A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.

OBJECTIVE: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal growth factor receptor 2 (HER2) and to identify luminal histotype of the breast cancer. METHODS: From four Italian centers were recruited 180 malignant lesions and 68 benign lesions. However, only the malignant lesions were considered for the analysis. All patients underwent contrast-enhanced mammography in cranium caudal (CC) and medium lateral oblique (MLO) view. Considering histological findings as the ground truth, four outcomes were considered: (1) G1 + G2 vs. G3; (2) HER2 + vs. HER2 - ; (3) HR + vs. HR - ; and (4) non-luminal vs. luminal A or HR + /HER2- and luminal B or HR + /HER2 + . For multivariate analysis feature selection, balancing techniques and patter recognition approaches were considered. RESULTS: The univariate findings showed that the diagnostic performance is low for each outcome, while the results of the multivariate analysis showed that better performances can be obtained. In the HER2 + detection, the best performance (73% of accuracy and AUC = 0.77) was obtained using a linear regression model (LRM) with 12 features extracted by MLO view. In the HR + detection, the best performance (77% of accuracy and AUC = 0.80) was obtained using a LRM with 14 features extracted by MLO view. In grading classification, the best performance was obtained by a decision tree trained with three predictors extracted by MLO view reaching an accuracy of 82% on validation set. In the luminal versus non-luminal histotype classification, the best performance was obtained by a bagged tree trained with 15 predictors extracted by CC view reaching an accuracy of 94% on validation set. CONCLUSIONS: The results suggest that radiomics analysis can be effectively applied to design a tool to support physician decision making in breast cancer classification. In particular, the classification of luminal versus non-luminal histotypes can be performed with high accuracy.

Preoperative localisation of nonpalpable breast lesions using magnetic markers in a tertiary cancer centre.

BACKGROUND: We retrospectively evaluated safety and performance of magnetic seed localisation of nonpalpable breast lesions. METHODS: We reviewed records of patients with nonpalpable breast lesions preoperative localised by placing magnetic Magseed® marker between February 2019 and December 2020. During surgery, Sentimag® magnetic probe was used to localise the marker and guide surgery. Safety, lesion identification and excision with tumour with free margins and re-excision rate were assessed. RESULTS: A total of 77 Magseed® devices were placed into the breasts of 73 patients, 44 under ultrasound and 33 under stereotactic guidance (4 bilateral). All devices were retrieved as were the target lesions. Magnetic marker placement was successful in all cases without any adverse event. Intraoperative identification and excision of the localised lesion were successful in 77 of 77 of cases (100%). In three cases (all of them calcifications with the seed placed under stereotactic guidance), the seed did not reach the exact target position of the biopsy clip; thus, larger excision was needed, with localisation failure attributed to incorrect clip insertion (n = 1) or to clip dislocation (n = 2). Migration of the marker was negligible in all patients. Complete excision after the initial procedure with at least 1-mm disease-free margins was obtained in 74 out of 77 (96.1%) lesions. The re-excision rate was 3 out of 77 (4%). CONCLUSIONS: Magnetic marker localisation for nonpalpable breast lesions was safe, reliable, and effective in terms of lesion identification, excision with tumour-free margins and re-excision rate.

Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.

Purpose:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures were performed. Methods: Fifty-four patients with 79 histo-pathologically proven breast lesions (48 malignant lesions and 31 benign lesions) underwent both CEM and DCE-MRI. The lesions were retrospectively analyzed with radiomic and artificial intelligence approaches. Forty-eight textural metrics were extracted, and univariate and multivariate analyses were performed: non-parametric statistical test, receiver operating characteristic (ROC) and machine learning classifiers. Results: Considering the single metrics extracted from CEM, the best predictors were KURTOSIS (area under ROC curve (AUC) = 0.71) and SKEWNESS (AUC = 0.71) calculated on late MLO view. Considering the features calculated from DCE-MRI, the best predictors were RANGE (AUC = 0.72), ENERGY (AUC = 0.72), ENTROPY (AUC = 0.70) and GLN (gray-level nonuniformity) of the gray-level run-length matrix (AUC = 0.72). Considering the analysis with classifiers and an unbalanced dataset, no significant results were obtained. After the balancing and feature selection procedures, higher values of accuracy, specificity and AUC were reached. The best performance was obtained considering 18 robust features among all metrics derived from CEM and DCE-MRI, using a linear discriminant analysis (accuracy of 0.84 and AUC = 0.88). Conclusions: Classifiers, adjusted with adaptive synthetic sampling and feature selection, allowed for increased diagnostic performance of CEM and DCE-MRI in the differentiation between benign and malignant lesions.

