%, SP 81.8%, ACC 76.4%, and AUC 0.742) and texture (SE 50%, SP 72.7%, ACC 64.7%, and AUC 0.613) models. Reproducibility was high of all manual evaluations. CONCLUSIONS: the AI-based radiomics model using a CT feature demonstrates good predictive performance for preoperative risk stratification of GISTs.

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

ABSTRACT: Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented various technical advances, such as automatic noise reduction filters, automatic exposure control, and refined imaging reconstruction algorithms.Focusing on imaging reconstruction, filtered back-projection has represented the standard reconstruction algorithm for over 3 decades, obtaining adequate image quality at standard radiation dose exposures. To overcome filtered back-projection reconstruction flaws in low-dose CT data sets, advanced iterative reconstruction algorithms consisting of either backward projection or both backward and forward projections have been developed, with the goal to enable low-dose CT acquisitions with high image quality. Iterative reconstruction techniques play a key role in routine workflow implementation (eg, screening protocols, vascular and pediatric applications), in quantitative CT imaging applications, and in dose exposure limitation in oncologic patients.Therefore, this review aims to provide an overview of the technical principles and the main clinical application of iterative reconstruction algorithms, focusing on the strengths and weaknesses, in addition to integrating future perspectives in the new era of artificial intelligence.

Adrenal Lesions: A Review of Imaging.

Adrenal lesions are frequently incidentally diagnosed during investigations for other clinical conditions. Despite being usually benign, nonfunctioning, and silent, they can occasionally cause discomfort or be responsible for various clinical conditions due to hormonal dysregulation; therefore, their characterization is of paramount importance for establishing the best therapeutic strategy. Imaging techniques such as ultrasound, computed tomography, magnetic resonance, and PET-TC, providing anatomical and functional information, play a central role in the diagnostic workup, allowing clinicians and surgeons to choose the optimal lesion management. This review aims at providing an overview of the most encountered adrenal lesions, both benign and malignant, including describing their imaging characteristics.

Radiomic Cancer Hallmarks to Identify High-Risk Patients in Non-Metastatic Colon Cancer.

The study was aimed to develop a radiomic model able to identify high-risk colon cancer by analyzing pre-operative CT scans. The study population comprised 148 patients: 108 with non-metastatic colon cancer were retrospectively enrolled from January 2015 to June 2020, and 40 patients were used as the external validation cohort. The population was divided into two groups­High-risk and No-risk­following the presence of at least one high-risk clinical factor. All patients had baseline CT scans, and 3D cancer segmentation was performed on the portal phase by two expert radiologists using open-source software (3DSlicer v4.10.2). Among the 107 radiomic features extracted, stable features were selected to evaluate the inter-class correlation (ICC) (cut-off ICC > 0.8). Stable features were compared between the two groups (T-test or Mann−Whitney), and the significant features were selected for univariate and multivariate logistic regression to build a predictive radiomic model. The radiomic model was then validated with an external cohort. In total, 58/108 were classified as High-risk and 50/108 as No-risk. A total of 35 radiomic features were stable (0.81 ≤ ICC < 0.92). Among these, 28 features were significantly different between the two groups (p < 0.05), and only 9 features were selected to build the radiomic model. The radiomic model yielded an AUC of 0.73 in the internal cohort and 0.75 in the external cohort. In conclusion, the radiomic model could be seen as a performant, non-invasive imaging tool to properly stratify colon cancers with high-risk disease.

Cardiac Magnetic Resonance Imaging in Immune Check-Point Inhibitor Myocarditis: A Systematic Review.

