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Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions based on IMS protein data, a task that is challenging solely by histopathologic evaluation. Most IMS-focused studies collect microscopy in tandem with IMS data, but this microscopy data is generally omitted in downstream data analysis. Microscopy, nevertheless, forms the basis for traditional histopathology and thus contains invaluable morphological information. In this work, we developed a multimodal classification pipeline that uses deep learning, in the form of a pre-trained artificial neural network, to extract the meaningful morphological features from histopathological images, and combine it with the IMS data. To test whether this deep learning-based classification strategy can improve on our previous results in classification of melanocytic neoplasia, we utilized MALDI IMS data with collected serial H&E stained sections for 331 patients, and compared this multimodal classification pipeline to classifiers using either exclusively microscopy or IMS data. The multimodal pipeline achieved the best performance, with ROC-AUCs of 0.968 vs. 0.938 vs. 0.931 for the multimodal, unimodal microscopy and unimodal IMS pipelines respectively. Due to the use of a pre-trained network to perform the morphological feature extraction, this pipeline does not require any training on large amounts of microscopy data. As such, this framework can be readily applied to improve classification performance in other experimental settings where microscopy data is acquired in tandem with IMS experiments., Competing Interests: JLM, NHP, SN, RMC, JLN, and JR disclose a financial interest in Fron- tier Diagnostics, LLC (FDx). FDx has issued and pending patent appli- cations in the US Patent Office that include part of the methods described in this paper. NV and MC, principals of Aspect Analytics NV, are paid consultants and provide services to FDx. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm 2 ) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

Background: The definitive diagnosis of melanocytic neoplasia using solely histopathologic evaluation can be challenging. Novel techniques that objectively confirm diagnoses are needed. This study details the development and validation of a melanoma prediction model from spatially resolved multivariate protein expression profiles generated by imaging mass spectrometry (IMS)., Methods: Three board-certified dermatopathologists blindly evaluated 333 samples. Samples with triply concordant diagnoses were included in this study, divided into a training set (n = 241) and a test set (n = 92). Both the training and test sets included various representative subclasses of unambiguous nevi and melanomas. A prediction model was developed from the training set using a linear support vector machine classification model., Results: We validated the prediction model on the independent test set of 92 specimens (75 classified correctly, 2 misclassified, and 15 indeterminate). IMS detects melanoma with a sensitivity of 97.6% and a specificity of 96.4% when evaluating each unique spot. IMS predicts melanoma at the sample level with a sensitivity of 97.3% and a specificity of 97.5%. Indeterminate results were excluded from sensitivity and specificity calculations., Conclusion: This study provides evidence that IMS-based proteomics results are highly concordant to diagnostic results obtained by careful histopathologic evaluation from a panel of expert dermatopathologists., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Computational analysis is crucial to capitalize on the wealth of spatio-molecular information generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial information available in MSI data is often under-utilized, due to the challenges of in-depth spatial pattern extraction. The advent of deep learning has greatly facilitated such complex spatial analysis. In this work, we use a pre-trained neural network to extract high-level features from ion images in MSI data, and test whether this improves downstream data analysis. The resulting neural network interpretation of ion images, coined neural ion images, is used to cluster ion images based on spatial expressions. We evaluate the impact of neural ion images on two ion image clustering pipelines, namely DBSCAN clustering, combined with UMAP-based dimensionality reduction, and k-means clustering. In both pipelines, we compare regular and neural ion images from two different MSI datasets. All tested pipelines could extract underlying spatial patterns, but the neural network-based pipelines provided better assignment of ion images, with more fine-grained clusters, and greater consistency in the spatial structures assigned to individual clusters. Additionally, we introduce the relative isotope ratio metric to quantitatively evaluate clustering quality. The resulting scores show that isotopical m/z values are more often clustered together in the neural network-based pipeline, indicating improved clustering outcomes. The usefulness of neural ion images extends beyond clustering towards a generic framework to incorporate spatial information into any MSI-focused machine learning pipeline, both supervised and unsupervised.

Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a large number of ions concurrently in a single experiment. While this makes it particularly suited for exploratory analysis, the large amount and high-dimensional nature of data generated by IMS techniques make automated computational analysis indispensable. Research into computational methods for IMS data has touched upon different aspects, including spectral preprocessing, data formats, dimensionality reduction, spatial registration, sample classification, differential analysis between IMS experiments, and data-driven fusion methods to extract patterns corroborated by both IMS and other imaging modalities. In this work, we review unsupervised machine learning methods for exploratory analysis of IMS data, with particular focus on (a) factorization, (b) clustering, and (c) manifold learning. To provide a view across the various IMS modalities, we have attempted to include examples from a range of approaches including matrix assisted laser desorption/ionization, desorption electrospray ionization, and secondary ion mass spectrometry-based IMS. This review aims to be an entry point for both (i) analytical chemists and mass spectrometry experts who want to explore computational techniques; and (ii) computer scientists and data mining specialists who want to enter the IMS field. © 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc. Mass SpecRev 00:1-47, 2019., (© 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc.)

In this work, uniform manifold approximation and projection (UMAP) is applied for nonlinear dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We evaluate the performance of the UMAP algorithm on MSI data sets acquired in mouse pancreas and human lymphoma samples and compare it to those of principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and the Barnes-Hut (BH) approximation of t-SNE. Furthermore, we compare different distance metrics in (BH) t-SNE and UMAP and propose the use of spatial autocorrelation as a means of comparing the resulting low-dimensional embeddings. The results indicate that UMAP is competitive with t-SNE in terms of visualization and is well-suited for the dimensionality reduction of large (>100 000 pixels) MSI data sets. With an almost fourfold decrease in runtime, it is more scalable in comparison with the current state-of-the-art: t-SNE or the Barnes-Hut approximation of t-SNE. In what seems to be the first application of UMAP to MSI data, we assess the value of applying alternative distance metrics, such as the correlation, cosine, and the Chebyshev metric, in contrast to the traditionally used Euclidean distance metric. Furthermore, we propose "histomatch" as an additional custom distance metric for the analysis of MSI data.

Purpose: To investigate the potential added value of paclitaxel-coated balloon (PCB) angioplasty to reduce fistula dysfunction related to recurrent stenoses in patients undergoing hemodialysis., Materials and Methods: A prospective, randomized study was conducted in 3 dialysis referral centers. From January 2013 to October 2015, 64 patients (22 female, 42 male) with dysfunctional autologous dialysis fistulae were randomized to undergo conventional percutaneous balloon angioplasty (n = 31) or PCB angioplasty (n = 33). Procedural and postprocedural data were assessed. Primary patency of the fistula was evaluated at 3, 6, and 12 months following the procedure. Statistical analysis was based on the Fisher exact test and independent t test., Results: There were no procedural or postprocedural complications. After 3, 6, and 12 months of follow-up, primary patency rates after PCB angioplasty and percutaneous transluminal angioplasty (PTA) were 88% and 80% (P = .43), 67% and 65% (P = .76), and 42% and 39% (P = .95), respectively., Conclusions: Although primary patency rates after PCB angioplasty in autologous dialysis fistulae at 3, 6, and 12 months of follow-up are slightly better than those after PTA, the difference is not statistically significant., (Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.)