Not only lymphadenopathy: case of chest lymphangitis assessed with MRI after COVID 19 vaccine.

BACKGROUND: To date, no paper reports cases of lymphangitis after COVID 19 vaccination. We present a case of lymphangitis after vaccination from COVID 19, in a patient with colorectal liver metastases. METHODS: We described the case of a 56-year-old woman with history of a surgical resection of colorectal cancer and liver metastases, without any kind of drug therapy for about a month. In addition, a recent administration (2 days ago) of Spikevax (mRNA-1273, Moderna vaccine), as a booster dose, on the right arm was reported. RESULTS: The magnetic resonance (MR) examination showed the effects of the previous surgical resection and five new hepatic metastases, located in the VIII, VI, V, IV and II hepatic segments. As an accessory finding the presence of lymphadenopathy in the axillary area and lymphangitis of the right breast and chest were identified. The computed tomography scan performed a week earlier, and re-evaluated in light of the MR data, did not identify the presence of lymphadenopathy in the axillary area and lymphangitis signs. CONCLUSIONS: Lymphangitis could occur after COVID 19 vaccine and it is important to know this data to avoid alarmism in patients and clinicians and economic waste linked to the execution of various radiological investigations for the search for a tumour that probably does not exist. TRIAL REGISTRATION: Not applicable.

Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI, and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience.

PURPOSE: To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. METHODS: Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. RESULTS: R2* and D had a significant negative correlation (-0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the 'poor' diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. CONCLUSIONS: Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy, and vacuum assisted breast biopsy for benign lesions. In total, 104 samples of 80 patients were analyzed. Furthermore, 48 textural parameters were extracted by manually segmenting regions of interest. Univariate and multivariate approaches were performed: non-parametric Wilcoxon-Mann-Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), artificial neural network (NNET), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance considering the CC view (accuracy (ACC) = 0.75; AUC = 0.82) was reached with a DT trained with leave-one-out cross-variation (LOOCV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of three robust textural features (MAD, VARIANCE, and LRLGE). The best performance (ACC = 0.77; AUC = 0.83) considering the early-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of ten robust features (MEAN, MAD, RANGE, IQR, VARIANCE, CORRELATION, RLV, COARSNESS, BUSYNESS, and STRENGTH). The best performance (ACC = 0.73; AUC = 0.82) considering the late-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of eleven robust features (MODE, MEDIAN, RANGE, RLN, LRLGE, RLV, LZLGE, GLV_GLSZM, ZSV, COARSNESS, and BUSYNESS). Multivariate analyses using pattern recognition approaches, considering 144 textural features extracted from all three mammographic projections (CC, early MLO, and late MLO), optimized by adaptive synthetic sampling and feature selection operations obtained the best results (ACC = 0.87; AUC = 0.90) and showed the best performance in the discrimination of benign and malignant lesions.

Kinase-inhibitors for iodine-refractory differentiated thyroid cancer: still far from a structured therapeutic algorithm.

The kinase-inhibitors (KIs) sorafenib and lenvatinib demonstrated efficacy in iodine-refractory DTC upon phase III studies. However, evidence allowing a punctual balance of benefits and risks is poor. Furthermore, the lack of a direct comparison hampers to establish the proper sequence of administration. However, some insights may provided: a) indirect comparison between phase III trials showed milder toxicity for sorafenib, which should be preferred in case of cardiovascular comorbidities; b) prospective evidence of efficacy in KIs pre-treated patients is available only for lenvatinib, which should be used as second-line. Promising activity was found for the majority of other tested KIs, but no placebo-controlled trials are available. Emerging, but still early, frontiers include the restoration of iodine-sensitivity and the selective activity on pathogenic mutations. In conclusion, the use of KIs in iodine-refractory DTC is far from a structured therapeutic algorithm.