Immune checkpoint inhibitors (ICIs) are a family of anticancer drugs in which the immune response elicited against the tumor may involve other organs, including the heart. Cardiac magnetic resonance (CMR) imaging is increasingly used in the diagnostic work-up of myocardial inflammation; recently, several studies investigated the use of CMR in patients with ICI-myocarditis (ICI-M). The aim of the present systematic review is to summarize the available evidence on CMR findings in ICI-M. We searched electronic databases for relevant publications; after screening, six studies were selected, including 166 patients from five cohorts, and further 86 patients from a sub-analysis that were targeted for a tissue mapping assessment. CMR revealed mostly preserved left ventricular ejection fraction; edema prevalence ranged from 9% to 60%; late gadolinium enhancement (LGE) prevalence ranged from 23% to 83%. T1 and T2 mapping assessment were performed in 108 and 104 patients, respectively. When available, the comparison of CMR with endomyocardial biopsy revealed partial agreement between techniques and was higher for native T1 mapping amongst imaging biomarkers. The prognostic assessment was inconsistently assessed; CMR variables independently associated with the outcome included decreasing LVEF and increasing native T1. In conclusion, CMR findings in ICI-M include myocardial dysfunction, edema and fibrosis, though less evident than in more classic forms of myocarditis; native T1 mapping retained the higher concordance with EMB and significant prognostic value.

The Role of Chest CT Radiomics in Diagnosis of Lung Cancer or Tuberculosis: A Pilot Study.

In many low-income countries, the poor availability of lung biopsy leads to delayed diagnosis of lung cancer (LC), which can appear radiologically similar to tuberculosis (TB). To assess the ability of CT Radiomics in differentiating between TB and LC, and to evaluate the potential predictive role of clinical parameters, from March 2020 to September 2021, patients with histological diagnosis of TB or LC underwent chest CT evaluation and were retrospectively enrolled. Exclusion criteria were: availability of only enhanced CT scans, previous lung surgery and significant CT motion artefacts. After manual 3D segmentation of enhanced CT, two radiologists, in consensus, extracted and compared radiomics features (T-test or Mann−Whitney), and they tested their performance, in differentiating LC from TB, via Receiver operating characteristic (ROC) curves. Forty patients (28 LC and 12 TB) were finally enrolled, and 31 were male, with a mean age of 59 ± 13 years. Significant differences were found in normal WBC count (p < 0.019) and age (p < 0.001), in favor of the LC group (89% vs. 58%) and with an older population in LC group, respectively. Significant differences were found in 16/107 radiomic features (all p < 0.05). LargeDependenceEmphasis and LargeAreaLowGrayLevelEmphasis showed the best performance in discriminating LC from TB, (AUC: 0.92, sensitivity: 85.7%, specificity: 91.7%, p < 0.0001; AUC: 0.92, sensitivity: 75%, specificity: 100%, p < 0.0001, respectively). Radiomics may be a non-invasive imaging tool in many poor nations, for differentiating LC from TB, with a pivotal role in improving oncological patients' management; however, future prospective studies will be necessary to validate these initial findings.

Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review.

Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.

Optimization of contrast medium volume for abdominal CT in oncologic patients: prospective comparison between fixed and lean body weight-adapted dosing protocols.

BACKGROUND: Patient body size represents the main determinant of parenchymal enhancement and by adjusting the contrast media (CM) dose to patient weight may be a more appropriate approach to avoid a patient over dosage of CM. To compare the performance of fixed-dose and lean body weight (LBW)-adapted contrast media dosing protocols, in terms of image quality and parenchymal enhancement. RESULTS: One-hundred cancer patients undergoing multiphasic abdominal CT were prospectively enrolled in this multicentric study and randomly divided in two groups: patients in fixed-dose group (n = 50) received 120 mL of CM while in LBW group (n = 50) the amount of CM was computed according to the patient's LBW. LBW protocol group received a significantly lower amount of CM (103.47 ± 17.65 mL vs. 120.00 ± 0.00 mL, p < 0.001). Arterial kidney signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and pancreatic CNR were significantly higher in LBW group (all p ≤ 0.004). LBW group provided significantly higher arterial liver, kidney, and pancreatic contrast enhancement index (CEI) and portal venous phase kidney CEI (all p ≤ 0.002). Significantly lower portal vein SNR and CNR were observed in LBW-Group (all p ≤ 0.020). CONCLUSIONS: LBW-adapted CM administration for abdominal CT reduces the volume of injected CM and improves both image quality and parenchymal enhancement.