Imaging mass spectrometry (IMS) is a molecular imaging technology that can measure thousands of biomolecules concurrently without prior tagging, making it particularly suitable for exploratory research. However, the data size and dimensionality often makes thorough extraction of relevant information impractical. To help guide and accelerate IMS data analysis, we recently developed a framework that integrates IMS measurements with anatomical atlases, opening up opportunities for anatomy-driven exploration of IMS data. One example is the automated anatomical interpretation of ion images, where empirically measured ion distributions are automatically decomposed into their underlying anatomical structures. While offering significant potential, IMS-atlas integration has thus far been restricted to the Allen Mouse Brain Atlas (AMBA) and mouse brain samples. Here, we expand the applicability of this framework by extending towards new animal species and a new set of anatomical atlases retrieved from the Scalable Brain Atlas (SBA). Furthermore, as many SBA atlases are based on magnetic resonance imaging (MRI) data, a new registration pipeline was developed that enables direct non-rigid IMS-to-MRI registration. These developments are demonstrated on protein-focused FTICR IMS measurements from coronal brain sections of a Parkinson's disease (PD) rat model. The measurements are integrated with an MRI-based rat brain atlas from the SBA. The new rat-focused IMS-atlas integration is used to perform automated anatomical interpretation and to find differential ions between healthy and diseased tissue. IMS-atlas integration can serve as an important accelerator in IMS data exploration, and with these new developments it can now be applied to a wider variety of animal species and modalities. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann., (Copyright © 2017. Published by Elsevier B.V.)

Purpose: When dialysis access stenoses are dilated by noncoated balloons, respective primary and secondary patencies hardly reach 50 per cent and 85 per cent at one year. This study determines the primary and secondary patency rates at 6 and 12 months for venous stenoses treated by paclitaxel-coated balloon (PCB) angioplasty in native hemodialysis accesses., Materials and Methods: From 2012 to 2014, 70 venous stenoses in 41 patients benefited from PCB angioplasties. The patients' mean age was 62.5 ± 13.8 years' standard deviation (SD) with 75 per cent male gender, 31.7 per cent diabetes, and 65.9 per cent arterial hypertension. There were 58.5 per cent forearm fistulas and 41.5 per cent arm fistulas. Primary and secondary patency rates were prospectively established by using the Kaplan-Meier technique and tested by using the log-rank test., Results: The primary patency rates ± SD were 81.4 ± 4.6 per cent and 60 ± 5.9 per cent at 6 and 12 months, respectively. The secondary patency rates ± SD reached 94.3 ± 2.8 per cent at 6 months and 91.4 ± 3.3 per cent at 12 months., Conclusion: This study shows an improvement of the primary and secondary patency rates at 6 and 12 months when venous stenoses of native dialysis fistulas are treated by PCB. The indications for PCB, however, remain to be established by larger randomized studies., Competing Interests: The authors declare that they have no competing interests.

Acute upper digestive tract hemorrhage most often arises from gastric and esophageal vessels located in the mucosa or the submucosa. Rupture in the upper gastrointestinal tract is a classical but uncommon complication of arterial (mainly the abdominal aorta) aneurysms. Splenic artery aneurysm usually ruptures in the peritoneum, unless it is associated with a disease eroding the gastrointestinal wall. We present and describe the management of the rare occurrence of an intragastric rupture of a splenic aneurysm associated with a pancreatic cancer.

Objective: This study aims to assess whether a comparison of the Doppler flow measurements of the ulnar artery and of the postanastomotic radial artery can help detect steal syndromes at the level of native dialysis fistulas of the wrist., Patients and Methods: We have prospectively analyzed 35 distal radiocephalic arteriovenous fistulas presenting with postanastomotic radial artery Doppler inversion of flow. The flows of the ulnar artery and of the postanastomotic radial artery have been measured and compared. Subsequent clinical examination to detect any sign of ischemia at the hand level was performed and the results of medical imaging were confronted with the clinical data., Results: A steal syndrome was discovered in a total of 6 patients (17%), 4 patients out of 23 displaying an ulnar flow lower than the postanastomotic radial one and 2 patients among 12 with an ulnar flow higher than the radial one. Sensitivity, specificity, positive predictive value and negative predictive value of the test were 67%, 34%, 17% and 83%, respectively. Paradoxically, the mean intensity of ulnar flow deficiency has been measured at 40% among true positive patients and at 70% among false positive ones. We have not been able to identify any difference, be it in terms of systolic upstroke time, maximum systolic speed, telediastolic speed or in terms of global architecture of the curves between the Doppler waveforms of 4 true positive and 4 false positive patients., Conclusion: The comparative Doppler study of the flows of the ulnar and postanastomotic radial arteries does not enable us to detect steal syndromes at the level of wrist dialysis fistulas. Hence we consider that a systematic study of the postanastomotic radial artery flow, during routine Doppler examination of distal dialysis fistulas, proves superfluous.