Evaluation of average glandular dose and investigation of the relationship with compressed breast thickness in dual energy contrast enhanced digital mammography and digital breast tomosynthesis.

PURPOSE: To quantitatively assess the dose of Dual energy contrast enhanced digital mammography (CEDM) and digital breast tomosynthesis (DBT) and to investigate the relationship between average absorbed glandular dose (AGD), compressed breast thickness (CBT) and compression force (CF). MATERIALS AND METHODS: All CEDM and DBT examinations were performed in cranio-caudal (CC) and medio-lateral oblique (MLO) view. Exposure parameters of 135 mammographic procedures that using AEC (automatic exposure control) mode were recorded. AGDs were calculated. Kruskal Wallis test was performed. RESULTS: CBT population ranged from 23 to 94 mm with a thickness median value of 52 mm in CC view and of 57 mm in MLO views. CEDM AGD median value was significatively lower than DBT AGD in each views (p << 0.01). AGD showed a positive correlation and linear regression with CBT for both CEDM and DBT while CF did not show a correlation and linear regression with AGD. The highest values were found for MLO view: R2 of 0.74 for CEDM and R2 of 0.61 for DBT. Kruskal Wallis test shows that there was a difference statistically significant between AGD values of CEDM and DBT in CC view respect to MLO views (p < 0.01). CONCLUSIONS: Dose values of both techniques meet the recommendations for maximum dose in mammography. The results of the present study indicated that there was significant difference between AGD for CEDM and DBT exposure in different views (AGD in CC views had the lowest value) and that CBT could influence the AGD while CF was not correlated to AGD.

Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification.

To compare diagnostic performance of contrast-enhanced dual-energy digital mammography (CEDM) and digital breast tomosynthesis (DBT) alone and in combination compared to 2D digital mammography (MX) and dynamic contrast-enhanced MRI (DCE-MRI) in women with breast lesions. We enrolled 100 consecutive patients with breast lesions (BIRADS 3-5 at imaging or clinically suspicious). CEDM, DBT, and DCE-MRI 2D were acquired. Synthetized MX was obtained by DBT. A total of 134 lesions were investigated on 111 breasts of 100 enrolled patients: 53 were histopathologically proven as benign and 81 as malignant. Nonparametric statistics and receiver operating characteristic (ROC) curve were performed. Two-dimensional synthetized MX showed an area under ROC curve (AUC) of 0.764 (sensitivity 65%, specificity 80%), while AUC was of 0.845 (sensitivity 80%, specificity 82%) for DBT, of 0.879 (sensitivity 82%, specificity 80%) for CEDM, and of 0.892 (sensitivity 91%, specificity 84%) for CE-MRI. DCE-MRI determined an AUC of 0.934 (sensitivity 96%, specificity 88%). Combined CEDM with DBT findings, we obtained an AUC of 0.890 (sensitivity 89%, specificity 74%). A difference statistically significant was observed only between DCE-MRI and CEDM (P = .03). DBT, CEDM, CEDM combined to tomosynthesis, and DCE-MRI had a high ability to identify multifocal and bilateral lesions with a detection rate of 77%, 85%, 91%, and 95% respectively, while 2D synthetized MX had a detection rate for multifocal lesions of 56%. DBT and CEDM have superior diagnostic accuracy of 2D synthetized MX to identify and classify breast lesions, and CEDM combined with DBT has better diagnostic performance compared with DBT alone. The best results in terms of diagnostic performance were obtained by DCE-MRI. Dynamic information obtained by time-intensity curve including entire phase of contrast agent uptake allows a better detection and classification of breast lesions.

Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS.

PURPOSE: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. MATERIALS AND METHODS: In this retrospective study, we assessed 62 patients (14 women-48 men; mean age, 63 years; range 38-80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. RESULTS: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. CONCLUSION: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.

