Dual-Energy CT for Locoregional Staging of Breast Cancer: Preliminary Results

Diagnostic Accuracy of Contrast-Enhanced Thoracic Photon-Counting Computed Tomography for Opportunistic Locoregional Staging of Breast Cancer Compared With Digital Mammography: A Prospective Trial

OBJECTIVE

Accurate locoregional staging is crucial for effective breast cancer treatment. Photon-counting computed tomography (PC-CT) is an emerging technology with high spatial resolution and the ability to depict uptake of contrast agents in tissues, making it a promising tool for breast cancer imaging. The aim of this study was to establish the feasibility of locoregional staging of breast cancer through contrast-enhanced thoracic PC-CT, assess its diagnostic performance, and compare it with that of digital mammography (DM).

MATERIALS AND METHODS

Patients with newly diagnosed breast cancer, DM, and indication of thoracic CT staging were prospectively enrolled in this clinical cohort study over a period of 6 months. Participants underwent contrast-enhanced thoracic PC-CT and breast magnetic resonance imaging in prone position. After blinding to patient data, 2 radiologists independently rated PC-CT and DM regarding the following 6 characteristics: (1) diameter of the largest mass lesion, (2) infiltration of cutis/pectoral muscle/thoracic wall, (3) number of mass lesions, (4) presence/absence of adjacent ductal carcinoma in situ (DCIS), (5) tumor conspicuity, and (6) diagnostic confidence. Reference standard was generated from consensus reading of magnetic resonance imaging combined with all histopathological/clinical data by an independent adjudication committee applying TNM eighth edition.

RESULTS

Among 32 enrolled female subjects (mean ± SD age, 59 ± 13.0 years), diagnostic accuracy for T-classification was higher for PC-CT compared with DM (0.94 vs 0.50, P < 0.01). Moreover, the correlation of the number of detected tumor masses with the reference standard was stronger for PC-CT than for DM (0.72 vs 0.50, P < 0.01). We observed that PC-CT significantly ( P < 0.04) outperformed DM regarding not only sensitivity (0.83 and 0.25, respectively) but also specificity (0.99 and 0.80, respectively) for adjacent DCIS. The κ values for interreader reliability were higher for PC-CT compared with DM (mean 0.88 vs 0.54, respectively; P = 0.01).

CONCLUSIONS

Photon-counting computed tomography outperformed DM in T-classification and provided higher diagnostic accuracy for the detection of adjacent DCIS. Therefore, opportunistic locoregional staging of breast cancer in contrast-enhanced thoracic PC-CT is feasible and could overcome limitations of DM with the potential to improve patient management.

CT-based delta-radiomics nomogram to predict pathological complete response after neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma patients

BACKGROUND

This study developed a nomogram model using CT-based delta-radiomics features and clinical factors to predict pathological complete response (pCR) in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiotherapy (nCRT).

METHODS

The study retrospectively analyzed 232 ESCC patients who underwent pretreatment and post-treatment CT scans. Patients were divided into training (n = 186) and validation (n = 46) sets through fivefold cross-validation. 837 radiomics features were extracted from regions of interest (ROIs) delineations on CT images before and after nCRT to calculate delta values. The LASSO algorithm selected delta-radiomics features (DRF) based on classification performance. Logistic regression constructed a nomogram incorporating DRFs and clinical factors. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses evaluated nomogram performance for predicting pCR.

RESULTS

No significant differences existed between the training and validation datasets. The 4-feature delta-radiomics signature (DRS) demonstrated good predictive accuracy for pCR, with α-binormal-based and empirical AUCs of 0.871 and 0.869. T-stage (p = 0.001) and differentiation degree (p = 0.018) were independent predictors of pCR. The nomogram combined the DRS and clinical factors improved the classification performance in the training dataset (AUCαbin = 0.933 and AUCemp = 0.941). The validation set showed similar performance with AUCs of 0.958 and 0.962.

CONCLUSIONS

The CT-based delta-radiomics nomogram model with clinical factors provided high predictive accuracy for pCR in ESCC patients after nCRT.

Assignment of the biological value of solid breast masses based on quantitative evaluations of spectral CT examinations using electron density mapping, Zeffective mapping and iodine mapping

OBJECTIVE

We aimed to asses, in a clinical setting, whether the newly available quantitative evaluation of electron density (ED) in spectral CT examinations of the breast provide information on the biological identity of solid breast masses and whether ED maps yield added value to the diagnostic information of iodine maps and Zeff maps calculated from the same CT image datasets.

METHODS

All patients at the University Breast Cancer Center who underwent a clinically indicated Dual Layer Computed Tomography (DLCT) examination for staging of invasive breast cancer from 2018 to 2020 were prospectively included. Iodine concentration maps, Zeff maps and ED maps were automatically reconstructed from the DLCT datasets. Region of interest (ROI) based evaluations in the breast target lesions and in the aorta were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Case-by-case evaluations were carried independently by 2 of 4 radiologists for each examination, respectively. Statistical analysis derived from the ROIs was done by calculating ROC/AUC curves and Youden indices.

RESULTS

The evaluations comprised 166 DLCT examinations. In the ED maps the measurements in the breast target lesions yielded Youden cutpoints of 104.0% (reader 1) and 103.8% (reader 2) resulting in AUCs of 0.63 and 0.67 at the empirical cutpoints. The variables "Zeff" and "iodine content" derived from the target lesions showed superior diagnostical results, with a Youden cutpoint of 8.0 mg/ml in the iodine maps and cutpoints of 1.1/1.2 in the Zeff maps the AUCs ranging from 0.84 to 0.85 (p = 0.023 to <0.000). The computational combination of Zeff and ED measurements in the target lesions yielded a slight AUC increase (readers 1: 0.85-0.87; readers 2: 0.84-0.94). The ratios of the measured values in the target lesions normalized to the values measured in the aorta showed comparable results. The AUCs of ED derived from the cutpoints showed inferior results to those derived from the Zeff maps and iodine maps (ED: 0.64 and 0.66 for reader 1 and 2; Zeff: 0.86 for both readers; iodine content: 0.89 and 0.86 for reader 1 and 2, respectively). The computational combination of the ED results and the Zeff measurements did not lead to a clinically relevant diagnostic gain with AUCs ranging from 0.86 to 0.88.

CONCLUSIONS

Quantitative assessments of Zeff, iodine content and ED all targeting the physical and chemical aspects of iodine uptake in solid breast masses confirmed diagnostically robust cutpoints for the differentiation of benign and malignant findings (Zeff < 7.7, iodine content of <0.8 mg/ml). The evaluations of the ED did not indicate any added diagnostic value beyond the quantitative assessments of Zeff and iodine content. Further research is warranted to develop suitable clinical indications for the use of ED maps.