Imaging mass spectrometry (IMS) has become a prime tool for studying the distribution of biomolecules in tissue. Although IMS data sets can become very large, computational methods have made it practically feasible to search these experiments for relevant findings. However, these methods lack access to an important source of information that many human interpretations rely upon: anatomical insight. In this work, we address this need by (1) integrating a curated anatomical data source with an empirically acquired IMS data source, establishing an algorithm-accessible link between them and (2) demonstrating the potential of such an IMS-anatomical atlas link by applying it toward automated anatomical interpretation of ion distributions in tissue. The concept is demonstrated in mouse brain tissue, using the Allen Mouse Brain Atlas as the curated anatomical data source that is linked to MALDI-based IMS experiments. We first develop a method to spatially map the anatomical atlas to the IMS data sets using nonrigid registration techniques. Once a mapping is established, a second computational method, called correlation-based querying, gives an elementary demonstration of the link by delivering basic insight into relationships between ion images and anatomical structures. Finally, a third algorithm moves further beyond both registration and correlation by providing automated anatomical interpretation of ion images. This task is approached as an optimization problem that deconstructs ion distributions as combinations of known anatomical structures. We demonstrate that establishing a link between an IMS experiment and an anatomical atlas enables automated anatomical annotation, which can serve as an important accelerator both for human and machine-guided exploration of IMS experiments.

Primary aortic thrombosis remains a rare entity that can be defined as clotting of the vessel without any obvious atheromatous lesion. Cancer chemotherapy, cocaine intake, essential thrombocythemia, some hypercoagulable states, heparin-induced thrombocytopenia, inflammatory disease of the digestive tract and acute pancreatitis are, beside some cases of rather unknown etiology, the causes of primary aortic thrombosis. Intravenous contrast-enhanced multislice CT, which is widely available, noninvasive and affordable in terms of cost, is the imaging modality of choice for the investigation of primary aortic thrombosis and the assessment of potential complications. Three cases due to chemotherapy, antiphospholipid syndrome and acute pancreatitis are reported.

Renal transplantation is the choice treatment of end-stage renal disease. When it is not indicated or not immediately feasible, hemodialysis must be performed, preferably via a native arteriovenous fistula in the forearm. A pre-anastomotic occlusion of this type of fistula is often accompanied by a thrombosis of its draining vein. In some instances, the venous segment may remain permeable thanks to the development of arterial collateral pathways and may even allow efficient dialysis without any clinical syndrome of distal steal. We present the echo-Doppler, magnetic and angiographic characteristics of three of these collateralized shunts that have remained functional, in one of the cases following a percutaneous dilation.

Objective: To test the hypothesis that differential surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein or peptide expression in plasma can be used in infertile women with or without pelvic pain to predict the presence of laparoscopically and histologically confirmed endometriosis, especially in the subpopulation with a normal preoperative gynecologic ultrasound examination., Methods: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis was performed on 254 plasma samples obtained from 89 women without endometriosis and 165 women with endometriosis (histologically confirmed) undergoing laparoscopies for infertility with or without pelvic pain. Data were analyzed using least squares support vector machines and were divided randomly (100 times) into a training data set (70%) and a test data set (30%)., Results: Minimal-to-mild endometriosis was best predicted (sensitivity 75%, 95% confidence interval [CI] 63-89; specificity 86%, 95% CI 71-94; positive predictive value 83.6%, negative predictive value 78.3%) using a model based on five peptide and protein peaks (range 4.898-14.698 m/z) in menstrual phase samples. Moderate-to-severe endometriosis was best predicted (sensitivity 98%, 95% CI 84-100; specificity 81%, 95% CI 67-92; positive predictive value 74.4%, negative predictive value 98.6%) using a model based on five other peptide and protein peaks (range 2.189-7.457 m/z) in luteal phase samples. The peak with the highest intensity (2.189 m/z) was identified as a fibrinogen β-chain peptide. Ultrasonography-negative endometriosis was best predicted (sensitivity 88%, 95% CI 73-100; specificity 84%, 95% CI 71-96) using a model based on five peptide peaks (range 2.058-42.065 m/z) in menstrual phase samples., Conclusion: A noninvasive test using proteomic analysis of plasma samples obtained during the menstrual phase enabled the diagnosis of endometriosis undetectable by ultrasonography with high sensitivity and specificity., Level of Evidence: II.