Optical imaging of the breast: evaluation of deoxyhemoglobin concentration alteration in 166 patients with suspicious breast lesions.

BACKGROUND: We investigated the performance of optical imaging evaluating deoxyhemoglobin concentration alteration (DeHCA) in breast tissues. METHODS: We enrolled all consecutive patients from January 2015 to October 2016 with clinically suspicious and/or BI-RADS grade 3-5 lesions at mammography or ultrasound (US). Patients underwent optical imaging (ComfortScan) to evaluate for DeHCA. The reference standard was pathology from a surgical specimen for malignant lesions, pathology from a surgical specimen or core needle biopsy for benign lesions, and negative follow-up for contralateral negative breasts. Non-parametric statistics, receiver operating characteristic, and linear discrimination analyses were performed. RESULTS: Of 334 enrolled patients, 168 (50%) were excluded for technical problems and 166 (50%) (median age 52 years) were analyzed totaling 331 breasts and 176 lesions. Of these, 75 were benign (median size 19 mm) and 101 malignant (median size 20 mm). The median DeHCA score in malignant lesions (0.95, interquartile range [IQR] 1.00-0.87) was higher (p < 0.001) than in benign lesions (0.80, IQR 0.95-0.70). Using the optimal cutoff (0.85), DeHCA score was less accurate than mammography, US, and their combination, with 78% sensitivity, 52% specificity, 40% positive predictive value (PPV), and 85% negative predictive value (NPV); using a 0.8 cutoff, sensitivity reached 93% and NPV 91%, but specificity fell to 32% and PPV to 37%. The accuracy of DeHCA score linearly combined with mammography or US was higher than that of DeHCA score alone (p < 0.001) and not significantly higher than that of mammography or US alone. CONCLUSIONS: DeHCA score was significantly higher in malignant than in benign lesions, but its accuracy was significantly lower than that of mammography or US. Future refinements are needed.

Added Value of Breast MRI for Preoperative Diagnosis of Ductal Carcinoma In Situ: Diagnostic Performance on 362 Patients.

INTRODUCTION: The purpose of this study was to evaluate the added value of breast magnetic resonance imaging (MRI) in preoperative diagnosis of ductal carcinoma in situ (DCIS). We reviewed our institution database of 3499 consecutive patients treated for breast cancer. PATIENTS AND METHODS: A total of 362 patients with histologically proven DCIS were selected from the institutional database. Of these, 245 (67.7%) preoperatively underwent conventional imaging (CI) (mammography/ultrasonography) (CI group), and 117 (32.3%) underwent CI and dynamic MRI (CI + MRI group). The pathology of surgical specimens served as a reference standard. The Mann-Whitney U, χ2 test, and Spearman correlation coefficient were performed. RESULTS: The CI + MRI group showed a sensitivity of 98.5% with an increase of 10.1% compared with the CI group to detect pure DCIS. Dynamic MRI identified 19.7% (n = 13) additional pure DCIS compared with CI. In the CI + MRI group, a single (1.5%) false negative was reported, whereas in the CI group, 11 (11.6%) false negatives were reported. Moreover, the CI + MRI group showed a sensitivity of 98.0% to detect DCIS + small invasive component. In this group, dynamic MRI identified 21.6% (n = 11) additional DCIS and a single (2.0%) false negative compared with the CI group, whereas in the CI group, 7 (4.7%) false negatives were reported. MRI and histopathologically measured lesion sizes, Breast Imaging Reporting and Data System MRI assessment categories, and enhancement signal intensity curve types showed a significant correlation. The MRI detection rate of DCIS increased significantly with increasing nuclear grade. CONCLUSIONS: Preoperative breast MRI showed a better accuracy then CI in preoperative diagnosis for both pure DCIS and DCIS + small invasive component with a precise assessment of lesion size. This can provide a more appropriate management of DCIS patients.

Breast Contrast Enhanced MR Imaging: Semi-Automatic Detection of Vascular Map and Predominant Feeding Vessel.