Photon-counting computed tomography - clinical application in oncological, cardiovascular, and pediatric radiology

BACKGROUND

 Photon-counting detector computed tomography (PCD-CT) is a promising new technology with the potential to fundamentally change workflows in the daily routine and provide new quantitative imaging information to improve clinical decision-making and patient management.

METHOD

 The contents of this review are based on an unrestricted literature search of PubMed and Google Scholar using the search terms "photon-counting CT", "photon-counting detector", "spectral CT", "computed tomography" as well as on the authors' own experience.

RESULTS

 The fundamental difference with respect to the currently established energy-integrating CT detectors is that PCD-CT allows for the counting of every single photon at the detector level. Based on the identified literature, PCD-CT phantom measurements and initial clinical studies have demonstrated that the new technology allows for improved spatial resolution, reduced image noise, and new possibilities for advanced quantitative image postprocessing.

CONCLUSION

 For clinical practice, the potential benefits include fewer beam hardening artifacts, a radiation dose reduction, and the use of new or combinations of contrast agents. In particular, critical patient groups such as oncological, cardiovascular, lung, and head & neck as well as pediatric patient collectives benefit from the clinical advantages.

KEY POINTS

  · Photon-counting computed tomography (PCD-CT) is being used for the first time in routine clinical practice, enabling a significant dose reduction in critical patient populations such as oncology, cardiology, and pediatrics.. · Compared to conventional CT, PCD-CT enables a reduction in electronic image noise.. · Due to the spectral data sets, PCD-CT enables fully comprehensive post-processing applications..

CITATION FORMAT

· Hagen F, Soschynski M, Weis M et al. Photon-counting computed tomography - clinical application in oncological, cardiovascular, and pediatric radiology. Fortschr Röntgenstr 2024; 196: 25 - 34.

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.

Development of a dual energy CT based model to assess response to treatment in patients with high grade serous ovarian cancer: a pilot cohort study

BACKGROUND

In patients with cancer, the current gold standard for assessing response to treatment involves measuring cancer lesions on computed tomography (CT) imaging. The percentage change in size of specific lesions determines whether patients have had a complete/partial response or progressive disease, according to RECIST criteria. Dual Energy CT (DECT) permits additional measurements of iodine concentration, a surrogate marker of vascularity. Here we explore the role of changes in iodine concentration within cancer tissue on CT scans to assess its suitability for determining treatment response in patients with high grade serous ovarian cancer (HGSOC).

METHODS

Suitable RECIST measurable lesions were identified from the CT images of HGSOC patients, taken at 2 different time points (pre and post treatment). Changes in size and iodine concentration were measured for each lesion. PR/SD were classified as responders, PD was classified as non-responder. Radiological responses were correlated with clinical and CA125 outcomes.

RESULTS

62 patients had appropriate imaging for assessment. 22 were excluded as they only had one DECT scan. 32/40 patients assessed (113 lesions) had received treatment for relapsed HGSOC. RECIST and GCIG (Gynaecologic Cancer Inter Group) CA125 criteria / clinical assessment of response for patients was correlated with changes in iodine concentration, before and after treatment. The prediction of median progression free survival was significantly better associated with changes in iodine concentration (p = 0.0001) and GCIG Ca125 / clinical assessment (p = 0.0028) in comparison to RECIST criteria (p = 0.43).

CONCLUSION

Changes in iodine concentration from dual energy CT imaging may be more suitable than RECIST in assessing response to treatment in patients with HGSOC.

TRIAL REGISTRATION

CICATRIx IRAS number 198179, 14 Dec 2015, https://www.myresearchproject.org.uk/ .

Intermodal correlation of quantitative CT-data and MRI-biomarkers derived from synchronous spectral CT-maps and breast MRI-examinations with molecular biomarkers in invasive ductal breast carcinomas

OBJECTIVE

To asses the correlation of data derived from dual-layer (DL)-CT material-maps and breast MRI data with molecular biomarkers in invasive breast carcinomas.

METHODS

All patients at the University Breast Cancer Center who underwent a clinically indicated DLCT-scan and a breast MRI for staging of invasive ductal breast cancer from 2016 to 2020 were prospectively included. Iodine concentration-maps, and Zeffective-maps were reconstructed from the CT-datasets. T1w- and T2w-signal intensities, ADC and the clustered shapes of the dynamic-curves (washout, plateau, persistent) were derived from the MRI-datasets. ROI-based evaluations of the cancers and the reference "musculature" were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation.

RESULTS

The signal intensities measured in the 3rd phase of the contrast dynamics correlated at an intermediate level of significance with the iodine content and the Zeffective-values derived from the breast target lesions (Spearmańs rank correlation-coefficient r = 0.237/0.236, p = 0.002/0.003). The bivariate and the multivariate analyses displayed correlations of an intermediate significance level of the iodine content and the Zeff-values measured in the breast target lesions with immunhistochemical subtyping (r = 0.211-0.243, p = 0.002-0.009, respectively). The Zeff-values showed the strongest correlations when normalized to the values measured in the musculature and in the aorta (r = -0.237 to -0.305, r=<0.001-0.003). The MRI-assessments showed correlations of intermediate to high significance and low to intermediate significance between the ratios of the T2w-signal intensities and the trends of the dynamic curves measured in the breast target lesions and in musculature and immunohistochemical cancer subtyping, respectively (T2w: r = 0.232-0.249, p = 0.003/0.002; dynamics: r = -0.322/-0.245, p=<0.001/0.002). The ratios of the clustered trends of the dynamic curves measured in the breast target lesions and in musculature correlated with tumor grading on intermediate significance level (r = -0.213 and -0.194, p = 0.007/0.016) and with Ki-67 on a low significance level (bivariate analysis: r = -0.160, p = 0.040). There was only a weak correlation between the ADC-values measured in the breast target lesions and HER2-expression (bivariate ansalysis: r = 0.191, p = 0.030).

CONCLUSIONS

Our preliminary results indicate that evaluation of perfusion based DLCT-data and MRI-biomarkers show correlations with the immunhistochemical subtyping of invasive ductal breast carcinomas. Further clinical research is warranted in order to validate the value of the results and define clinical situations in which the use of the described DLCT-biomaker and MRI biomarkers may be helpful in clinical patient care.