Despite being time-consuming and observer-dependent, CDUS is a method of choice for performing and controlling dialysis shunts. It contributes to increasing the number of native AVFs and enables early detection of lesions therefore allowing quick percutaneous or surgical therapy.

Usually considered as a life-threatening disease, emphysematous pancreatitis requires early diagnosis and aggressive multidisciplinary treatment including the Departments of Gastroenterology, Intensive Care Medicine, Interventional Radiology and even Surgery. The prognosis for emphysematous cholecystitis is also quite poor. It requires surgery even if a percutaneous cholecystostomy can contribute to a temporary stabilization of the patient. Computed tomography is the imaging modality of choice to detect emphysematous pancreatitis and gas-forming cholecystitis. It enables their grading and helps identify their complications. Moreover, it proves essential in the follow-up of the lesions.

Though duodenal varix ruptures account for only 5% of variceal hemorrhages, they often have a fatal outcome with a mortality as high as 40%. Their detection and treatment, which often prove quite difficult endoscopically, benefit of CT imaging and percutaneous endovascular radiological techniques.

In most cases, renal graft obstruction is caused by ureteral stenosis due to ischemia or technical error. Exceptional cases have been published where the obstacle was the result of incarceration of the ureter in an inguinal hernia. We report a case of this type, which prompt assessment was possible due to ultrasound and magnetic resonance imaging with 3D reconstruction.

Unlabelled: Purposes. In this prospective study, we sought to determine the sensitivity and the specificity of arterial Doppler findings of valvular aortic stenosis (VAS)., Patients and Methods: 20 control subjects and 20 patients with various degrees of VAS underwent Doppler ultrasound of the carotids, abdominal aorta, renal arteries and limb arteries. We analyzed and compared the shape of the spectral profiles, peak systolic velocity (PSV), systolic upstroke time (SUT) and systolic upstroke index (SUI) of every tracing. The protodiastolic notch (PDN) of the common femoral arteries were recorded too., Results: VAS hardly modifies the overall shape of the Doppler spectrums of the aorta or limb arteries but it implies a biphasic deformation or a doubling of the systolic peak of the neck vessels. We also encountered biphasic profiles in renal arteries of patients with tight VAS. The PSV, SUI and depth of the PDN tend to diminish in cases of VAS but the variations are inconstant and rarely proportional to the severity of the narrowing. The increase of the SUT, on the contrary, is linearly correlated to the severity of the stenosis in every arterial system: SUTs in the common carotid artery, internal carotid artery or brachial artery that are shorter than or equal to 70 milliseconds (msec) are the obvious marks of the absence of VAS. It was not possible to differentiate between the intermediate stenoses (aortic valve area between 0.8 and 2 square centimeters) whereas critical aortic stenoses, whose area is less than or equal to 0.7 square centimeter, can be detected by the presence of at least two of the four following criteria of SUT: equal to or above 180 msec for the common carotid, 200 msec for the internal carotid, 130 msec for the aorta and 110 msec for the common femoral artery., Conclusion: During routine arterial Doppler ultrasound, a precise analysis of the spectrums and some SUT measurements allow the assessment of the aortic valve.

We report a rare case of an extracranial internal carotid artery aneurysm (EICAA) discovered incidentally by color Doppler sonography (CDUS) and confirmed by CT angiography with three-dimensional reconstructions. As both brain MRI and cerebral angiography were normal and the patient remained asymptomatic, he was neither operated on nor stented but was discharged with appropriate antiplatelet therapy. The volume of his EICAA is checked regularly by CDUS.

