The utility of ultrasound for the diagnosis and treatment of primary and metastatic melanoma - a remaining oncological challenge.

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Pre-operative high-frequency ultrasound: a reliable management tool in auricular and nasal non-melanoma skin cancer.

BACKGROUND AND OBJECTIVES: The knowledge of depth infiltration in non-melanoma skin cancer (NMSC) using pre-operative ultrasound could enable clinicians to choose the most adequate therapeutic approach, avoiding unnecessary surgeries and expensive imaging methods, delaying diagnosis and treatment. Our single-center retrospective study determined the usefulness of high-frequency ultrasound (HFUS) for depth infiltration assessment in auricular and nasal NMSC and assessed the subsequent change in therapeutic approach. PATIENTS AND METHODS: In 60 NMSC cases, we assessed the accuracy of HFUS in cartilaginous/bone infiltration detection as well as the correlation of sonographic and histological parameters. RESULTS: In 16.6% of cases, a deep cartilaginous/bone involvement or locoregional disease was identified pre-operatively, resulting in a changed therapeutical scheme of radio-immunological treatment rather than surgery. In two cases, pre-operative HFUS identified local cartilage infiltration, reducing the number of surgical procedures. Forty-eight remaining lesions with no depth infiltration were excised; a correlation of > 99% between the histologic and sonographic tumor depth (p<0.001) was found. CONCLUSIONS: Pre-surgical HFUS influences the therapeutic management in NMSC by detecting subclinical involvement of deeper structures, avoiding more extensive diagnostics, reducing costs, and improving healthcare quality. High-frequency ultrasound should be implemented in dermatosurgery before tumor excision for optimized therapy and improved patient counseling.

Preoperative MRI accuracy after neoadjuvant chemoradiation for locally advanced rectal cancer.

Background and aims: To evaluate the performance of magnetic resonance imaging (MRI) in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT), with pathologic correlation. Methods: 80 patients with LARC treated with neoadjuvant therapy, with restaging MRI and surgery, were enrolled and prospectively reviewed. The diagnostic accuracy of the restaging MRI was assessed for tumor (ymrT), nodal status (ymrN), circumferential resection margin (ymrCRM), extramural vascular invasion (ymrEMVI) and tumoral deposits (ymrN1c) by calculating the sensitivity (Se), specificity (Sp), negative predictive values (NPV) and positive predictive values (PPV). Response to treatment was classified as good response (complete/near complete) vs. poor response (poor/partial response). The agreement between the tumor regression grade at MRI (mrTRG) and pathology (pTRG) was reported, as well the performance of mrTRG to identify good responders. The correlation between restaging MRI and histopathology was assessed by Spearman correlation coefficient. Results: The MRI accuracy ranged between 63.8% and 92.5% for T stage and was 81.3% for N stage. All MRI parameters evaluated at restaging were statistically significant correlated with histopathology evaluation, but EMVI. There was moderate correlation for N and N1c and a positive strong correlation for T, CRM and TRG (Spearman correlation coefficient of 0.390 for mrN1c-pN1c, 0.428 for mrN-pN, 0.522 for mrCRM-pCRM, 0.550 for mrT-pT and 0.731 for mrTRG-pTRG). Diagnostic accuracy of anal sphincter invasion was 91.3%, with a negative predictive value (NPV) of 100%. Accuracy rate varied between 70% for partial response to 93.75% for complete response after nCRT. Conclusions: MR imaging had good accuracy in restaging LARCs after nCRT. Our results showed high MRI accuracy in detecting anal sphincter involvement for low rectal tumors, with high NPV to exclude tumoral invasion. Restaging MRI predicted well the tumor regression grade, with good diagnostic performance in differentiating good responders from poor/partial responders. The accuracy was high for detecting complete response.

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.

Hepatocellular Carcinoma (HCC) is the most frequent malignant liver tumor and the third cause of cancer-related deaths worldwide. For many years, the golden standard for HCC diagnosis has been the needle biopsy, which is invasive and carries risks. Computerized methods are due to achieve a noninvasive, accurate HCC detection process based on medical images. We developed image analysis and recognition methods to perform automatic and computer-aided diagnosis of HCC. Conventional approaches that combined advanced texture analysis, mainly based on Generalized Co-occurrence Matrices (GCM) with traditional classifiers, as well as deep learning approaches based on Convolutional Neural Networks (CNN) and Stacked Denoising Autoencoders (SAE), were involved in our research. The best accuracy of 91% was achieved for B-mode ultrasound images through CNN by our research group. In this work, we combined the classical approaches with CNN techniques, within B-mode ultrasound images. The combination was performed at the classifier level. The CNN features obtained at the output of various convolution layers were combined with powerful textural features, then supervised classifiers were employed. The experiments were conducted on two datasets, acquired with different ultrasound machines. The best performance, above 98%, overpassed our previous results, as well as representative state-of-the-art results.