Dual Energy CT in Oncology: Benefits for Both Patients and Radiologists From an Emerging Quantitative and Functional Diagnostic Technique

Dual-energy CT (DECT) imaging makes it possible to identify the characteristics of materials that cannot be recognized with conventional single-energy CT (SECT). In the postprocessing study phase, virtual monochromatic images and virtual-non-contrast (VNC) images, also permits reduction of dose exposure by eliminating the precontrast acquisition scan. Moreover, in virtual monochromatic images, the iodine contrast increases when the energy level decreases resulting in better visualization of hypervascular lesions and in a better tissue contrast between hypovascular lesions and the surrounding parenchyma; thus, allowing for reduction of required iodinate contrast material, especially important in patients with renal impairment. All these advantages are particularly important in oncology, providing the possibility of overcoming many SECT imaging limits and making CT examinations safer and more feasible in critical patients. This review explores the basis of DECT imaging and its utility in routine oncologic clinical practice, with particular attention to the benefits of this technique for both the patients and the radiologists.

Virtual monochromatic spectral CT imaging in preoperative evaluations for intraductal spread of breast cancer: comparison with conventional CT and MRI

PURPOSE

To investigate the efficacy of virtual monochromatic spectral computed tomography imaging (VMI) in the preoperative evaluation for intraductal spread of breast cancer.

MATERIALS AND METHODS

Twenty-four women who underwent spectral CT and were pathologically diagnosed with ductal carcinoma with a ≥ 2-cm noninvasive component were retrospectively enrolled in Group 1. Twenty-two women with 22 lesions pathologically diagnosed with ductal carcinoma in situ or microinvasive carcinoma were enrolled in Group 2. We compared the contrast-to-noise ratios (CNRs) of the lesions on conventional 120-kVp CT images and 40-keV VMIs in Group 1. Two board-certified radiologists measured the maximum diameters of enhancing areas on 120-kVp CT, 40-keV VMI, and MRI in Group 2 and compared with histopathological sizes.

RESULTS

The quantitative assessment of Group 1 revealed that the mean ± SD of the CNRs in the 40-keV images were significantly greater than those in the 120-kVp images (5.5 ± 1.9 vs. 3.6 ± 1.5, p < 0.0001). The quantitative assessment of Group 2 demonstrated that the lesion size observed in the conventional 120-kVp CT images by both readers was significantly underestimated as compared to the histopathological size (p = 0.017, 0.048), whereas both readers identified no significant differences between the lesion size measured on 40-keV VMI and the histopathological data. In a comparison with MRI, 40-keV VMI provided measurement within a 10-mm error range in more lesions as compared to the conventional 120-kVp CT.

CONCLUSION

VMI improves the evaluation of intraductal spread and is useful for the preoperative evaluations of breast cancer.

Iodinated Contrast Enhancement of Breast Cancer on Prone Multidetector Computed Tomography-Preliminary Findings

OBJECTIVES

Contrast-enhanced breast imaging has gained increasing importance in the diagnosis and management of breast cancer. The aim of this study was to assess breast cancer enhancement after contrast administration on prone multidetector computed tomography (MDCT).

MATERIALS AND METHODS

This retrospective, unicentric, institutional review board-approved study included patients with newly diagnosed breast cancer who were submitted to contrast-enhanced MDCT in prone position, with image acquisition before and after nonionic iodinated contrast administration.

RESULTS

Sixty breast cancer patients aged between 31 and 74 years (mean, 49 years) were included. Most patients (n = 50, 83.3%) had no special type invasive breast carcinoma and luminal subtype (n = 45, 75%). All index breast tumors were identified on prone MDCT. Forty-three cases (70.5%) presented as mass, 13 (21.3%) as nonmass enhancement and 4 (6.6%) as both mass and nonmass enhancement. Mean tumor density was 37.8 HU and 87.9 HU on precontrast and postcontrast images, respectively. Mean contrast enhancement was 50.2 HU (range, 20-109 HU). There were no statistically significant differences in tumor enhancement according to histological type, molecular subtype, nuclear grade, tumor size, or imaging presentation.

CONCLUSIONS

Our results show that breast cancer usually can be identified and have significant contrast enhancement on prone MDCT images. This method could be used as an alternative when other contrast-enhanced breast imaging methods are not available.

Iodine map histogram metrics in early-stage breast cancer: prediction of axillary lymph node metastasis status

BACKGROUND

Variations in axillary lymph node (ALN) metastatic potential between different breast cancers lead to microscopical alterations in tumor perfusion heterogeneity. This study investigated the usefulness of histogram metrics from iodine maps in the preoperative diagnosis of metastatic ALNs in patients with early-stage breast cancer.

METHODS

Between October 2020 and November 2021 enhanced spectral computed tomography (CT) was performed in female patients with breast cancer. Quantitative spectral CT parameters and histogram parameters (mean, median, maximum, minimum, 10th percentiles, 90th percentiles, kurtosis, skewness, energy, range, and variance) from iodine maps were compared between patients with metastatic and nonmetastatic ALNs. Continuous variables were compared using Student's t-test or Mann-Whitney U test. Categorical variables were compared using Pearson's chi-square tests or Fisher's exact tests. Associations between ALN status and imaging features were evaluated using Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis.

RESULTS

This study included 113 female patients (62 and 51 in the ALN-negative and ALN-positive groups, respectively). Tumor size, molecular subtypes, and location differed significantly between the ALN-negative and ALN-positive groups (P<0.05). None of the quantitative spectral CT parameters of mass between metastatic and nonmetastatic ALN groups were significantly different (P>0.05). Histogram parameters of iodine maps for breast cancers, including maximum, 10th percentile, range, and energy, were significantly higher in the metastatic ALNs group compared with the nonmetastatic ALNs group (P<0.05). Multivariable logistic regression analyses showed that tumor location and energy were independent predictors of metastatic ALNs in breast cancers. The combination of independent predictors yielded an area under the curve (AUC) of 0.824 (sensitivity 72.5%; specificity 74.2%).

CONCLUSIONS

Whole-lesion histogram parameters derived from spectral CT iodine maps may be used as a complementary noninvasive means for the preoperative identification of ALN metastases in patients with early-stage breast cancer.

Multi-detector CT chest: can it omit the further need for contrast enhnaced spectral mammography in breast cancer patients candidate for CT staging?

Background

During multi-detector computed tomography (MDCT) of the chest, incidental breast lesions (IBLs) are occasionally encountered. Mammography remains the gold standard for the early detection of breast cancer. However, limitations exist in patients with dense breasts. Contrast spectral mammography (CESM) is widely available compared to MRI; it increases the sensitivity for breast cancer detection without decreasing the specificity.