We present a case of inguinal bladder hernia detected initially with sonography in an adult patient. Compared with digestive or omental hernias, inguinocrural bladder herniations are a rarer occurrence (1 to 4% of all cases). Their detection is nevertheless highly imperative in order to avoid inadvertent injury to the bladder during routine hemiorrhaphy. Since the advent of high frequency equipment, ultrasonography has become the essential method of diagnosing vesical hernias. It is simple and fast, totally non-invasive, inexpensive, and widely available.

We present a case of post-cardiac catheterization femoral fistula diagnosed by color and pulsed Doppler sonography and treated by ultrasound-guided compression. We avail ourselves of the case to review the echo Doppler semiology of the different types of arteriovenous fistulas with an emphasis on the functional analysis of the dialysis accesses. We also stress the therapeutic options in front of undesirable shunts.

Purpose: The purpose of this study was to determine the sensitivity and specificity of arterial Doppler findings of aortic regurgitation to assess if the amplitude of changes of Doppler tracings can accurately quantify the degree of regurgitation., Patients and Methods: We analysed and compared the arterial Doppler tracings and echocardiograms of 250 patients., Results: Even if the obvious pitfall of vascular stenoses is avoided, the global sensitivity of arterial Doppler findings for aortic regurgitation remains weak (30%). However, our study demonstrates that it can reach 100% if only significant AR (> or =2/4) is taken into account. Since the clear false-positive cases have been carefully excluded from the very start, the specificity of the classical criteria already proves excellent (above 95%). It will reach perfection if additional simple criteria gathered from the data mentioned in this study are considered. Quantifying precisely the degree of aortic regurgitation on the basis of arterial Doppler tracings is impossible. Nevertheless, we show that it is easy to identify significant AR (> or =2/4) that should be further assessed with echocardiography., Conclusion: Arterial Doppler sonography is unable to detect all cases of aortic regurgitation but those that are overlooked are not significant (1/4). If AR signs happen to be detected by arterial Doppler, the amplitude of the leak cannot be accurately determined based on tracing analysis. Yet, simple criteria will indicate whether it is important enough (> or =2/4) to require complementary echocardiogram, with well documented accuracy for morphological and hemodynamic evaluation.

In most cases, ostial occlusion of the subclavian artery induces a reversal of the blood flow in the ipsilateral vertebral artery. This hemodynamic diversion is obviously brought out by Doppler ultrasound of the neck vessels. Nevertheless, when the subclavian ostial lesions are less severe or in case of anatomical variations, the alterations of the vertebral flux are more discrete. An accurate Doppler examination is then required to avoid pitfalls. In the light of a particularly complex case, we reviewed the Doppler signs of vertebral blood flow in normal conditions and in patent or less obvious subclavian steals.

Occlusion of the common carotid artery (CCA) is most often associated with thrombosis of the distal vessels. In rare cases, however, a weak antegrade flow can still be detected in the internal carotid artery (ICA). This patency is the result of a retrograde perfusion of the ipsilateral external carotid artery (ECA) via its collaterals. Such situation should not be ignored since bypass surgery can easily allow for effective restoration of flow. Most authors agree to say that color flow duplex imaging (CFDI) has now become the hallmark to detect a patent ICA in spite of a CCA occlusion.

Mesenchymal chondrosarcomas are rare malignant cartilaginous tumors arising either in bones or in extraosseous sites. Their diagnosis is essentially based on medical imaging and pathological analysis. Despite heavy treatment, their prognosis remains extremely poor.

Though duodenal diverticula are frequent and most often asymptomatic, they can cause serious complications. We present a case of duodenal diverticulitis without perforation, diagnosed by CT and treated conservatively by means of endoscopic maneuvers and medical therapy. A review of the recent literature regarding duodenal diverticula, complications, diagnosis and management is included.