First pass dual input volume CT-perfusion of lung lesions: The influence of the CT- value range settings on the perfusion values of benign and malignant entities

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Comparison of Spectral and Perfusion Computed Tomography Imaging in the Differential Diagnosis of Peripheral Lung Cancer and Focal Organizing Pneumonia

Objective

To investigate the spectral and perfusion computed tomography (CT) findings of peripheral lung cancer (PLC) and focal organizing pneumonia (FOP) and to compare the accuracy of spectral and perfusion CT imaging in distinguishing PLC from FOP.

Materials and Methods

Patients who were suspected of having lung tumor and underwent “one-stop” chest spectral and perfusion CT, with their diagnosis confirmed pathologically, were prospectively enrolled from September 2020 to March 2021. Patients who were suspected of having lung tumor and underwent “one-stop” chest spectral and perfusion CT, with their diagnosis confirmed pathologically, were prospectively enrolled from September 2020 to March 2021. A total of 57 and 35 patients with PLC and FOP were included, respectively. Spectral parameters (CT_40keV, CT_70keV, CT_100keV, iodine concentration [IC], water concentration [WC], and effective atomic number [Zeff]) of the lesions in the arterial and venous phases were measured in both groups. The slope of the spectral curve (K_70keV) was calculated. The perfusion parameters, including blood volume (BV), blood flow (BF), mean transit time (MTT), and permeability surface (PS), were measured simultaneously in both groups. The differences in the spectral and perfusion parameters between the groups were examined. Receiver operating characteristic (ROC) curves were generated to calculate and compare the area under the curve (AUC), sensitivity, specificity, and accuracy of both sets of parameters in both groups.

Results

The patients’ demographic and clinical characteristics were similar in both groups (P > 0.05). In the arterial and venous phases, the values of spectral parameters (CT_40keV, CT_70keV, spectral curve K_70keV, IC, and Zeff) were greater in the FOP group than in the PLC group (P < 0.05). In contrast, the values of the perfusion parameters (BV, BF, MTT, and PS) were smaller in the FOP group than in the PLC group (P < 0.05). The AUC of the combination of the spectral parameters was larger than that of the perfusion parameters. For the former imaging method, the AUC, sensitivity, and specificity were 0.89 (95% confidence interval [CI]: 0.82–0.96), 0.86, and 0.83, respectively. For the latter imaging method, the AUC, sensitivity, and specificity were 0.80 (95% CI: 0.70–0.90), 0.71, and 0.83, respectively. There was no significant difference in AUC between the two imaging methods (P > 0.05).

Conclusion

Spectral and perfusion CT both has the capability to differentiate PLC and FOP. However, compared to perfusion CT imaging, spectral CT imaging has higher diagnostic efficiency in distinguishing them.

Pulmonary lesions: correlative study of dynamic triple-phase enhanced CT perfusion imaging with tumor angiogenesis and vascular endothelial growth factor expression

Background

To investigate value of the quantitative perfusion parameters of dynamic triple-phase enhanced CT in differential diagnosis of pulmonary lesions, and explore the correlation between perfusion parameters of lung cancer with microvessel density (MVD) and vascular endothelial growth factor (VEGF).

Methods

73 consecutive patients with lung lesions who successfully underwent pre-operative CT perfusion examination with dynamic triple-phase enhanced CT and received a final diagnosis by postoperative pathology or a clinical follow-up. The cases were divided into malignant and benign groups according to the pathological results. CT perfusion parameters, such as Median, Mean, Standard deviation (Std), Q10, Q25, Q50, Q75, Q90 of pulmonary artery perfusion (PAP), bronchial artery perfusion (BAP), perfusion index (PI) and arterial enhancement fraction (AEF) were obtained by performing computed tomography perfusion imaging (CTPI). Computed tomography perfusion (CTP) parameters were compared between malignant and benign lesions. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CTP parameters in diagnosing malignant lesions. The correlations between CTP parameters with MVD and VEGF were analysed in 36 lung cancer patients who had extra sections be used for immunohistochemistry staining of CD34 and VEGF.

Results

BAP (Mean, Std, Q90) and PI Std of benign lesions were higher than malignant lesions (p < 0.05), and PAP (Q10, Q25), PI (Median, Mean, Q10, Q25, Q50) of malignant lesions were higher than the benign (p < 0.05). The area under the ROC curve of PI Mean, PI Q10 and PI Std was 0.722 (95% CI = [0.595–0.845]), 0.728 (95% CI = [0.612–0.844]) and 0.717 (95% CI = [0.598–0.835]) respectively. Partial perfusion parameters of BAP and AEF Q10 were positively correlated with MVD (p value range is < 0.001–0.037, ρ value range is 0.483–0.683), and partial perfusion parameters of PI were negatively correlated with MVD (p value range is 0.001–0.041,ρvalue range is − 0.523–− 0.343). Partial perfusion parameters of BAP and AEF Q10 were positively correlated with VEGF (p value range is 0.001–0.016, ρvalue range is 0.398–0.570), meanwhile some perfusion parameters of PAP and PI were negatively correlated with VEGF (p value range is 0.001–0.040, ρ value range is − 0.657–0.343).

Conclusions

Quantitative parameters of dynamic triple-phase enhanced CT can provide diagnostic basis for the differentiation of lung lesions, and there were connection with tumor angiogenesis and vascular endothelial growth factor expression.