Results

The study is a prospective study that included 113 female breast cancer patients for CT staging. One hundred and six of the patients had unilateral carcinoma and 7 of them had bilateral cancer with a total of 120 breasts evaluated. The CT findings were correlated with CESM findings regarding the multiplicity and bilaterality of the disease. The sensitivity, specificity, PPV, NPV, and accuracy of the CT in the detection of multiplicity were 97.44%, 100%, 100%, 95.45%, and 98.33%, respectively, and the sensitivity, specificity, PPV, NPV, and accuracy of the CT in the detection of bilateral disease were 68.18%, 97.96%, 88.24%, 93.20%, and 92.50%, respectively.

Conclusions

Breast cancer patients for MDCT chest as a part of their metastatic workup can omit the further need for CESM.

Correlation of CT-data derived from multiparametric dual-layer CT-maps with immunohistochemical biomarkers in invasive breast carcinomas

OBJECTIVE

To examine the correlation of quantitative measurements from material decomposition maps calculated from dual-layer CT (DLCT)-image datasets with immunohistochemical biomarkers of invasive breast carcinomas.

MATERIAL AND METHODS

All patients at the University Breast Cancer Center who underwent a clinically indicated dual-layer CT-scan for staging of invasive ductal breast carcinoma from 01/2016 to 07/2020 were prospectively included. Iodine concentration maps and maps of the effective atomic numbers (Zeffective) were reconstructed from the image datasets. ROI-based evaluations of the index tumors and predefined references tissues for normalization were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation.

RESULTS

Bivariate showed statistically significant correlations of iodine contents (r = -0.154/-0.202/0.180, p = 0.039/0.006/0.015), and Zeffective-values (r = -0.158/-0.199/0.179, p = 0.034/0.007/0.016) for all 184 carcinomas and the subgroup of 168 invasive ductal carcinomas. The results were confirmed by multivariate analyses with "age", "diameter" and "ACR-grade" as possible confounders. Normalization of the measured target values with those in the aorta confirmed significant correlations of iodine content and Zeffective compared to Estrogen (r = 0.174, p = 0.019), Progesteron (r = 0.168/0.177, p = 0.024/0.017), and HER2 receptor expression (r = -0.222/-0.184, p = 0.003/0.013). All CT-parameters showed significant correlations with immunohistochemical subtyping (r = 0.191/0.192, p = 0.010).

CONCLUSIONS

Our preliminary results indicate that iodine content and Zeffective-values derived from DLCT-examinations correlate with hormone receptor expression in invasive breast carcinomas. Assignments to benign entities already seam feasible in clinical routine CT-diagnostics. After further investigations iodine content and Zeffective may be translated as diagnostical and prognostical biomarkers into clinical routine in the long term.

Detection of axillary lymph node metastasis in breast cancer using dual-layer spectral computed tomography

PURPOSE

To investigate the value of contrast-enhanced dual-layer spectral computed tomography (DLCT) in the detection of axillary lymph node (ALN) metastasis in breast cancer.

MATERIALS AND METHODS

In this prospective study, 31 females with breast cancer underwent contrast-enhanced DLCT from August 2019 to June 2020. All ALNs were confirmed by postoperative histology. Spectral quantitative parameters, including λ _HU (in Hounsfield units per kiloelectron-volt), nIC (normalized iodine concentration), and Z_eff (Z-effective value) in both arterial and delay phases, were calculated and contrasted between metastatic and nonmetastatic ALNs using the McNemar test. Discriminating performance from metastatic and nonmetastatic ALNs was analyzed using receiver operating characteristic curves.

RESULTS

In total, 132 ALNs (52 metastatic and 80 nonmetastatic) were successfully matched between surgical labels and preoperative labels on DLCT images. All spectral quantitative parameters (λ_Hu , nIC, and Z_eff) derived from both arterial and delayed phases were greater in metastatic ALNs than in nonmetastatic SLNs (all p < 0.001). Logistic regression analyses showed that λ_Hu in the delayed phase was the best single parameter for the detection of metastatic ALNs on a per-lymph node basis, with an area under the curve of 0.93, accuracy of 86.4% (114/132), sensitivity of 92.3% (48/52), and specificity of 87.5% (70/80).

CONCLUSION

The spectral quantitative parameters derived from contrast-enhanced DLCT, such as λ_Hu , can be applied for the preoperative detection of ALN metastasis in breast cancer.

Predicting axillary lymph node metastasis in breast cancer using the similarity of quantitative dual-energy CT parameters between the primary lesion and axillary lymph node

PURPOSE

To evaluate the similarity of quantitative dual-energy computed tomography (DECT) parameters between the primary breast cancer lesion and axillary lymph node (LN) for predicting LN metastasis.

MATERIALS AND METHODS

This retrospective study included patients with breast cancer who underwent contrast-enhanced DECT between July 2019 and April 2021. Relationships between LN metastasis and simple DECT parameters, similarity of DECT parameters, and pathological and morphological features were analyzed. ROC curve analysis was used to evaluate diagnostic ability.

RESULTS

Overall, 137 LNs (39 metastases and 98 non-metastases) were evaluated. Significant differences were observed in some pathological (nuclear grade, estrogen receptor status, and Ki67 index) and morphological characteristics (shortest and longest diameters of the LN, longest-to-shortest diameter ratio, and hilum), most simple DECT parameters, and all DECT similarity parameters between the LN metastasis and non-metastasis groups (all, P < 0.001-0.004). The shortest diameter of the LN (odds ratio 2.22; 95% confidence interval 1.47, 3.35; P < 0.001) and the similarity parameter of 40-keV attenuation (odds ratio, 2.00; 95% confidence interval 1.13, 3.53; P = 0.017) were independently associated with LN metastasis compared to simple DECT parameters of 40-keV attenuation (odds ratio 1.01; 95% confidence interval 0.99, 1.03; P =0.35). The AUC value of the similarity parameters for predicting metastatic LN was 0.78-0.81, even in cohorts with small LNs (shortest diameter < 5 mm) (AUC value 0.73-0.78).

CONCLUSION

The similarity of the delayed-phase DECT parameters could be a more useful tool for predicting LN metastasis than simple DECT parameters in breast cancer, regardless of LN size.

Laryngeal and hypopharyngeal squamous cell carcinoma: association between quantitative parameters derived from dual-energy CT and histopathological prognostic factors

BACKGROUND

Dual-energy computed tomography (DECT) can provide objective evaluation of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC).

