Venous-phase chest CT with reduced contrast medium dose: Utilization of spectral low keV monoenergetic images improves image quality

[Cancer imaging and prevention of renal failure]

The risk of acute renal failure (ARF) following iodinated contrast media injection has long been overestimated because of the previous use of more toxic ICPs and uncontrolled studies. Nowadays, this concept is being questioned. Patients with severe renal failure and/or ARF are the only group still considered at risk. In these patients, it is necessary to discuss an alternative without an iodinated contrast agent. Contrast-enhanced ultrasound, MRI, spectral CT or PET-CT scan can be used instead of contrast-enhanced CT. Preventive measures should be applied when appropriate substitute to CT is not available or not diagnosed (minimum necessary dose of ICP, interruption of some treatments and prior hydration). These recommendations formalized by the European Society of Urogenital Radiology (ESUR) in 2018 address most situations faced by clinicians. In complex situations, an opinion from a nephrologist remains necessary after asking the radiologist about the availability of acceptable substitutes.

Thoracic Applications of Spectral CT Scan

TOPIC IMPORTANCE

Thoracic imaging with CT scan has become an essential component in the evaluation of respiratory and thoracic diseases. Providers have historically used conventional single-energy CT; however, prevalence of dual-energy CT (DECT) is increasing, and as such, it is important for thoracic physicians to recognize the utility and limitations of this technology.

REVIEW FINDINGS

The technical aspects of DECT are presented, and practical approaches to using DECT are provided. Imaging at multiple energy spectra allows for postprocessing of the data and the possibility of creating multiple distinct image reconstructions based on the clinical question being asked. The data regarding utility of DECT in pulmonary vascular disorders, ventilatory defects, and thoracic oncology are presented. A pictorial essay is provided to give examples of the strengths associated with DECT.

SUMMARY

DECT has been most heavily studied in chronic thromboembolic pulmonary hypertension; however, it is increasingly being used across a wide spectrum of thoracic diseases. DECT combines morphologic and functional assessments in a single imaging acquisition, providing clinicians with a powerful diagnostic tool. Its role in the evaluation and treatment of thoracic diseases will likely continue to expand in the coming years as clinicians become more experienced with the technology.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas

PURPOSE

To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9).

METHODS

This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test.

RESULTS

The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076).

CONCLUSIONS

Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

Low Contrast Volume Protocol in Routine Chest CT Amid the Global Contrast Shortage: A Single Institution Experience

OBJECTIVE

To assess the effectiveness of low contrast volume (LCV) chest CT performed with multiple contrast agents on multivendor CT with varying scanning techniques.

METHODS

The study included 361 patients (65 ± 15 years; M: F 173:188) who underwent LCV chest CT on one of the six 64-256 detector-row CT scanners using single-energy (SECT) or dual-energy (DECT) modes. All patients were scanned with either a fixed-LCV (LCVf, n = 103) or weight-based LCV (LCVw, n = 258) protocol. Two thoracic radiologists independently assessed all LCV CT and patients' prior standard contrast volume (SCV, n = 263) chest CT for optimality of contrast enhancement in thoracic vasculature, cardiac chambers, and in pleuro-parenchymal and mediastinal abnormalities. CT attenuations were recorded in the main pulmonary trunk, ascending, and descending thoracic aorta. To assess the interobserver agreement, pulmonary arterial enhancement was divided into two groups: optimal or suboptimal.

RESULTS

There was no significant difference among patients' BMI (p = 0.883) in the three groups. DECT had a significantly higher aortic arterial enhancement (250 ± 99HU vs 228 ± 76 HU for SECT, p < 0.001). Optimal enhancement was present in 558 of 624 chest CT (89.4%), whereas 66 of 624 chest CT with suboptimal enhancement was noted in 48 of 258 LCVw (18.6%) and 14 of 103 LCVf (13.6%). Most patients with suboptimal enhancement with LCVw injection protocol were overweight/obese (30/48; 62.5%), (p < 0.001).

CONCLUSION

LCV chest CT can be performed across complex multivendor, multicontrast media, multiscanner, and multiprotocol CT practices. However, LCV chest CT examinations can result in suboptimal contrast enhancement in patients with larger body habitus.

Thoracic Diseases: Technique and Applications of Dual-Energy CT

Dual-energy computed tomography (DECT) is one of the most promising technological innovations made in the field of imaging in recent years. Thanks to its ability to provide quantitative and reproducible data, and to improve radiologists' confidence, especially in the less experienced, its applications are increasing in number and variety. In thoracic diseases, DECT is able to provide well-known benefits, although many recent articles have sought to investigate new perspectives. This narrative review aims to provide the reader with an overview of the applications and advantages of DECT in thoracic diseases, focusing on the most recent innovations. The research process was conducted on the databases of Pubmed and Cochrane. The article is organized according to the anatomical district: the review will focus on pleural, lung parenchymal, breast, mediastinal, lymph nodes, vascular and skeletal applications of DECT. In conclusion, considering the new potential applications and the evidence reported in the latest papers, DECT is progressively entering the daily practice of radiologists, and by reading this simple narrative review, every radiologist will know the state of the art of DECT in thoracic diseases.