Association Between the Incidence of Pancreatic Fistula After Pancreaticoduodenectomy and the Degree of Pancreatic Fibrosis

OBJECTIVE

The objective of this study is to investigate the association between the incidence of pancreatic fistula after pancreaticoduodenectomy (PD) and the degree of pancreatic fibrosis.

METHOD

Between January 2013 and December 2016, the analysis of the clinical data of 529 cases of pancreaticoduodenectomy patients of our hospital was performed in a retrospective fashion. The univariate analysis and multivariate analysis were done using the Pearson chi-squared test and binary logistic regression analysis model; correlations were analyzed by Spearman rank correlation analysis. The value of the degree of pancreatic fibrosis to predict the incidence of pancreatic fistula after pancreaticoduodenectomy was evaluated by the area under the receiver operating characteristic (ROC) curve.

RESULTS

The total incidence of pancreatic fistula after pancreaticoduodenectomy was 28.5% (151/529). Univariate analysis and multivariate analysis showed that BMI ≥ 25 kg/m², pancreatic duct size ≤ 3 mm, pancreatic CT value< 30, the soft texture of the pancreas (judged during the operation), and the percent of fibrosis of pancreatic lobule ≤ 25% are prognostic factors of pancreatic fistula after pancreaticoduodenectomy (P < 0.05); the pancreatic CT value and the percent of fibrosis of pancreatic lobule in pancreatic fistula group were both lower than those in non-pancreatic fistula group (P < 0.05). Results indicated that there is a negative correlation between the severity of pancreatic fistula and the pancreatic CT value or the percent of fibrosis of pancreatic lobule (r = - 0.297, - 0.342, respectively). The areas under the ROC curve of the percent of fibrosis of pancreatic lobule and the pancreatic CT value were 0.756 and 0.728, respectively.

CONCLUSION

The degree of pancreatic fibrosis is a prognostic factor which can influence the pancreatic texture and the incidence of pancreatic fistula after pancreaticoduodenectomy. The pancreatic CT value can be used as a quantitative index of the degree of pancreatic fibrosis to predict the incidence of pancreatic fistula after pancreaticoduodenectomy.

Dynamic Contrast-Enhanced Perfusion Area-Detector CT: Preliminary Comparison of Diagnostic Performance for N Stage Assessment With FDG PET/CT in Non-Small Cell Lung Cancer

OBJECTIVE

The objective of our study was to directly compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion area-detector CT (ADCT) and FDG PET/CT for differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with non-small cell lung carcinoma (NSCLC).

SUBJECTS AND METHODS

Seventy-seven consecutive patients, 45 men (mean age ± SD, 70.4 ± 5.9 years) and 32 women (71.2 ± 7.7 years), underwent dynamic first-pass CE-perfusion ADCT at two or three different positions for covering the entire thorax, FDG PET/CT, surgical treatment, and pathologic examination. From all ADCT data for each of the subjects, a whole-chest perfusion map was computationally generated using the dual- and single-input maximum slope and Patlak plot methods. For quantitative N stage assessment, perfusion parameters and the maximum standardized uptake value (SUV_max) for each lymph node were determined by measuring the relevant ROI. ROC curve analyses were performed for comparing the diagnostic capability of each of the methods on a per-node basis. N stages evaluated by each of the indexes were then statistically compared with the final pathologic diagnosis by means of chi-square and kappa statistics.

RESULTS

The area under the ROC curve (A_z) values of systemic arterial perfusion (A_z = 0.89), permeability surface (A_z = 0.78), and SUV_max (A_z = 0.85) were significantly larger than the A_z values of total perfusion (A_z = 0.70, p < 0.05) and distribution volume (A_z = 0.55, p < 0.05). For each of the threshold values, agreement for systemic arterial perfusion calculated using the dual-input maximum slope model was substantial (κ = 0.70, p < 0.0001), and agreement for SUV_max was moderate (κ = 0.60, p < 0.0001).

CONCLUSION

Dynamic first-pass CE-perfusion ADCT is as useful as FDG PET/CT for the differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with NSCLC.

Multislice Analysis of Blood Flow Values in CT Perfusion Studies of Lung Cancer

Objectives. Tumour heterogeneity represents a key issue in CT perfusion (CTp), where all studies are usually based on global mean or median values of perfusion maps, often computed on whole tumour. We sought to determine whether, and to what extent, such global values can be representative of tumour heterogeneity, with respect to single slices, and could be used for therapy assessment. Materials and Methods. Twelve patients with one primary non-small cell lung cancer lesion were enrolled in this study, for a total amount of 26 CTp examinations and 118 slices. Mean and median blood flow (BF) values, calculated voxel-based, were computed on each slice and the whole tumour. To measure functional heterogeneity, entropy was calculated on BF values as well. Results. Most of the slices were not represented by the global BF values computed on the whole tumour. In addition, there are a number of lesions having equivalent global BF values, but they are composed of slices having very different heterogeneity distributions, that is, entropy values. Conclusions. Global mean/median BF values of the single slices separately should be considered for clinical assessment, only if interpreted through entropy computed on BF values. The numerical equivalence between global BF values of different lesions may correspond to different clinical status, thus inducing possible errors in choice of therapy when considering global values only.