MRI Evaluation of Complete and Near-Complete Response after Neoadjuvant Therapy in Patients with Locally Advanced Rectal Cancer.

Purpose To evaluate MRI performance in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT) and interobserver agreement in identifying complete response (CR) and near-complete response (nCR). Methods 40 patients with CR and nCR on restaging MRI, surgery and/or endoscopy were enrolled. Two radiologists independently scored the restaging MRI and reported the presence of split scar sign (SSS) and MRI tumor regression grade (mrTRG). Diagnostic accuracy and ROC curves were calculated for single and combined sequences, with inter-reader agreement. Results Diagnostic performance was good for detecting CR and weaker for nCR. T2WI had the highest AUCs among individual sequences. There was a significant positive correlation between SSS and CR, with high Sp (89.5%/73.7%) and PPV (90%/79.2%) for both Readers. Similar accuracy rates were observed for the combination of sequences, with AUCs of 0.828-0.847 for CR and 0.690-0.762 for nCR. Interobserver agreement was strong for SSS, moderate for T2WI, weak for the combination of sequences. Conclusions Restaging MRI had good diagnostic performance in identifying CR and nCR. SSS had high Sp and PPV in diagnosing CR, with a strong level of interobserver agreement. T2WI with DWI was the optimal combination of sequences for selecting good responders.

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

BACKGROUND: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. METHODS: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naïve Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. RESULTS: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 ± 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 ± 0.03) or SERS data (AUC = 0.84 ± 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 ± 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 ± 0.04) or SERS (AUC = 0.92 ± 0.05) individually, although SERS alone performed better in terms of classification accuracy. CONCLUSION: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged.

SERS Liquid Biopsy Profiling of Serum for the Diagnosis of Kidney Cancer.

Renal cancer (RC) represents 3% of all cancers, with a 2% annual increase in incidence worldwide, opening the discussion about the need for screening. However, no established screening tool currently exists for RC. To tackle this issue, we assessed surface-enhanced Raman scattering (SERS) profiling of serum as a liquid biopsy strategy to detect renal cell carcinoma (RCC), the most prevalent histologic subtype of RC. Thus, serum samples were collected from 23 patients with RCC and 27 controls (CTRL) presenting with a benign urological pathology such as lithiasis or benign prostatic hypertrophy. SERS profiling of deproteinized serum yielded SERS band spectra attributed mainly to purine metabolites, which exhibited higher intensities in the RCC group, and Raman bands of carotenoids, which exhibited lower intensities in the RCC group. Principal component analysis (PCA) of the SERS spectra showed a tendency for the unsupervised clustering of the two groups. Next, three machine learning algorithms (random forest, kNN, naïve Bayes) were implemented as supervised classification algorithms for achieving discrimination between the RCC and CTRL groups, yielding an AUC of 0.78 for random forest, 0.78 for kNN, and 0.76 for naïve Bayes (average AUC 0.77 ± 0.01). The present study highlights the potential of SERS liquid biopsy as a diagnostic and screening strategy for RCC. Further studies involving large cohorts and other urologic malignancies as controls are needed to validate the proposed SERS approach.

Contrast-enhanced ultrasound for the assessment of focal nodular hyperplasia - results of a multicentre study.