Magnetic Resonance of Rectal Cancer Response to Therapy: An Image Quality Comparison between 3.0 and 1.5 Tesla.

PURPOSE: To evaluate signal intensity (SI) differences between 3.0 T and 1.5 T on T2-weighted (T2w), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) in rectal cancer pre-, during, and postneoadjuvant chemoradiotherapy (CRT). MATERIALS AND METHODS: 22 patients with locally advanced rectal cancer were prospectively enrolled. All patients underwent T2w, DWI, and ADC pre-, during, and post-CRT on both 3.0 T MRI and 1.5 T MRI. A radiologist drew regions of interest (ROIs) of the tumor and obturator internus muscle on the selected slice to evaluate SI and relative SI (rSI). Additionally, a subanalysis evaluating the SI before and after-CRT (∆SI pre-post) in complete responder patients (CR) and nonresponder patients (NR) on T2w, DWI, and ADC was performed. RESULTS: Significant differences were observed for T2w and DWI on 3.0 T MRI compared to 1.5 T MRI pre-, during, and post-CRT (all P < 0.001), whereas no significant differences were reported for ADC among all controls (all P > 0.05). rSI showed no significant differences in all the examinations for all sequences (all P > 0.05). ∆SI showed significant differences between 3.0 T and 1.5 T MRI for DWI-∆SI in CR and NR (188.39 ± 166.90 vs. 30.45 ± 21.73 and 169.70 ± 121.87 vs. 22.00 ± 31.29, respectively, all P 0.02) and ADC-∆SI for CR (-0.58 ± 0.27 vs. -0.21 ± 0.24P value 0.02), while no significant differences were observed for ADC-∆SI in NR and both CR and NR for T2w-∆SI. CONCLUSION: T2w-SI and DWI-SI showed significant differences for 3.0 T compared to 1.5 T in all three controls, while ADCSI showed no significant differences in all three controls on both field strengths. rSI was comparable for 3.0 T and 1.5 T MRI in rectal cancer patients; therefore, rectal cancer patients can be assessed both at 3.0 T MRI and 1.5 T MRI. However, a significant DWI-∆SI and ADC-∆SI on 3.0 T in CR might be interpreted as a better visual assessment in discriminating response to therapy compared to 1.5 T. Further investigations should be performed to confirm future possible clinical application.

Dynamic contrast-enhanced magnetic resonance imaging in locally advanced rectal cancer: role of perfusion parameters in the assessment of response to treatment.

PURPOSE: To correlate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters to tumor grading and to assess their reliability in predicting pathological complete response (pCR) before neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC). MATERIALS AND METHODS: Forty patients (24 male; mean age, 67.3 ± 8.1 years) with histologically proven LARC who had undergone 3-Tesla DCE-MRI before (MRI_1) and after CRT (MRI_2) between August 2015 and February 2016 were included in this retrospective study. DCE-MRI parameters at MRI_1 and MRI_2 were extracted by two board certified radiologists in consensus reading with Olea Sphere 2.3 software using the extended Tofts model. Based on DCE-MRI results, patients were divided in complete responders (CR) and non-complete responders (nCR) and the perfusion parameters were correlated to tumor grading and pCR. RESULTS: Wash-out and Kep at MRI_1 showed significant correlation with LARC grading (P = 0.004 and 0.01, respectively). Ve showed a significant increase between MRI_1 (0.47 ± 0.27) and MRI_2 (0.63 ± 0.23; P = 0.007). Ktrans measured at MRI_1 was significantly higher in CR (0.66 ± 0.48) compared to nCR (0.53 ± 0.34, P = 0.02). CONCLUSION: Wash-out and Kep measured before CRT correlate with LARC grading. Ve changes during CRT, while Ktrans measured before CRT may predict the response to therapy. Therefore, DCE-MRI parameters can predict tumor aggressiveness and CRT efficacy, playing a role as imaging biomarkers in patients with LARC.