PURPOSE

To investigate the relationship between quantitative parameters acquired from DECT and histopathological prognostic factors in LHSCC.

MATERIAL AND METHODS

A total of 65 patients with LHSCC who underwent arterial phase and venous phase DECT scans were retrospectively enrolled. Iodine concentration (IC) and normalized IC (NIC) of the tumor were calculated in both the arterial (IC_A and NIC_A) and venous (IC_V and NIC_V) phases, and compared among different pathological grades, T stages, and lymph node stages. Receiver operating characteristic (ROC) curves were generated to evaluate their diagnostic performance.

RESULTS

There were significantly differences on IC_A and NIC_A among three pathological grades (IC_A, P = 0.001; NIC_A, P = 0.002). For differentiating moderately and poorly differentiated from well-differentiated LHSCC using IC_A and NIC_A, the areas under curve (AUCs) were 0.753 and 0.726, respectively. High T stage (T3/4) LHSCC showed significantly higher IC_A (P = 0.012) and NIC_A (P = 0.005) than low T stage (T1/2) LHSCC. The AUCs of the IC_A and NIC_A were 0.674 and 0.703, respectively, in discriminating high from low T stage LHSCC. Lymph node metastasis (LNM)-positive (N1/2/3) LHSCC showed significantly higher IC_A (P = 0.008) and NIC_A (P = 0.003) than LNM-negative (N0) LHSCC. For discriminating the LNM-positive from the LNM-negative group using IC_A and NIC_A, the AUCs were 0.697 and 0.744, respectively.

CONCLUSION

IC_A and NIC_A might be helpful in assessing histopathological prognostic factors in patients with LHSCC.

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.

Application of machine learning with multiparametric dual-energy computed tomography of the breast to differentiate between benign and malignant lesions

BACKGROUND

Multiparametric dual-energy computed tomography (mpDECT) is widely used to differentiate various kinds of tumors; however, the data regarding its diagnostic performance with machine learning to diagnose breast tumors is limited. We evaluated univariate analysis and machine learning performance with mpDECT to distinguish between benign and malignant breast lesions.

METHODS

In total, 172 patients with 214 breast lesions (55 benign and 159 malignant) who underwent preoperative dual-phase contrast-enhanced DECT were included in this retrospective study. Twelve quantitative features were extracted for each lesion, including CT attenuation (precontrast, arterial, and venous phases), the arterial-venous phase difference in normalized effective atomic number (nZ_eff), normalized iodine concentration (NIC), and slope of the spectral Hounsfield unit (HU) curve (λ_Hu). Predictive models were developed using univariate analysis and eight machine learning methods [logistic regression, extreme gradient boosting (XGBoost), stochastic gradient descent (SGD), linear discriminant analysis (LDA), adaptive boosting (AdaBoost), random forest (RF), decision tree, and linear support vector machine (SVM)]. Classification performances were assessed based on the area under the receiver operating characteristic curve (AUROC). The best performances of the conventional univariate analysis and machine learning methods were compared using the Delong test.

RESULTS

The univariate analysis showed that the venous phase λ_Hu had the highest AUROC (0.88). Machine learning with mpDECT achieved an excellent and stable diagnostic performance, as shown by the mean classification performances in the training dataset (AUROC, 0.88-0.99) and testing (AUROC, 0.83-0.96) datasets. The performance of the AdaBoost model based on mpDECT was more stable than the other machine learning models and superior to the univariate analysis (AUROC, 0.96 vs. 0.88; P<0.001).

CONCLUSIONS

The performance of the AdaBoost classifier based on mpDECT data achieved the highest mean accuracy compared to the other machine learning models and univariate analysis in differentiating between benign and malignant breast lesions.

Structured and shared CT radiological report of gastric cancer: a consensus proposal by the Italian Research Group for Gastric Cancer (GIRCG) and the Italian Society of Medical and Interventional Radiology (SIRM)

OBJECTIVES

Written radiological report remains the most important means of communication between radiologist and referring medical/surgical doctor, even though CT reports are frequently just descriptive, unclear, and unstructured. The Italian Society of Medical and Interventional Radiology (SIRM) and the Italian Research Group for Gastric Cancer (GIRCG) promoted a critical shared discussion between 10 skilled radiologists and 10 surgical oncologists, by means of multi-round consensus-building Delphi survey, to develop a structured reporting template for CT of GC patients.

METHODS

Twenty-four items were organized according to the broad categories of a structured report as suggested by the European Society of Radiology (clinical referral, technique, findings, conclusion, and advice) and grouped into three "CT report sections" depending on the diagnostic phase of the radiological assessment for the oncologic patient (staging, restaging, and follow-up).

RESULTS

In the final round, 23 out of 24 items obtained agreement ( ≥ 8) and consensus ( ≤ 2) and 19 out 24 items obtained a good stability (p > 0.05).

CONCLUSIONS

The structured report obtained, shared by surgical and medical oncologists and radiologists, allows an appropriate, clearer, and focused CT report essential to high-quality patient care in GC, avoiding the exclusion of key radiological information useful for multidisciplinary decision-making.

KEY POINTS

• Imaging represents the cornerstone for tailored treatment in GC patients. • CT-structured radiology report in GC patients is useful for multidisciplinary decision making.

Recent Advancements in CT and MR Imaging of Prostate Cancer

CT and MRI are both commonly used in prostate cancer (PCa) management, which includes a large spectrum from screening positive pre-diagnosis phase to metastatic disease. CT and MRI have continually evolved to meet the changing demands for PCa management. For CT, novel techniques such as dual energy CT and photon counting CT show promising results for tissue characterization and quantification. For MRI, the detection, staging, and management of prostate cancer has been significantly improved by the development of multiparametric, biparametric, and whole-body MRI techniques. Additionally, research on ultrasmall superparamagnetic particles of iron oxide contrast-enhanced MRI has revealed promising results for nodal staging of PCa. In this manuscript we aim to outline the current status and recent advancements of CT and MRI in PCa imaging.