AIM: Contrast-enhanced ultrasound (CEUS) has become a relevant imaging method for the evaluation of focal liver le-sions (FLL). The aim of this study was to evaluate the performance of CEUS for the assessment of focal nodular hyperplasia (FNH) in a large study group. MATERIAL AND METHODS: We performed a multicentre prospective observational study, which included successive CEUS examinations from fourteen Romanian centres. CEUS examinations were performed in de novo FLL, using low mechanical index ultrasound, following an intravenous bolus of 2.4 ml SonoVue. CEUS was considered conclusive for FNH if a typical pattern was present following contrast (rapid "spoke-wheel" enhancement during the arterial phase, hyperenhanced lesion during venous phase, hyper- or isoenhanced in the late phase). In all cases a reference method was available (contrast enhanced CT or MRI or biopsy). The trial was registered in clinicaltrials.gov (Identifier NCT01329458). RESULTS: During the 6 years study, 2062 "de novo" FLL were evaluated by CEUS. From this cohort, 94/2062 (4.5%) had a typical enhancing pattern for FNH as described in the EFSUMB guidelines. Contrast enhanced CT/MRI and biopsy diagnosed additional 15 FNH. From the 94 cases diagnosed as FNH by CEUS, in nine the final diagnosis was different (five of them adenomas). CEUS had 85% sensitivity, 99.5% specificity, 90.4% positive predictive value, 99.2% negative predictive value and 98.8% diagnostic accuracy for the diagnosis of FNH. CONCLUSIONS: CEUS is a sensitive and very specific method for the diagnosis of FNH.

Time Trends Analysis of Cervical Cancer Incidence in Cluj County, Romania, Using Data from a Population-Based Cancer Registry.

(1) Background: Romania has one of the highest cervical cancer incidence rates in Europe. In Cluj County, the first screening program was initiated in 1998. We aimed to investigate the time trends of cervical cancer incidence in women from Cluj County and to evaluate the data quality at the Cancer Registry. (2) Methods: We calculated time trends of standardized incidence rates in the period 1998-2014 and the Annual Percent Change (APC%). To assess data quality, we used the indicators: mortality/incidence ratio (M/I), percentage of cases declared only at death (DOD%), and percentage of cases with pathological confirmation (PC%). (3) Results: The standardized incidence rate increased steadily, from 23.74 cases/100,000 in 1998, to 32/100,000 in 2014, with an APC% of 2.49% (p < 0.05). The rise in incidence affected both squamous cell carcinoma (APC% 2.49%) (p < 0.05) and cervical adenocarcinoma (APC% 10.54%) (p < 0.05). The M/I ratio was 0.29, DOD% 2.66%, and MC% 94.8%. The last two parameters are within the silver standard concerning data quality. (4) Conclusions. Our study revealed an ascending trend of cervical cancer incidence, more consistent for adenocarcinoma, in the context of a newly introduced screening program and partially due to the improvement of the quality of case reporting at the Cancer Registry from Cluj.

Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods.

Hepatocellular Carcinoma (HCC) is the most common malignant liver tumor, being present in 70% of liver cancer cases. It usually evolves on the top of the cirrhotic parenchyma. The most reliable method for HCC diagnosis is the needle biopsy, which is an invasive, dangerous method. In our research, specific techniques for non-invasive, computerized HCC diagnosis are developed, by exploiting the information from ultrasound images. In this work, the possibility of performing the automatic diagnosis of HCC within B-mode ultrasound and Contrast-Enhanced Ultrasound (CEUS) images, using advanced machine learning methods based on Convolutional Neural Networks (CNN), was assessed. The recognition performance was evaluated separately on B-mode ultrasound images and on CEUS images, respectively, as well as on combined B-mode ultrasound and CEUS images. For this purpose, we considered the possibility of combining the input images directly, performing feature level fusion, then providing the resulted data at the entrances of representative CNN classifiers. In addition, several multimodal combined classifiers were experimented, resulted by the fusion, at classifier, respectively, at the decision levels of two different branches based on the same CNN architecture, as well as on different CNN architectures. Various combination methods, and also the dimensionality reduction method of Kernel Principal Component Analysis (KPCA), were involved in this process. These results were compared with those obtained on the same dataset, when employing advanced texture analysis techniques in conjunction with conventional classification methods and also with equivalent state-of-the-art approaches. An accuracy above 97% was achieved when our new methodology was applied.

Intraoperative ultrasound in liver and pancreatic surgery.

This paper summarizes the current knowledge of intraoperative ultrasonography (IOUS) in open and laparoscopic ab-dominal surgery. The abdominal IOUS contributes to the diagnosis and staging (for parenchymal organ tumors), to establish surgical procedure and to guide surgical maneuvers. The main applications are represented by liver, biliary tract and pancreatic pathology. Diagnostic approaches are frequently combined with therapeutic purposes. The technique, equipment, training, benefits and limits of IOUS in abdominal surgery are discussed and cases from our experience are used as examples.

European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) Position Statement on Dermatologic Ultrasound.