Evaluation of optimal monoenergetic images acquired by dual-energy CT in the diagnosis of T staging of thoracic esophageal cancer

OBJECTIVES

The purpose of our study was to objectively and subjectively assess optimal monoenergetic image (MEI (+)) characteristics from dual-energy CT (DECT) and the diagnostic performance for the T staging in patients with thoracic esophageal cancer (EC).

METHODS

In this retrospective study, patients with histopathologically confirmed EC who underwent DECT from September 2019 to December 2020 were enrolled. One standard polyenergetic image (PEI) and five MEI (+) were reconstructed. Two readers independently assessed the lesion conspicuity subjectively and calculated the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of EC. Two readers independently assessed the T stage on the optimal MEI (+) and PEI subjectively. Multiple quantitative parameters were measured to assess the diagnostic performance to identify T1-2 from T3-4 in EC patients.

RESULTS

The study included 68 patients. Subjectively, primary tumor delineation received the highest ratings in MEI (+) _40 keV of the venous phase. Objectively, MEI (+) images showed significantly higher SNR compared with PEI (p < 0.05), peaking at MEI (+) _40 keV in the venous phase. CNR of tumor (MEI (+) _{40 keV -80 keV}) was all significantly higher than PEI in arterial and venous phases (p < 0.05), peaking at MEI (+) _40 keV in venous phases. The agreement between MEI (+) _40 keV and pathologic T categories was 81.63% (40/49). Rho values in venous phases had excellent diagnostic efficiency for identifying T1-2 from T3-4 (AUC = 0.84).

CONCLUSIONS

MEI (+) reconstructions at low keV in the venous phase improved the assessment of lesion conspicuity and also have great potential for preoperative assessment of T staging in patients with EC.

Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules

Background

This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules.

Methods

Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy.

Results

One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentration_nodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort.

Conclusions

Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.

Utilisation of virtual non-contrast images and virtual mono-energetic images acquired from dual-layer spectral CT for renal cell carcinoma: image quality and radiation dose

Background

Renal cell carcinoma (RCC) is the most common renal malignant tumour. We evaluated the potential value and dose reduction of virtual non-contrast (VNC) images and virtual monoenergetic images (VMIs) from dual-layer spectral CT (DL-CT) in the diagnosis of RCC.

Results

Sixty-two patients with pathologically confirmed RCC who underwent contrast-enhanced DL-CT were retrospectively analysed. For the comparison between true non-contrast (TNC) and VNC images of the excretory phase, the attenuation, image noise, signal-to-noise ratio (SNR) and subjective image quality of tumours and different abdominal organs and tissues were evaluated. To compare corticomedullary phase images and low keV VMIs (40 to 100 keV) from the nephrographic phase, the attenuation, image noise, SNR and subjective lesion visibility of the tumours and renal arteries were evaluated. For the tumours, significant differences were not observed in attenuation, noise or SNR between TNC and VNC images (p > 0.05). For the abdominal organs and tissues, except for fat, the difference in attenuation was 100% within 15 HU and 96.78% within 10 HU. The subjective image quality of TNC and VNC images was equivalent (p > 0.05). The attenuation of lesions in 40 keV VMIs and renal arteries in 60 keV VMIs were similar to those in the corticomedullary images (p > 0.05). The subjective lesion visibility in low keV VMIs is slightly lower than that in the corticomedullary images (p < 0.05). Using VNC and VMIs instead of TNC and corticomedullary phase images could decrease the radiation dose by 50.5%.

Conclusion

VNC images and VMIs acquired from DL-CT can maintain good image quality and decrease the radiation dose for diagnosis of RCC.

Spectral CT of the abdomen: Where are we now?

Spectral CT adds a new dimension to radiological evaluation, beyond assessment of anatomical abnormalities. Spectral data allows for detection of specific materials, improves image quality while at the same time reducing radiation doses and contrast media doses, and decreases the need for follow up evaluation of indeterminate lesions. We review the different acquisition techniques of spectral images, mainly dual-source, rapid kV switching and dual-layer detector, and discuss the main spectral results available. We also discuss the use of spectral imaging in abdominal pathologies, emphasizing the strengths and pitfalls of the technique and its main applications in general and in specific organs.

Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis

Dual energy CT (DECT)with image acquisition at two different photon X-ray levels allows the characterization of a specific tissue or material/elements, the extrapolation of virtual unenhanced and monoenergetic images, and the quantification of iodine uptake; such special capabilities make the DECT the perfect technique to support oncological imaging for tumor detection and characterization and treatment monitoring, while concurrently reducing the dose of radiation and iodine and improving the metal artifact reduction. Even though its potential in the field of oncology has not been fully explored yet, DECT is already widely used today thanks to the availability of different CT technologies, such as dual-source, single-source rapid-switching, single-source sequential, single-source twin-beam and dual-layer technologies. Moreover DECT technology represents the future of the imaging innovation and it is subject to ongoing development that increase according its clinical potentiality, in particular in the field of oncology. This review points out recent state-of-the-art in DECT applications in gland tumors, with special focus on its potential uses in the field of oncological imaging of endocrine and exocrine glands.