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The existing standard for axillary lymph node staging in breast cancer patients with a clinically and radiologically normal axilla is sentinel lymph node biopsy with a radioisotope and blue dye (dual technique). The dependence on radioisotopes means that uptake of the procedure is limited to only about 60% of eligible patients in developed countries and is negligible elsewhere. We did a systematic review to assess three techniques for sentinel lymph node biopsy that are not radioisotope dependent or that refine the existing method: indocyanine green fluorescence, contrast-enhanced ultrasound using microbubbles, and superparamagnetic iron oxide nanoparticles. Our systematic review suggested that these new methods for sentinel lymph node biopsy have clinical potential but give high levels of false-negative results. We could not identify any technique that challenged the existing standard procedure. Further assessment of these techniques against the standard dual technique in randomised trials is needed.

PurposeCurrently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses.MethodsWith institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution’s pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes.ResultsWe analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8–14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0–13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%.ConclusionsThe best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.

IntroductionSince FDA approval for contrast-enhanced ultrasound (CEUS), clinical applications have increased to include diagnostic imaging of hepatic, renal, and other abdominal lesions. The modality has also demonstrated utility in certain image-guided procedures. Intravascular ultrasound contrast agents use microbubbles to improve visibility of solid tumors. Lesions not well seen on grayscale or Doppler ultrasound may become amenable to CEUS-guided biopsy or ablation.Materials and MethodsThis pictorial essay provides eleven examples to illustrate the current use of CEUS in a variety of abdominal image-guided procedures. Hepatic, renal, peritoneal, and soft tissue cases are presented.ConclusionCEUS can improve visualization and targeting in abdominal image-guided procedures, without nephrotoxicity or radiation exposure.

PurposePseudocirrhosis has been demonstrated to mimic cirrhosis radiographically, but studies evaluating the pathophysiology and clinical features are lacking. To better understand the incidence, risk factors, clinical course, and etiology of pseudocirrhosis, we performed a retrospective analysis of consecutively treated patients with metastatic breast cancer (MBC).MethodsOf 374 patients treated for MBC from 2006 to 2012, 199 had imaging available for review. One radiologist evaluated computed tomography scans for evidence of pseudocirrhosis. Features of groups with and without pseudocirrhosis were compared by Kaplan–Meier product-limit survival estimates and log-rank tests. Wilcoxon Rank-Sum testing evaluated if patients more heavily treated were more likely to develop pseudocirrhosis. Univariate and multivariate Cox proportional hazard models investigated factors associated with mortality.ResultsPseudocirrhosis developed in 37 of 199 patients (19%). Of the patients with liver metastases, 55% developed pseudocirrhosis. Liver metastases were demonstrated in 100% of patients with pseudocirrhosis. Survival in the subset with liver metastases favored those without pseudocirrhosis, 189 versus 69 months (p = 0.01). The number of systemic regimens received were higher in patients with pseudocirrhosis (p = 0.01). Ascites was demonstrated in 68%, portal hypertension in 11%, and splenomegaly in 8% of patients with pseudocirrhosis.ConclusionsPseudocirrhosis does not occur in the absence of liver metastases, can manifest as hepatic decompensation, and appears to be associated with poorer survival amongst patients with hepatic metastases. Higher cumulative exposure to systemic therapy may be causative, instead of the previously held belief of pseudocirrhosis as an adverse effect of a particular systemic agent/class.

Molecular testing has reduced the need for diagnostic hemithyroidectomy for indeterminate thyroid nodules. No studies have directly compared molecular testing techniques. Compare the diagnostic performance of Afirma Gene Expression Classifier (GEC) with that of ThyroSeq v2 next-generation sequencing assay. Parallel randomized trial, monthly block randomization of patients with Bethesda III/IV cytology to GEC or ThyroSeq v2. University of California, Los Angeles. Patients who underwent thyroid biopsy (April 2016 to June 2017). Testing with GEC or ThyroSeq v2. Molecular test performance. Of 1372 thyroid nodules, 176 (13%) had indeterminate cytology and 149 of 157 eligible indeterminate nodules (95%) were included in the study. Of nodules tested with GEC, 49% were suspicious, 43% were benign, and 9% were insufficient. Of nodules tested with ThyroSeq v2, 19% were mutation positive, 77% were mutation negative, and 4% were insufficient. The specificities of GEC and ThyroSeq v2 were 66% and 91%, respectively (P = 0.002); the positive predictive values of GEC and ThyroSeq v2 were 39% and 57%, respectively. Diagnostic hemithyroidectomy was avoided in 28 patients tested with GEC (39%) and 49 patients tested with ThyroSeq v2 (62%). Surveillance ultrasonography was available for 46 nodules (45 remained stable). ThyroSeq v2 had higher specificity than Afirma GEC and allowed more patients to avoid surgery. Long-term surveillance is necessary to assess the false-negative rate of these particular molecular tests. Further studies are required for comparison with other available molecular diagnostics and for newer tests as they are developed.