Dermatologic ultrasound is a recent application of ultrasound for the evaluation of healthy skin and appendages and their diseases. Although the scientific literature regarding this application is still not sufficient for evidence-based guidelines, general recommendations issued by scientific societies are necessary. The EFSUMB (European Federation of Societies for Ultrasound in Medicine and Biology) steering committee for dermatologic ultrasound has developed a series of consensus position statements regarding the main fields of dermatologic ultrasound (technical requirement, normal skin and appendages, inflammatory skin diseases, tumoral skin diseases, aesthetic dermatology and practice-training requirements). This document is the foundation for future evidence-based recommendations and guidelines for dermatologic ultrasound practice.

All that glitters is not gold: a case report of a diffuse peritoneal aspergillosis.

Invasive aspergillosis is a rare disease, more frequently encountered in immunocompromised patients. We report a case of diffuse peritoneal aspergillosis. A 56-year old female with a history of recent renal transplantation was admitted with a suspicion of peritoneal carcinomatosis following a native computed tomography scan. Gray scale abdominal ultrasound showed multiple peritoneal masses. Upon performing contrast-enhanced ultrasound these masses demonstrated peripheral arterial enhancement and slow wash-out during the venous phase. The final histopathological examination confirmed a diagnosis of peritoneal aspergillosis. Gray scale ultrasonography in combination with contrast-enhanced ultrasonography is useful in the evaluation of intraabdominal masses. The procedures are of great value especially in patients with a high risk of contrastinduced nephropathy where contrast-enhanced CT or MRI are contraindicated.

Ultrasonography techniques in the preoperative diagnosis of parotid gland tumors - an updated review of the literature.

Preoperative diagnosis of parotid tumors plays a crucial role in selecting and planning the surgical treatment. Ultrasound (US) with its modern techniques can contribute to the differential diagnosis of parotid tumors. This paper aims to achieve a comprehensive review of the ultrasound techniques used in the differential diagnosis of parotid tumors, based on the latest literature data. Considering that most parotid gland tumors are located in the superficial lobe, US is frequently the first imaging technique used for the diagnosis of parotid tumors. Sonoelastography can provide additional data on the elasticity of parotid tumors, but there is an overlap between malignant and benign parotid tumors parameters. Contrast-enhanced ultrasound adds value to conventional ultrasound and allows a more complete characterization of parotid tumors. Many authors have reported promising results using contrast-enhanced ultrasound in the differential diagnosis of parotid tumors. Multiparametric ultrasound with a careful and systematic approach usually allows an accurate differential diagnosis of parotid tumors.

Cross-sectional imaging and cytologic investigations in the preoperative diagnosis of parotid gland tumors - An updated literature review.

An accurate preoperative diagnosis of parotid tumors is essential for the selection and planning of surgical treatment. Various modern cross-sectional imaging and cytologic investigations can support the differential diagnosis of parotid tumors. The aim of this study was to achieve a comprehensive and updated review of modern imaging and cytologic investigations used in parotid tumor diagnosis, based on the latest literature data. This literature review could serve as a guide for clinicians in selecting different types of investigations for the preoperative differential diagnosis of parotid tumors. Magnetic resonance imaging (MRI) with its dynamic and advanced sequences is the first-line imaging investigation used in differentiating parotid tumors. Computed tomography (CT) and positron emission tomography (PET)-CT provide limited indications in differentiating parotid tumors. Fine needle aspiration biopsy and core needle biopsy can contribute with satisfactory results to the cytological diagnosis of parotid tumors. Dynamic MRI with its dynamic contrast-enhanced and diffusion-weighted sequences provides the best accuracy for the preoperative differential diagnosis of parotid tumors. CT allows the best evaluation of bone invasion, being useful when MRI cannot be performed, and PET-CT has value in the follow-up of cancer patients. The dual cytological and imaging approach is the safest method for an accurate differential diagnosis of parotid tumors.

Integration of Real-Time Image Fusion in the Robotic-Assisted Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide, with its mortality rate correlated with the tumor staging; i.e., early detection and treatment are important factors for the survival rate of patients. This paper presents the development of a novel visualization and detection system for HCC, which is a composing module of a robotic system for the targeted treatment of HCC. The system has two modules, one for the tumor visualization that uses image fusion (IF) between computerized tomography (CT) obtained preoperatively and real-time ultrasound (US), and the second module for HCC automatic detection from CT images. Convolutional neural networks (CNN) are used for the tumor segmentation which were trained using 152 contrast-enhanced CT images. Probabilistic maps are shown as well as 3D representation of HCC within the liver tissue. The development of the visualization and detection system represents a milestone in testing the feasibility of a novel robotic system in the targeted treatment of HCC. Further optimizations are planned for the tumor visualization and detection system with the aim of introducing more relevant functions and increase its accuracy.