PURPOSE: To obtain breast vascular map and to assess correlation between predominant feeding vessel and tumor location with a semi-automatic method compared to conventional radiologic reading. METHODS: 148 malignant and 75 benign breast lesions were included. All patients underwent bilateral MR imaging. Written informed consent was obtained from the patients before MRI. The local ethics committee granted approval for this study. Semi-automatic breast vascular map and predominant vessel detection was performed on MRI, for each patient. Semi-automatic detection (depending on grey levels threshold manually chosen by radiologist) was compared with results of two expert radiologists; inter-observer variability and reliability of semi-automatic approach were assessed. RESULTS: Anatomic analysis of breast lesions revealed that 20% of patients had masses in internal half, 50% in external half and the 30% in subareolar/central area. As regards the 44 tumors in internal half, based on radiologic consensus, 40 demonstrated a predominant feeding vessel (61% were supplied by internal thoracic vessels, 14% by lateral thoracic vessels, 16% by both thoracic vessels and 9% had no predominant feeding vessel-p<0.01), based on semi-automatic detection, 38 tumors demonstrated a predominant feeding vessel (66% were supplied by internal thoracic vessels, 11% by lateral thoracic vessels, 9% by both thoracic vessels and 14% had no predominant feeding vessel-p<0.01). As regards the 111 tumors in external half, based on radiologic consensus, 91 demonstrated a predominant feeding vessel (25% were supplied by internal thoracic vessels, 39% by lateral thoracic vessels, 18% by both thoracic vessels and 18% had no predominant feeding vessel-p<0.01), based on semi-automatic detection, 94 demonstrated a predominant feeding vessel (27% were supplied by internal thoracic vessels, 45% by lateral thoracic vessels, 4% by both thoracic vessels and 24% had no predominant feeding vessel-p<0.01). An excellent agreement between two radiologic assessments (k = 0.81) and between radiologic consensus and semi-automatic assessment (k = 0.80) was found to identify origin of predominant feeding vessel. An excellent reliability for semi-automatic assessment (Cronbach's alpha = 0.96) was reported. CONCLUSIONS: Predominant feeding vessel location was correlated with breast lesion location: internal thoracic artery supplied the highest proportion of breasts with tumor in internal half and lateral thoracic artery supplied the highest proportion of breasts with lateral tumor.

Contrast-Enhanced Ultrasound in the Assessment of Patients with Indeterminate Abdominal Findings at Positron Emission Tomography Imaging.

Widespread use of fluorodeoxyglucose-positron emission tomography (PET) in cancer imaging may result in a number of indeterminate and false-positive findings. We investigated the role of contrast-enhanced ultrasound (CEUS) as a second-level option after inconclusive PET. We reviewed CEUS images acquired over 4 y, selecting the examinations performed specifically to better assess an unclear PET image. Final diagnosis was confirmed by biopsy, surgery, further imaging or follow-up. Seventy CEUS examinations were performed after a PET scan (44 PET examinations, 19 PET-computer tomography [CT] examinations and 7 PET-CECT examinations). The target organ was the liver in 54 cases, spleen in 12, gallbladder in 2 and pancreas and kidney in one each. In 6 of 70 cases, CEUS was performed because of a negative PET (no uptake) despite an abnormal finding on the CT images of the PET-CT study; CEUS allowed a correct diagnosis in all of these. In 20 of 70 cases, the PET findings were categorized as indeterminate and non-specific (non-specific fluorodeoxyglucose uptake in PET report with no standardized uptake value given); CEUS reached a correct diagnosis in 19 of the 20 cases with one false negative. In 34 of 70 cases, PET was indeterminate, but specific (fluorodeoxyglucose uptake with a standardized uptake value provided); CEUS reached a correct diagnosis in 30 of these 34 cases. In 10 of 70 cases, PET was categorized as determinate but to be investigated because of discrepancy with clinical or imaging findings; CEUS a definitive diagnosis in 9 of 10 cases. CEUS proved to be effective option in the assessment of cancer patients with indeterminate PET findings.

Integrating contrast-enhanced sonography in the follow-up algorithm of hepatocellular carcinoma treated with radiofrequency ablation: single cancer center experience.