Dual-energy CT imaging with limited-angular-range data

In dual-energy computed tomography (DECT), low- and high-kVp data are collected often over a full-angular range (FAR) of 360^○. While there exists strong interest in DECT with low- and high-kVp data acquired over limited-angular ranges (LARs), there remains little investigation of image reconstruction in DECT with LAR data.Objective: We investigate image reconstruction with minimized LAR artifacts from low- and high-kVp data over LARs of ≤180^○by using a directional-total-variation (DTV) algorithm.Methods: Image reconstruction from LAR data is formulated as a convex optimization problem in which data-l₂is minimized with constraints on image's DTVs along orthogonal axes. We then achieve image reconstruction by applying the DTV algorithm to solve the optimization problem. We conduct numerical studies from data generated over arcs of LARs, ranging from 14^○to 180^○, and perform visual inspection and quantitative analysis of images reconstructed.Results: Monochromatic images of interest obtained with the DTV algorithm from LAR data show substantially reduced artifacts that are observed often in images obtained with existing algorithms. The improved image quality also leads to accurate estimation of physical quantities of interest, such as effective atomic number and iodine-contrast concentration.Conclusion: Our study reveals that from LAR data of low- and high-kVp, monochromatic images can be obtained that are visually, and physical quantities can be estimated that are quantitatively, comparable to those obtained in FAR DECT.Significance: As LAR DECT is of high practical application interest, the results acquired in the work may engender insights into the design of DECT with LAR scanning configurations of practical application significance.

Advancement in Diagnostic Imaging of Thymic Tumors

Simple Summary

Diagnostic imaging is pivotal for the diagnosis and staging of thymic tumors. It is important to distinguish thymoma and other tumor histotypes amenable to surgery from lymphoma. Furthermore, in cases of thymoma, it is necessary to differentiate between early and advanced disease before surgery since patients with locally advanced tumors require neoadjuvant chemotherapy for improving survival. This review aims to provide to radiologists a full spectrum of findings of thymic neoplasms using traditional and innovative imaging modalities.

Abstract

Thymic tumors are rare neoplasms even if they are the most common primary neoplasm of the anterior mediastinum. In the era of advanced imaging modalities, such as functional MRI, dual-energy CT, perfusion CT and radiomics, it is possible to improve characterization of thymic epithelial tumors and other mediastinal tumors, assessment of tumor invasion into adjacent structures and detection of secondary lymph nodes and metastases. This review aims to illustrate the actual state of the art in diagnostic imaging of thymic lesions, describing imaging findings of thymoma and differential diagnosis.

Comparison of low kVp CT and dual-energy CT for the evaluation of hypervascular hepatocellular carcinoma

PURPOSE

To compare lesion conspicuity and image quality of arterial phase images obtained from low kVp (90-kVp) and dual-energy (DE) scans for the evaluation of hypervascular hepatocellular carcinoma (HCC).

METHODS

This retrospective study included 229 patients with HCC who underwent either 90 kVp (n = 106) or DE scan (80- and 150-kVp with a tin filter) (n = 123) during the arterial phase. DE scans were reconstructed into a linearly blended image with a mixed ratio of 0.6 (60% 80kVp and 40% 150 kVp) and post-processed for 40 keV and 50 keV images. The contrast-to-noise ratio (CNR) of HCC to the liver and image noise was measured. Lesion conspicuity, liver parenchymal image quality, and overall image preference were assessed qualitatively by three independent radiologists.

RESULTS

DE 40 keV images had the highest CNR of HCC, and DE blended images had the lowest image noise among four image sets (p = 0.01 and p < 0.001, respectively). There was no significant difference in mean volume CT dose index and dose-length product between DE and low kVp scan (ps > 0.05). For qualitative analyses, DE blended images had the highest scores for image quality and overall image preference (ps < 0.001).

CONCLUSION

At an equal radiation dose, DE 40 keV showed higher CNR of HCC and DE blended image showed higher image quality and image preference compared with low kVp CT.

Possibility to discriminate benign from malignant breast lesions detected on dual-layer spectral CT-evaluation

OBJECTIVES

Intramammary mass lesions are reportedly present in up to 5.8% of all contrast enhanced CT-examinations of the female chest. We aimed to assess whether their biological relevance can be estimated using spectral CT-datasets.

METHODS

In this bicentric retrospective study patients with breast masses visualized on spectral CT-examinations from 07/2017 to 06/2019 were included. Lesions were characterized as malignant or benign based on histology and/or a stable follow-up of >2 years. Conventional CT-images, iodine density-maps, virtual monoenergetic-images (40 keV, 100 keV) and Zeffective-maps were evaluated by two independent readers. Statistical analysis derived from the Regions of interest (ROIs) was done by calculating the Areas under the Receiver operating characteristic (ROC) curve (AUC) and Youden-indices.

RESULTS

106 breast masses (malignant/benign: 81/25, 76.4%/23.6%) were included. The mean AUCs of the variables "iodine content" (reader 1/2:0.97;0.98), "monoenergetic curve-slope" (0.97;0.96) and "Zeffective" (0.98;0.98) measured in the target lesions (TL) showed superior results compared to those derived from the variable "density" (0.92;0.93) (p < 0.001). The ratios "TL to aorta" calculated for the variables "iodine content", "monoenergetic curve-slope" and "Zeffective" showed superior results compared to normal breast tissue and muscle (p < 0.001). The optimal cutpoint for the "iodine content" in the TL was 0.7-0.9 mg/ml (sensitivity 96.6%, specificity 91.7%). The best diagnostic results were achieved by normalizing the iodine content in the TL to that in the aorta (optimal cutpoint 0.1, sensitivity 95.5%, 98.9%, specificity 91.7%).

CONCLUSIONS

Our preliminary results suggest that spectral CT-datasets might allow to estimate the biological dignity of breast masses detected on clinically indicated chest-examinations.

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer-a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Background

To predict response to neoadjuvant chemotherapy (NAC) of gastric cancer (GC), prior to surgery, would be pivotal to customize patient treatment. The aim of this study is to investigate the reliability of computed tomography (CT) texture analysis (TA) in predicting the histo-pathological response to NAC in patients with resectable locally advanced gastric cancer (AGC).

Methods

Seventy (40 male, mean age 63.3 years) patients with resectable locally AGC, treated with NAC and radical surgery, were included in this retrospective study from 5 centers of the Italian Research Group for Gastric Cancer (GIRCG). Population was divided into two groups: 29 patients from one center (internal cohort for model development and internal validation) and 41 from other four centers (external cohort for independent external validation). Gross tumor volume (GTV) was segmented on each pre- and post-NAC multidetector CT (MDCT) image by using a dedicated software (RayStation), and 14 TA parameters were then extrapolated. Correlation between TA parameters and complete pathological response (tumor regression grade, TRG1), was initially investigated for the internal cohort. The univariate significant variables were tested on the external cohort and multivariate logistic analysis was performed.

Results

In multivariate logistic regression the only significant TA variable was delta gray-level co-occurrence matrix (GLCM) contrast (P=0.001, Nagelkerke R²: 0.546 for the internal cohort and P=0.014, Nagelkerke R²: 0.435 for the external cohort). Receiver operating characteristic (ROC) curves, generated from the logistic regression of all the patients, showed an area under the curve (AUC) of 0.763.