Current status of imaging diagnosis in the transplanted kidney. A review of the literature with a special focus on contrast-enhanced ultrasonography.

OBJECTIVES: Ultrasonographic scanning is currently the most widespread imaging diagnostic procedure. The method provides real-time morphological, vascular and elastographic information in a non-invasive manner. In recent years, harmonic vascular examination has become accessible using intravenous contrast agents. In urological pathology, this procedure is used in the detection and evaluation of vascular and ischemic complications, in the classification of complex cysts according to the Bosniak system, also in the renal lesions with uncertain etiology and in acute pyelonephritis for the detection of abscesses. The contrast agent (SonoVue) is angiospecific and can be used in patients transplanted immediately after surgery without adverse effects or impaired renal function. Thus, it is desirable to be used in the nephrological pathology of the renal graft and to develop diagnostic models based on the evaluation of renal microvascularization, as well as the quantitative data resulting from the graphical representation of the specific parameters. The purpose of this review is to evaluate the current state of the literature regarding the place and role of contrast substance ultrasound in the early diagnosis of acute renal graft dysfunction and to make a differential diagnosis of this pathological entity. METHOD: This review quantifies the role of contrast ultrasound in the diagnosis of acute complications of the renal graft. The research was conducted based on the databases PubMed, MedScape, Cochrane, according to the search criteria such as contrast-enhanced ultrasound + kidney transplant, "time intensity curves" + "kidney transplant", filtered for the period 2004-2018. RESULTS: In the nephrological pathology of the renal graft, contrast-enhanced ultrasound is a valuable tool, superior to Doppler ultrasound in predicting the evolution of the renal graft, identifying very small early defects in renal microvascularization. A number of studies succeeded in identifying acute graft dysfunction, some of which establish its etiology - humoral rejection versus acute tubular necrosis. On the other hand, the contrast-enhanced ultrasound parameters do not have the ability to distinguish between cellular and humoral rejection. CONCLUSIONS: If, at present, the histopathological examination is the only one that can differentiate with certainty the cause of acute renal graft dysfunction, we consider that contrast-enhanced ultrasound, as a non-invasive imaging technique, opens a favorable perspective for increasing the survival of the renal graft and decreasing the complications in the renal transplant. The combination of other ultrasound techniques, together with contrast-enhanced ultrasound, could lead to the development of new diagnostic models.

Embryonal carcinoma of an intraabdominal testicular tumor on an undescended testicle: a case report.

Cryptorchidism, as a singular pathology or associated with other dysgenesis syndromes, is one of the main factors of risk for the development of the testicular tumors. Although there are a great number of cases of undescended testicles that are diagnosed and treated during the first 6-12 months of life, there are rare cases of adults who are undiagnosed and untreated from this anomaly, which can present a high risk of malignancy. In this study we present the case of a 36-year-old patient, diagnosed at puberty with left cryptorchidism, untreated, who also hadevidenced a large intraabdominal tumoral mass associated with it. The tumoral mass had its origin in the undescended left testicle. Surgical excision of the tumor and retroperitoneal lymphadenectomy was performed. The histological result revealed embryonal carcinoma, without lymphnode metastasis. Adult patients with untreated cryptorchidism should be thoroughly investigated, as they have a high risk of developing testicular cancer.

Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.

The emergence of deep-learning methods in different computer vision tasks has proved to offer increased detection, recognition or segmentation accuracy when large annotated image datasets are available. In the case of medical image processing and computer-aided diagnosis within ultrasound images, where the amount of available annotated data is smaller, a natural question arises: are deep-learning methods better than conventional machine-learning methods? How do the conventional machine-learning methods behave in comparison with deep-learning methods on the same dataset? Based on the study of various deep-learning architectures, a lightweight multi-resolution Convolutional Neural Network (CNN) architecture is proposed. It is suitable for differentiating, within ultrasound images, between the Hepatocellular Carcinoma (HCC), respectively the cirrhotic parenchyma (PAR) on which HCC had evolved. The proposed deep-learning model is compared with other CNN architectures that have been adapted by transfer learning for the ultrasound binary classification task, but also with conventional machine-learning (ML) solutions trained on textural features. The achieved results show that the deep-learning approach overcomes classical machine-learning solutions, by providing a higher classification performance.