BACKGROUND: Hepatocellular carcinoma (HCC) patients treated with percutaneous ablation require close follow-up for early detecting and treating tumor recurrence. PURPOSE: To illustrate our single-center prospective experience on using contrast-enhanced ultrasound (CEUS) as a follow-up tool alternated with computed tomography (CT). MATERIAL AND METHODS: In a 7-year period 588 patients with one to three HCCs were treated with radiofrequency ablation (alone or combined with ethanol injection). Patients with completely ablated tumors at 1-month CT scan were followed up serially, using alternated CEUS (one microbubbles injection per lobe) and CT every 3 months for 2 years. In few cases magnetic resonance imaging (MRI) was employed instead of or in addition to CT. The following patterns of recurrence were considered: A, enhancing tissue within the lesion; B, enhancing tissue adherent to the lesion; C, enhancing tissue within the same liver segment of the treated nodule; and D, enhancing tissue within a different segment. Patients with positive CEUS underwent confirmatory CT/MRI (standard reference). RESULTS: Median follow-up was 19 months. There were 221 recurrences. Three pattern A recurrences (2 detected by CEUS and 1 by CT), 86 pattern B recurrences (44 detected by CEUS and 42 by CT), 70 pattern C recurrences (32 detected by CEUS and 38 by CT), and 62 pattern D recurrences (23 detected by CEUS and 39 by CT). CT detected additional nodules in 16/101 patients with positive CEUS. CONCLUSION: CEUS follow-up of HCC patients after ablation is feasible. Since 72% recurrences develop in the same segment of the necrotic nodule, CEUS proves to be effective despite the minor visualization of the entire liver during the arterial phase when compared to CT and MRI. Including CEUS in patient follow-up may reduce the number of CT and MRI examinations.

Surgical impact of preoperative breast MRI in women below 40 years of age.

Our aim was to evaluate the surgical impact of preoperative MRI in young patients. We reviewed a single-institution database of 283 consecutive patients below 40 years of age and who were treated for breast cancer. Thirty-seven (13 %) patients who received neoadjuvant chemotherapy were excluded. The remaining 246 patients included 124 (50 %) who preoperatively underwent conventional imaging (CI), i.e., mammography/ultrasonography (CI-group), and 122 (50 %) who underwent CI and dynamic MRI (CI + MRI-group). Pathology of surgical specimens served as a reference standard. Mann-Whitney, χ (2), and McNemar statistics were used. There were no significant differences between groups in terms of age, tumor pathologic subtype, stage, receptor, or nodal status. The mastectomy rate was 111/246 (45 %) overall but was significantly different between groups (46/124, 37 %, for the CI group and 65/122, 53 %, for the CI + MRI group; p = 0.011). Of 122 CI + MRI patients, 46 (38 %) would have undergone mastectomy due to CI alone, while MRI determined 19 additional mastectomies, increasing the mastectomy rate from 38 % to 53 % (p < 0.001). The number of patients with multifocal, multicentric, synchronous, or bilateral cancers was significantly different between groups (10/124, 8 %, for the CI group and 33/122, 27 %, for the CI + MRI group; p < 0.001). In the CI + MRI group, multifocal, multicentric, or synchronous bilateral cancers were detected with mammography in 5/33 (15 %) patients, with ultrasonography in 15/33 (45 %) patients, and with MRI in 32/33 (97 %) patients (p < 0.005). Two mastectomies were due to false positives at both conventional tests in the CI group (2/124, 1.6 %) and two mastectomies were due to MRI false positives in the CI + MRI group (2/122, 1.6 %). In conclusion, breast cancer in young patients was treated with mastectomy in 37-38 % of cases on the basis of CI only and in these patients MRI was more sensitive than CI for multifocal, multicentric, or synchronous bilateral cancers, resulting in an additional mastectomy rate of 15 %. A low probability of inappropriate imaging-based decision-making for mastectomy exists for both CI alone and for CI + MRI, making presurgical needle biopsy mandatory for findings that suggest a need for mastectomy.