A noise-optimized virtual monoenergetic reconstruction algorithm improves the diagnostic accuracy of late hepatic arterial phase dual-energy CT for the detection of hypervascular liver lesions.

OBJECTIVES: To assess the image quality and diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) algorithm compared with standard virtual monoenergetic imaging (VMI) and linearly-blended (M_0.6) reconstructions for the detection of hypervascular liver lesions in dual-energy CT (DECT). METHODS: Thirty patients who underwent clinical liver MRI were prospectively enrolled. Within 60 days of MRI, arterial phase DECT images were acquired on a third-generation dual-source CT and reconstructed with M_0.6, VMI and VMI+ algorithms from 40 to 100 keV in 5-keV intervals. Liver parenchyma and lesion contrast-to-noise-ratios (CNR) were calculated. Two radiologists assessed image quality. Lesion sensitivity, specificity and area under the receiver operating characteristic curves (AUCs) were calculated for the three algorithms with MRI as the reference standard. RESULTS: VMI+ datasets from 40 to 60 keV provided the highest liver parenchyma and lesion CNR (p ≤0.021); 50 keV VMI+ provided the highest subjective image quality (4.40±0.54), significantly higher compared to VMI and M_0.6 (all p <0.001), and the best diagnostic accuracy in < 1-cm diameter lesions (AUC=0.833 vs. 0.777 and 0.749, respectively; p ≤0.003). CONCLUSIONS: 50-keV VMI+ provides superior image quality and diagnostic accuracy for the detection of hypervascular liver lesions with a diameter < 1cm compared to VMI or M_0.6 reconstructions. KEY POINTS: • Low-keV VMI+ are characterized by higher contrast resulting from maximum iodine attenuation. • VMI+ provides superior image quality compared with VMI or M_0.6. • 50-keV_VMI+ provides higher accuracy for the detection of hypervascular liver lesions < 1cm.

High-pitch low-voltage CT coronary artery calcium scoring with tin filtration: accuracy and radiation dose reduction.

OBJECTIVES: To investigate diagnostic accuracy and radiation dose of high-pitch CT coronary artery calcium scoring (CACS) with tin filtration (Sn100kVp) versus standard 120kVp high-pitch acquisition. METHODS: 78 patients (58% male, 61.5±9.1 years) were prospectively enrolled. Subjects underwent clinical 120kVp high-pitch CACS using third-generation dual-source CT followed by additional high-pitch Sn100kVp acquisition. Agatston scores, calcium volume scores, Agatston score categories, percentile-based risk categorization and radiation metrics were compared. RESULTS: 61/78 patients showed coronary calcifications. Median Agatston scores were 34.9 [0.7-197.1] and 41.7 [0.7-207.2] and calcium volume scores were 34.1 [0.7-218.0] for Sn100kVp and 35.7 [1.1-221.0] for 120kVp acquisitions, respectively (both p<0.0001). Bland-Altman analysis revealed underestimated Agatston scores and calcium volume scores with Sn100kVp versus 120kVp acquisitions (mean difference: 16.4 and 11.5). However, Agatston score categories and percentile-based risk categories showed excellent agreement (ĸ=0.98 and ĸ=0.99). Image noise was 25.8±4.4HU and 16.6±2.9HU in Sn100kVp and 120kVp scans, respectively (p<0.0001). Dose-length-product was 9.9±4.8mGy*cm and 40.9±14.4mGy*cm with Sn100kVp and 120kVp scans, respectively (p<0.0001). This resulted in significant effective radiation dose reduction (0.13±0.07mSv vs. 0.57±0.2mSv, p<0.0001) for Sn100kVp acquisitions. CONCLUSION: CACS using high-pitch low-voltage tin-filtered acquisitions demonstrates excellent agreement in Agatston score and percentile-based cardiac risk categorization with standard 120kVp high-pitch acquisitions. Furthermore, radiation dose was significantly reduced by 78% while maintaining accurate risk prediction. KEY POINTS: • Coronary artery calcium scoring with tin filtration reduces radiation dose by 78%. • There is excellent correlation between high-pitch Sn100kVp and standard 120kVp acquisitions. • Excellent agreement regarding Agatston score categories and percentile-based risk categorization was achieved. • No cardiac risk reclassifications were observed using Sn100kVp coronary artery calcium scoring.