The Response Evaluation in Solid Tumors (RECIST) 1.1 provides key guidance for performing imaging response assessment and defines image-based outcome metrics in oncology clinical trials, including progression free survival. In this framework, tumors identified on imaging are designated as either target lesions, non-target disease or new lesions and a structured categorical response is assigned at each imaging time point. While RECIST provides definitions for these categories, it specifically and objectively defines only the target disease. Predefined thresholds of size change provide unbiased metrics for determining objective response and disease progression of the target lesions. However, worsening of non-target disease or emergence of new lesions is given the same importance in determining disease progression despite these being qualitatively assessed and less rigorously defined. The subjective assessment of non-target and new disease contributes to reader variability, which can impact the quality of image interpretation and even the determination of progression free survival. The RECIST Working Group has made significant efforts in developing RECIST 1.1 beyond its initial publication, particularly in its application to targeted agents and immunotherapy. A review of the literature highlights that the Working Group has occasionally employed or adopted objective measures for assessing non-target and new lesions in their evaluation of RECIST-based outcome measures. Perhaps a prospective evaluation of these more objective definitions for non-target and new lesions within the framework of RECIST 1.1 might improve reader interpretation. Ideally, these changes could also better align with clinically meaningful outcome measures of patient survival or quality of life.

PurposeClear cell renal cell carcinoma (ccRCC) comprises nearly 90% of all diagnosed RCC subtypes and has the worst prognosis and highest metastatic potential. The strongest prognostic factors for patients with ccRCC include histological subtype and Fuhrman grade, which are incorporated into prognostic models. Since ccRCC is a highly vascularized tumor, there may be differences in enhancement patterns on multidetector CT (MDCT) due to the hemodynamics and microvessel density (MVD) of the lesions. This may provide a noninvasive method to characterize incidentally detected low- and high-grade ccRCCs on MDCT. The purpose of our study was to determine the correlation between MDCT enhancement parameters, ccRCC MVD, and Fuhrman grade to determine its utility and value in assessing tumor vascularity and grade in vivo.MethodsIn this retrospective, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low-grade (LG), and 43 high-grade (HG) ccRCCs underwent preoperative four-phase MDCT. A 3D volume of interest (VOI) was obtained for every tumor and absolute enhancement and the wash-in/wash-out of enhancement for each phase was assessed. Immunohistochemistry on resected specimens was used to quantify MVD. Linear regression and Pearson correlation were used to investigate the strength of the association between 3D VOI enhancement and MVD. Stepwise logistic regression analysis determined independent predictors of HG ccRCC. Cut-off values and odds Ratio (OR) with 95% CIs were reported. The clinical, radiomic, and pathologic features with the highest performance in the stepwise logistic regression analysis were evaluated using receiver operator characteristics (ROC) and area under the curve (AUC).ResultsAbsolute enhancement in the nephrographic phase < 52.1 Hounsfield Units (HU) (HR 0.979, 95% CI 0.964–0.994, p value = 0.006), lesion size > 4.3 cm (HR 1.450, 95% CI 1.211–1.738, p value < 0.001), and an intratumoral MVD < 15% (HR 0.932, 95% CI 0.867–1.002, p value = 0.058) were independent predictors of HG ccRCC with an AUC of 0.818 (95% CI 0.725–0.911). HG ccRCCs had a significant association between 3D VOI enhancement and MVD in each post-contrast phase (r2 = 0.238 to 0.455, p < 0.05).ConclusionsAbsolute enhancement of the entire lesion obtained from a 3D VOI in the nephrographic phase on preoperative MDCT can provide quantitative data that are a significant, independent predictor of a high-grade clear cell RCC and can be used to assess tumor vascularity and grade in vivo.