Conclusions

Post-NAC GLCM contrast and dissimilarity and delta GLCM contrast TA parameters seem to be reliable for identifying patients with locally AGC responder to NAC.

Comparison of contrast-enhanced CT, dual-layer detector spectral CT, and whole-body MRI in suspected metastatic breast cancer: a prospective diagnostic accuracy study

OBJECTIVES

To compare diagnostic accuracy of contrast-enhanced CT, dual-layer detector spectral CT (DL-CT), and whole-body MRI (WB-MRI) for diagnosing metastatic breast cancer.

METHODS

One hundred eighty-two biopsy-verified breast cancer patients suspected of metastatic disease prospectively underwent contrast-enhanced DL-CT and WB-MRI. Two radiologists read the CT examinations with and without spectral data in consensus with 3-month washout between readings. Two other radiologists read the WB-MRI examinations in consensus. Lymph nodes, visceral lesions, and bone lesions were assessed. Readers were blinded to other test results. Reference standard was histopathology, previous or follow-up imaging, and clinical follow-up.

RESULTS

Per-lesion AUC was 0.80, 0.84, and 0.82 (CT, DL-CT, and WB-MRI, respectively). DL-CT showed significantly higher AUC than CT (p = 0.001) and WB-MRI (p = 0.02). Sensitivity and specificity of CT, DL-CT, and WB-MRI were 0.66 and 0.94, 0.75 and 0.95, and 0.65 and 0.98, respectively. DL-CT significantly improved sensitivity compared to CT (p < 0.0001) and WB-MRI (p = 0.002). Per-patient AUC was 0.85, 0.90, and 0.92 (CT, DL-CT, and WB-MRI, respectively). DL-CT and WB-MRI had significantly higher AUC than CT (p = 0.04 and p = 0.03). DL-CT significantly increased sensitivity compared to CT (0.89 vs. 0.79, p = 0.04). WB-MRI had significantly higher specificity than CT (0.84 vs. 0.96, p = 0.001) and DL-CT (0.87 vs. 0.96, p = 0.02).

CONCLUSIONS

DL-CT showed significantly higher per-lesion diagnostic performance and sensitivity than CT and WB-MRI. On a per-patient basis, DL-CT and WB-MRI had equal diagnostic performance superior to CT.

KEY POINTS

• Spectral CT has higher diagnostic performance for diagnosing breast cancer metastases compared to conventional CT and whole-body MRI on a per-lesion basis. • Spectral CT and whole-body MRI are superior to conventional CT for diagnosing patients with metastatic breast cancer. • Whole-body MRI is superior to conventional CT and spectral CT for diagnosing bone metastases.

Giant epidermal inclusion cyst with infection arising within the breast parenchyma: a case report

Epidermal inclusion cysts (EICs) of the breast develop in the deep breast parenchyma, and they are very rare. Only about 10 cases have been reported in the English-language literature to date. In this report, we present a rare case of a giant EIC with infection arising within the deep breast parenchyma. Unlike a typical EIC of the breast, the EIC in the present case was a cystic and solid lesion containing a large amount of liquid within the cyst and popcorn-like calcification in the wall. In this report, we describe the contrast-enhanced spectral mammography (CESM), ultrasonography, and computed tomography findings and provide a reference for the diagnosis of EICs. To the best of our knowledge, this is the first report of the CESM findings of an EIC. Our case illustrates that CESM has excellent performance similar to that of magnetic resonance imaging and is much more effective than conventional digital mammography. Additionally, our case indicates that precise correlation of CESM with ultrasonography findings contributes to the diagnosis of EICs. This rare case with multiple imaging findings will increase the awareness of EICs in the breast parenchyma.

Dual-energy CT quantitative parameters for the differentiation of benign from malignant lesions and the prediction of histopathological and molecular subtypes in breast cancer

Background

Dual-energy computed tomography (DECT) is widely used to characterize and differentiate tumors. However, data regarding its diagnostic performance for the characterization of breast tumors are limited. In this study, we assessed the diagnostic performance of quantitative parameters derived from DECT in differentiating benign from malignant lesions and predicting histopathological and molecular subtypes in patients with breast cancer.

Methods

Dual-phase contrast-enhanced DECT of the thorax was performed on participants with breast tumors. Conventional CT attenuation and DECT quantitative parameters, including normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit curve (λ_Hu), and normalized effective atomic number (nZ_eff), were obtained and compared between benign and malignant lesions, invasive non-special carcinoma, and ductal carcinoma in situ (DCIS), and among the four molecular subtypes of breast cancer. The diagnostic performance of the quantitative parameters was analyzed using receiver operating characteristic (ROC) curves.

Results

This study included 130 participants with 161 breast lesions (44 benign and 117 malignant). In the arterial and venous phase, NICs, λ_Hu, nZ_eff, and attenuation were higher in malignant lesions than benign lesions (all P<0.001). The venous phase λ_Hu had the best differential diagnostic capability, with an area under the curve (AUC) of 0.90, a sensitivity of 84.1% (37 of 44), a specificity of 86.3% (101 of 117), and an accuracy of 85.7% (138 of 161). The NICs in the arterial and venous phases were higher in invasive non-special carcinoma than DCIS (both P<0.001). In terms of diagnostic performance, NIC in the venous phase had an AUC of 0.77, a sensitivity of 75.0% (12 of 16), a specificity of 81.2% (82 of 101), and an accuracy of 80.3% (94 of 117). The luminal A subtype produced a lower venous phase NIC, and arterial and venous phase nZ_eff than the non-luminal A subtype (AUC of 0.91 for the combination of these three parameters).

Conclusions

Dual-energy CT quantitative parameters are a feasible and valuable noninvasive means of differentiating between benign and malignant lesions, and predicting histopathological and molecular subtypes in patients with breast cancer.

Breast cancer: comparison of quantitative dual-layer spectral CT and axillary ultrasonography for preoperative diagnosis of metastatic axillary lymph nodes

Background

Our aim was to compare the diagnostic performance of quantitative dual-layer spectral computed tomography (DLSCT) and axillary ultrasound (US) for diagnosing lymph node metastases in breast cancer patients.