Quantitative inversion time prescription for myocardial late gadolinium enhancement using T1-mapping-based synthetic inversion recovery imaging: reducing subjectivity in the estimation of inversion time.

To develop a quantitative T1-mapping-based synthetic inversion recovery (IRsynth) approach to calculate the optimal inversion time (TI0) for late gadolinium enhancement (LGE) imaging. Prospectively enrolled patients (n = 130, 58 ± 16 years) underwent cardiac MRI on a 1.5T system including Look-Locker TI-scout (LL), modified LL IR (MOLLI)-based T1-mapping, and LGE acquisitions. Patients were randomized into two groups: LL group (TI-scout followed T1-mapping) or MOLLI group (T1-mapping followed TI-scout). In both groups, the second acquisition was used to determine the TI0 for LGE. IRsynth images were generated from T1-maps between TI = 200-400 ms in 5 ms increments. Image quality was rated on a 3-point scale and the remote/background signal intensity ratio (SIR) was calculated. In the LL group (n = 53), the TI-scout-based TI0 was significantly shorter compared to IRsynth [230 ms (219-242) vs. 280 ms (263-297), P < 0.0001]. The TI0 used for LGE was set 30-40 ms longer [261 ms (247-276), P < 0.0001] than the TI-scout-based TI0, resulting in a TI0 ~ 20 ms shorter than what was obtained by IRsynth (P = 0.0156). In the MOLLI group (n = 63), IRsynth-based TI0 was significantly longer than the TI-scout-based TI0 [298 ms (262-334) vs. 242 ms (217-267), P = 0.0313]. The quality of myocardial nulling was rated higher [2.4 (2.2-2.5) vs. 2.0 (1.8-2.1), P = 0.0042] and the remote/background SIR was found to be more optimal (1.6 [1.1-2.1] vs. 2.6 [1.8-3.3], P = 0.0256) in the MOLLI group. T1-based IRsynth selects TI0 for LGE more accurately than conventional TI-scout imaging. IRsynth improves TI0 selection by providing excellent visualization of the representative image contrast for LGE images, reducing operator dependence in LGE acquisition.

Bowel preparation in CT colonography: Is diet restriction necessary? A randomised trial (DIETSAN).

OBJECTIVES: To investigate whether diet restriction affects quality of colon cleansing and patient tolerance during reduced bowel preparation for CT colonography (CTC). METHODS: Asymptomatic and symptomatic patients were enrolled in this pragmatic, single-centre, randomised trial. All patients were randomly assigned (1:1 ratio, blocks of ten) to receive a reduced bowel preparation and faecal tagging with (Diet-Restriction-Group [DR]) or without (No-Diet-Restriction-Group [NDR]) dietary restriction. Five readers performed a blinded subjective image analysis, by means of 4-point Likert-scales from 0 (highest score) to 3 (worst score). Endpoints were the quality of large bowel cleansing and tolerance to the assigned bowel preparation regimen. The trial is registered at ClinicalTrial.gov (URomLSDBAL1). RESULTS: Ninety-five patients were randomly allocated to treatments (48 in NDR-group, 47 in DR-group). Both groups resulted in optimal colon cleansing. The mean residual stool (0.22, 95%CI 0.00-0.44) and fluid burden (0.39, 95%CI 0.25-0.53) scores for patients in DR-group were similar to those in patients in NDR-group (0.25, 95%CI 0.03-0.47 [p = 0.82] and 0.49, 95%CI 0.30-0.67 [p = 0.38], respectively). Tolerance was significantly better in NDR-group. CONCLUSION: A reduced bowel preparation in association with faecal tagging and without any dietary restriction demonstrated optimal colon cleansing effectiveness for CTC, providing better patient compliance compared with dietary restriction. KEY POINTS: • Dietary restriction in reduced bowel preparation regimen can be avoided. • The quality of colon cleansing is not affected by dietary restriction. • The quality of faecal tagging is not affected by dietary restriction. • Avoidance of dietary restriction improves patients' tolerance for CTC.