Objective To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML). Materials and methods We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI − cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland–Altman analysis was used to compare peak ROI between CAD and manual method. Results The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732–0.968), 0.959 (95% CI 0.930–0.989), 0.792 (95% CI 0.716–0.869), and 0.825 (95% CI 0.703–0.948), respectively. On Bland–Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase. Conclusion A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.

PurposeThe purpose of the study was to determine if enhancement features and qualitative imaging features on multiphasic multidetector computed tomography (MDCT) were associated with tumor grade in patients with clear cell renal cell carcinoma (ccRCC).MethodsIn this retrospective, IRB approved, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low grade (LG) and 43 high grade (HG) ccRCCs underwent preoperative four-phase MDCT in unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases. Previously published quantitative (absolute peak lesion enhancement, absolute peak lesion enhancement relative to normal enhancing renal cortex, 3D whole lesion enhancement and the wash-in/wash-out of enhancement within the 3D whole lesion ROI) and qualitative (enhancement pattern; presence of necrosis; pattern of; tumor margin; tumor–parenchymal interface, tumor–parenchymal interaction; intratumoral vascularity; collecting system infiltration; renal vein invasion; and calcification) assessments were obtained for each lesion independently by two fellowship-trained genitourinary radiologists. Comparisons between variables included χ2, ANOVA, and student t test. p values less than 0.05 were considered to be significant. Inter-reader agreement was obtained with the Gwet agreement coefficient (AC1) and standard error (SE) was reported.ResultsNo significant differences were observed between the LG and HG ccRCC cohorts with respect to absolute peak lesion enhancement and relative lesion enhancement ratio. There was a significant inverse correlation between low and high grade ccRCC and tumor enhancement the NP (71 HU vs. 54 HU, p < 0.001) and EX (52 HU vs. 39 HU, p < 0.001) phases using the 3D whole lesion ROI method. The percent wash-in of 3D enhancement from the UN to the CM phase was also significantly different between LG and HG ccRCCs (352% vs. 255%, p = 0.003). HG lesions showed significantly more calcification, necrosis, collecting system infiltration and ill-defined tumor margins (p < 0.05). Overall agreement between the two readers had a mean AC1 of 0.8172 (SE 0.0235).ConclusionsQuantitatively, high grade ccRCC had significantly lower whole lesion enhancement in the NP and EX phases on MDCT. Qualitatively, high grade ccRCC were significantly more likely to be associated with calcifications, necrosis, collecting system infiltration, and an ill-defined tumor margin.

IntroductionBreast cancer is common and women requiring mastectomy will be offered a breast reconstruction if they are surgically suitable candidate. Breast reconstruction can be performed at the same time as the mastectomy (immediate) or delayed to a second operation after cancer treatments. The reconstruction can either use the patients’ own tissue to make the breast (autologous) or use a prosthesis to make the breast in the form of a fixed or expandable volume implant (implant-based breast reconstruction, IBBR). Immediate breast reconstruction on top of the chest wall muscles (prepectoral) is performed worldwide. This operation involves the use of a synthetic or biological mesh placed around the implant under the skin. Increasingly, surgeons are performing this technique without the use of mesh. Both techniques, with and without mesh, have not been compared in a head-to-head randomised controlled trial (RCT); therefore, surgeons and patients do not have high quality data to guide their decision making in this area.Methods and analysisUK-based pragmatic multicentre randomised controlled feasibility trial. The primary aim is to determine the feasibility of a definitive RCT comparing the clinical and cost-effectiveness of no-mesh versus mesh-assisted prepectoral breast reconstruction. Secondary objectives will explore patient understanding of mesh and willingness to be randomised within an RCT; determine if it is possible to collect data to inform a future economic analysis on the use of mesh in breast reconstruction and determine the feasibility of measuring breast biomechanics pre-surgery and post breast reconstruction surgery. Total number of patients to be included: 40 (20 per arm).Ethics and disseminationThis study will be conducted in compliance with the Declaration of Helsinki. Ethical approval has been obtained. Ethics Ref: 23/SC/0302; IRAS Project ID: 301 423. The results of this study will be published in a peer-reviewed medical journal, independent of the results, following the Consolidated Standards of Reporting Trials standards for RCTs.Trial registration numbersNCT06112977; ISRCTN17470747.