Sonography for locoregional staging and follow-up of cutaneous melanoma: how we do it.

OBJECTIVE: Sonography is being used with increasing frequency in the assessment of locoregional tumor spread in patients with melanoma. Nevertheless, to maximize its practical impact, sonography should be performed with state-of-the-art equipment, by specifically trained operators, and using a careful exploration technique and well-defined diagnostic criteria. In this "how I do it"-type article, we illustrate our practical approach to sonography of cutaneous melanoma. METHODS: We first illustrate the basic and advanced technical requirements; then we describe our exploration methods and our image interpretation approach; and finally, we report on our use of sonography as a guidance tool for interventional procedures. Special emphasis is given to methodological and interpretative clues, tricks, and pitfalls. RESULTS: Sonography can be used in the initial staging of patients with melanoma, particularly in the screening of patients scheduled for a sentinel lymph node biopsy procedure. Additionally, sonography can be used during patient follow-up to detect locoregional recurrence earlier than palpation. CONCLUSIONS: Sonography plays a growing role in the assessment of the superficial spread of melanoma. Nevertheless, state-of-the-art equipment and careful exploration by trained operators are necessary.

Can hepatocellular cancer screening increase the proportion of long-term survivors?

BACKGROUND/AIMS: Historically, only 10% of hepatocellular cancer (HCC) patients are diagnosed with early stage, potentially curable disease. We prospectively screened chronic hepatitis virus-infected patients to determine 1) the proportion diagnosed with potentially curable HCC, and 2) survival following curative therapy. METHODOLOGY: The study included 5670 chronic hepatitis B (1,077, 19.0%), C (4,196, 74.0%), or both (397, 7.0%)-infected patients enrolled in a prospective screening program. Screening was every 6 months with serum alpha-fetoprotein (AFP) measurement and ultrasonography. Curative treatments included liver transplantation, resection, RFA, and/or ethanol injection. RESULTS: HCC was diagnosed in 464 (8.2%) patients. Of 1006 cirrhotic patients, 462 (45.9%) developed HCC. Curative treatment was possible in 319 (68.7%). The 2- and 5-year overall survival rates in the curative treatment group were 65% and 28%, respectively, compared to 10% and 0% in the advanced disease group (p < 0.001). CONCLUSION: Prospective screening of patients at high risk to develop HCC increases the proportion diagnosed with potentially curable disease. This may result in an increase of the number of long-term survivors. A screening strategy should focus on those patients with chronic hepatitis B or C virus infection that has progressed to cirrhosis since more than 40% of these patients will develop HCC.

Transient hepatic echogenicity difference on contrast-enhanced ultrasonography: sonographic sign and pitfall.

OBJECTIVE: The purpose of this study was to report and analyze a new contrast-enhanced ultrasonographic (CEUS) imaging finding, the transient hepatic echogenicity difference due to perfusion changes, using computed tomography (CT) as a reference standard. METHODS: We retrospectively investigated the records of patients evaluated in a 2-year period, selecting those who had undergone both CT and CEUS within 15 days, who had CT evidence of a perfusion abnormality, and who had had a CEUS study that included the malperfused parenchymal area. RESULTS: There were 30 patients with 44 hepatic perfusion changes on CT scans (28 around liver focal lesions and 16 unrelated to focal lesions). Retrospectively, CEUS allowed recognition of 21 of 28 perifocal transient hepatic attenuation differences (THADs), 6 of 10 subsegmental THADs, 2 of 3 segmental THADs, and 1 of 3 lobar THADs. Only some of these abnormalities had been identified at the original CEUS examinations: 0 of 3 lobar THADs, 1 of 3 segmental THADs, 2 of 10 subsegmental THADs, and 16 of 28 perifocal THADs. CONCLUSIONS: Contrast-enhanced ultrasonography can show hepatic perfusion abnormalities similar to those well known from CT literature, although with a lower sensitivity. Knowledge of this transient hepatic echogenicity difference phenomenon may be relevant for avoiding incorrect image interpretation or incorrect tumor size measurement and for eventually identifying occult vascular disorders such as venous thrombosis or fistulas.