Heavily Calcified Coronary Arteries: Advanced Calcium Subtraction Improves Luminal Visualization and Diagnostic Confidence in Dual-Energy Coronary Computed Tomography Angiography.

OBJECTIVES: The aim of this study was to evaluate a prototype dual-energy computed tomography calcium subtraction algorithm and its impact on luminal visualization in patients with heavily calcified coronary arteries. MATERIALS AND METHODS: Twenty-nine patients (62% male; mean age, 64 ± 7 years) who had undergone dual-energy coronary computed tomography angiography were retrospectively included in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study. Linearly blended (M_0.6) and calcium-subtracted images were reconstructed. Two independent observers assessed luminal visualization of the coronary arteries in a segment-based analysis, subjective image quality, and diagnostic confidence using 5-point Likert scales. Contrast-to-noise ratios for both data sets were calculated. Wilcoxon testing and Cohen's κ were used for statistical comparisons. RESULTS: Calcium-subtracted image series showed improved lumen visualization of the coronary arteries (P = 0.008), with excellent interreader agreement (mean score, 3.3; κ = 0.82), compared with M_0.6 series (mean score, 2.9; κ = 0.77). The calcium subtraction algorithm improved diagnostic confidence compared with the M_0.6 reconstructions (mean scores, 4.0 and 3.1, respectively; all P ≤ 0.002). The image quality analysis showed no significant differences between calcium-subtracted and M_0.6 data sets (subjectively: mean scores, 4.1 and 4.2, respectively, P = 0.442; objectively: mean contrast-to-noise ratio, 37.0 and 38.2, respectively, P = 0.733). CONCLUSIONS: A prototype algorithm for calcium subtraction improves coronary lumen visualization and diagnostic confidence in patients with heavy coronary calcifications without differences in conventional subjective and objective measures of image quality.

Haralick's texture features for the prediction of response to therapy in colorectal cancer: a preliminary study.

PURPOSE: Haralick features Texture analysis is a recent oncologic imaging biomarker used to assess quantitatively the heterogeneity within a tumor. The aim of this study is to evaluate which Haralick's features are the most feasible in predicting tumor response to neoadjuvant chemoradiotherapy (CRT) in colorectal cancer. MATERIALS AND METHODS: After MRI and histological assessment, eight patients were enrolled and divided into two groups based on response to neoadjuvant CRT in complete responders (CR) and non-responders (NR). Oblique Axial T2-weighted MRI sequences before CRT were analyzed by two radiologists in consensus drawing a ROI around the tumor. 14 over 192 Haralick's features were extrapolated from normalized gray-level co-occurrence matrix in four different directions. A dedicated statistical analysis was performed to evaluate distribution of the extracted Haralick's features computing mean and standard deviation. RESULTS: Pretreatment MRI examination showed significant value (p < 0.05) of 5 over 14 computed Haralick texture. In particular, the significant features are the following: concerning energy, contrast, correlation, entropy and inverse difference moment. CONCLUSIONS: Five Haralick's features showed significant relevance in the prediction of response to therapy in colorectal cancer and might be used as additional imaging biomarker in the oncologic management of colorectal patients.