Methods

DLSCT and axillary US were prospectively performed in 70 needle biopsy-verified breast cancer patients. Histopathology and imaging data were available for evaluation in 36 axillae from 34 patients. In each patient, ipsilateral, contralateral, and inguinal lymph nodes (LNs) were semiautomatically segmented, and iodine density, spectral slope, Z effective, virtual non-contrast (VNC), conventional CT HU values, and Δ contrast enhancement (ΔCE, conventional CT HU minus VNC) were measured. Using histopathology as reference, the diagnostic performance of DLSCT and axillary US was compared.

Results

Of 36 axillae, 23 had metastatic lymph nodes. Compared with non-metastatic LNs, metastatic LNs had significantly different iodine density (p = 0.021), spectral slope (p < 0.001), Z effective (p < 0.001), conventional CT HU values (p < 0.01), and ΔCE (p < 0.01). All DLSCT parameters were significantly different between arterial phase and portal-venous phase (p < 0.001) except for VNC (p = 0.092). ΔCE had the highest diagnostic performance (sensitivity 0.79, specificity 0.92, positive predictive value 0.95, negative predictive value 0.69) with a significantly increased sensitivity compared with conventional CT HU (p = 0.027). There were no significant differences between ΔCE and axillary US for sensitivity (p = 1.000) or specificity (p = 0.320).

Conclusions

DLSCT is a promising quantitative technique for evaluating LN metastases and could potentially reduce the need for sentinel LN biopsy.

Dual-energy CT quantitative parameters for evaluating Immunohistochemical biomarkers of invasive breast cancer

Background

Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki67 are the most useful immunohistochemical biomarkers of invasive breast cancer. The purpose of this study is to investigate the possibility of quantitative parameters derived from dual-energy CT (DECT) to discriminate immunohistochemical biomarkers of invasive breast cancer.

Methods

This prospective study enrolled 120 patients with invasive breast cancer who underwent preoperative contrast-enhanced DECT for staging purposes from June 2019 to January 2020. DECT quantitative parameters, including normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit curve (λ_Hu), and the normalized effective atomic number (nZ_eff), were obtained from reconstructed images. DECT quantitative parameters were compared with the expression status, and the correlations with the value of immunohistochemical biomarkers were evaluated. Inter-observer reproducibility analysis was performed to assess the measurement reproducibility of quantitative parameters. The diagnostic performance of the quantitative parameters was analyzed by receiver operating characteristic curve.

Results

The ER-negative group tended to display higher venous phase NIC and nZ_eff compared with the ER-positive group (individually, p = 0.003, 0.011; area under the curve [AUC] of 0.65, 0.60). The PR-negative group demonstrated higher arterial and venous phase NIC compared with the PR-positive group (individually, p = 0.022, 0.005; AUC of 0.63, 0.65). NIC was correlated negatively with the value of ER and PR expression (r = − 0.175 ~ − 0.265, p = 0.002 ~ 0.042). The HER2-positive group tended to display higher venous phase nZ_eff than the HER2-negative group (p = 0.022; AUC of 0.59). The Ki67 high-proliferation group demonstrated higher arterial phase, venous phase NIC and nZ_eff than the Ki67 low-proliferation group (p < 0.001 ~ 0.005; AUC of 0.67 ~ 0.75). Both the NIC and nZ_eff were correlated positively with the value of Ki67 (r = 0.240 ~ 0.490, p < 0.001 ~ 0.014).

Conclusions

NIC and nZ_eff derived from DECT could be used to discriminate expression status and may associate with the value of immunohistochemical biomarkers of invasive breast cancer.

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.

Utility of 70-kV single-energy CT in depicting the extent of breast cancer for preoperative planning

PURPOSE

To evaluate the detectability of breast cancer and visibility of the tumor extent using 70-kV single-energy contrast-enhanced (CE) breast computed tomography (70-kV CECT) compared with CE breast magnetic resonance imaging (CEMR).

METHODS

Between 2013 and 2015, 110 patients with 112 breast cancer lesions who underwent breast surgery after undergoing both 70-kV CECT and CEMR were enrolled. The major axis lengths of the breast lesion were measured and compared with the pathologically determined major axes. Agreement in the measured major axes was evaluated using the intra-class correlation coefficient (ICC).

RESULTS

Both 70-kV CECT and CEMR depicted all breast cancer lesions. The mean major axis was 3.0 (95% confidence interval [CI], 2.5-3.4) cm on CECT and 2.9 (2.6-3.3) cm on CEMR. The mean differences between the pathologically and radiologically measured major axes on 70-kV CECT and CEMR were 0.9 (0.7-1.1) and 1.0 (0.8-1.2) cm, respectively. The accuracy of the radiological major axes compared with the pathological major axes was 82.1% and 80.4% on CECT and CEMR, respectively (p = 0.81). The major axes on the two modalities demonstrated moderate agreement (ICC = 0.69, 95% CI 0.58-0.77). Pathologically and radiologically measured major axes on 70-kV CECT and CEMR demonstrated excellent agreement (ICC = 0.91, 95% CI 0.93-0.96).

CONCLUSIONS

Low-tube voltage (70-kV) CECT is the preferred modality to identify breast cancer lesions and tumor extent for preoperative planning because it has a similar diagnostic ability to CEMR and can be performed in the supine position.

Multidetector Computed Tomography with Dedicated Protocol for Breast Cancer Locoregional Staging: Feasibility Study

BACKGROUND

The aim of this study was to demonstrate the feasibility of performing multidetector computed tomography (MDCT) with a dedicated protocol for locoregional staging in breast cancer patients.

METHODS

This prospective single-center study included newly diagnosed breast cancer patients submitted to contrast-enhanced chest MDCT and breast magnetic resonance imaging (MRI). MDCT was performed in prone position and using subtraction techniques. Fleiss' Kappa coefficient (K) and intraclass correlation coefficient (ICC) were used to assess agreement between MRI, MDCT, and pathology, when available.

RESULTS

Thirty-three patients were included (mean age: 47 years). Breast MRI and MDCT showed at least substantial agreement for evaluation of tumor extension (k = 0.674), presence of multifocality (k = 0.669), multicentricity (k = 0.857), nipple invasion (k = 1.000), skin invasion (k = 0.872), and suspicious level I axillary lymph nodes (k = 0.613). MDCT showed higher number of suspicious axillary lymph nodes than MRI, especially on levels II and III. Both methods had similar correlation with tumor size (MRI ICC: 0.807; p = 0.008 vs. MDCT ICC: 0.750; p = 0.020) and T staging (k = 0.699) on pathology.

CONCLUSIONS

MDCT with dedicated breast protocol is feasible and showed substantial agreement with MRI features in stage II or III breast cancer patients. This method could potentially allow one-step locoregional and systemic staging, reducing costs and improving logistics for these patients.