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State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "neo-N-termini" analysis or "N-terminomics"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.
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PURPOSE: First-line therapy options in advanced cholangiocarcinoma (CCA) are based on the ABC-02 trial regimen (gemcitabine/cisplatin [G/C]). The NIFE trial examined nanoliposomal irinotecan/fluorouracil/leucovorin (nal-IRI/FU/LV) as alternative first-line therapy in advanced CCA. METHODS: NIFE is a prospective, open-label, randomized, multicenter phase II study that aimed at detecting efficacy comparable with the standard treatment. Patients with advanced CCA were randomly assigned (1:1) to receive nal-IRI/FU/LV (arm A) or G/C (arm B). Stratification parameters were intrahepatic versus extrahepatic CCA, sex, and Eastern Cooperative Oncology Group (ECOG; 0/1). Arm A was designed as a Simon's optimal two-stage design and arm B served as a randomized control group. The primary goal was to exclude an inferior progression-free survival (PFS) at 4 months of only 40%, while assuming a rate of 60% on G/C population. RESULTS: Between 2018 and 2020, overall 91 patients were randomly assigned to receive nal-IRI/FU/LV (n = 49) or G/C (n = 42). The NIFE trial formally met its primary end point with a 4-month PFS rate of 51% in patients receiving nal-IRI/FU/LV. The median PFS was 6 months (2.4-9.6) in arm A and 6.9 months (2.5-7.9) in arm B. Median overall survival (OS) was 15.9 months (10.6-20.3) in arm A and 13.6 months (6.5-17.7) in arm B. The exploratory comparison of study arms suggested a numerical but statistically not significant advantage for nal-IRI/FU/LV (hazard ratio for PFS, 0.85 [95% CI, 0.53 to 1.38] and for OS, 0.94 [95% CI, 0.58 to 1.50]). Analysis for stratification parameters revealed no differences for sex and ECOG, but for tumor localization. The objective response rate was 24.5% with nal-IRI/FU/LV and 11.9% with G/C. No unexpected toxicities occurred. AEs related to nal-IRI/FU/LV were mainly GI and to G/C hematologic. CONCLUSION: Treatment of advanced CCA with nal-IRI/FU/LV demonstrated efficacy in first-line therapy without new safety findings and merits further validation.
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Cathepsin D (CTSD) is a lysosomal aspartic protease and its inherited deficiency causes a severe pediatric neurodegenerative disease called neuronal ceroid lipofuscinosis (NCL) type 10. The lysosomal dysfunction in the affected patients leads to accumulation of undigested lysosomal cargo especially in none-dividing cells, such as neurons, resulting in death shortly after birth. To explore which proteins are mainly affected by the lysosomal dysfunction due to CTSD deficiency, Lund human mesencephalic (LUHMES) cells, capable of inducible dopaminergic neuronal differentiation, were treated with Pepstatin A. This inhibitor of "acidic" aspartic proteases caused accumulation of acidic intracellular vesicles in differentiating LUHMES cells. Pulse-chase experiments involving stable isotope labelling with amino acids in cell culture (SILAC) with subsequent mass-spectrometric protein identification and quantification were performed. By this approach, we studied the degradation and synthesis rates of 695 and 680 proteins during early and late neuronal LUHMES differentiation, respectively. Interestingly, lysosomal bulk proteolysis was not altered upon Pepstatin A treatment. Instead, the protease inhibitor selectively changed the turnover of individual proteins. Especially proteins belonging to the mitochondrial energy supply system were differentially degraded during early and late neuronal differentiation indicating a high energy demand as well as stress level in LUHMES cells treated with Pepstatin A.
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PURPOSE: Sarcopenia is considered a negative prognostic factor in patients with malignant tumors. Among other diagnostic options, computed tomography (CT), which is repeatedly performed on tumor patients, can be of further benefit. The present study aims to establish a framework for classifying the impact of sarcopenia on the prognosis of patients diagnosed with esophageal or gastric cancer. Additionally, it explores the significance of CT radiomics in both diagnostic and prognostic methodologies. MATERIALS AND METHODS: CT scans of 83 patients with esophageal or gastric cancer taken at the time of diagnosis and during a follow-up period of one year were evaluated retrospectively. A total of 330 CT scans were analyzed. Seventy three of these patients received operative tumor resection after neoadjuvant chemotherapy, and 74% of the patients were male. The mean age was 64 years (31-83 years). Three time points (t) were defined as a basis for the statistical analysis in order to structure the course of the disease: t1 = initial diagnosis, t2 = following (neoadjuvant) chemotherapy and t3 = end of the first year after surgery in the "surgery" group or end of the first year after chemotherapy. Sarcopenia was determined using the psoas muscle index (PMI). The additional analysis included the analysis of selected radiomic features of the psoas major, quadratus lumborum, and erector spinae muscles at the L3 level. Disease progression was monitored according to the response evaluation criteria in solid tumors (RECIST 1.1). CT scans and radiomics were used to assess the likelihood of tumor progression and their correlation to sarcopenia. For machine learning, the established algorithms decision tree (DT), K-nearest neighbor (KNN), and random forest (RF) were applied. To evaluate the performance of each model, a 10-fold cross-validation as well as a calculation of Accuracy and Area Under the Curve (AUC) was used. RESULTS: During the observation period of the study, there was a significant decrease in PMI. This was most evident in patients with surgical therapy in the comparison between diagnosis and after both neoadjuvant therapy and surgery (each p < 0.001). Tumor progression (PD) was not observed significantly more often in the patients with sarcopenia compared to those without sarcopenia at any time point (p = 0.277 to p = 0.465). On average, PD occurred after 271.69 ± 104.20 days. The time from initial diagnosis to PD in patients "with sarcopenia" was not significantly shorter than in patients "without sarcopenia" at any of the time points (p = 0.521 to p = 0.817). The CT radiomics of skeletal muscle could predict both sarcopenia and tumor progression, with the best results for the psoas major muscle using the RF algorithm. For the detection of sarcopenia, the Accuracy was 0.90 ± 0.03 and AUC was 0.96 ± 0.02. For the prediction of PD, the Accuracy was 0.88 ± 0.04 and the AUC was 0.93 ± 0.04. CONCLUSIONS: In the present study, the CT radiomics of skeletal muscle together with machine learning correlated with the presence of sarcopenia, and this can additionally assist in predicting disease progression. These features can be classified as promising alternatives to conventional methods, with great potential for further research and future clinical application. However, when sarcopenia was diagnosed with PMI, no significant correlation between sarcopenia and PD could be observed.
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Gastroenteropancreatic neuroendocrine neoplasia (GEP-NEN) is a heterogeneous and complex group of tumors that are often difficult to classify due to their heterogeneity and varying locations. As standard radiological methods, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET/CT) are available for both localization and staging of NEN. Nuclear medical imaging methods with somatostatin analogs are of great importance since radioactively labeled receptor ligands make tumors visible with high sensitivity. CT and MRI have high detection rates for GEP-NEN and have been further improved by developments such as diffusion-weighted imaging. However, nuclear medical imaging methods are superior in detection, especially in gastrointestinal NEN. It is important for radiologists to be familiar with NEN, as it can occur ubiquitously in the abdomen and should be identified as such. Since GEP-NEN is predominantly hypervascularized, a biphasic examination technique is mandatory for contrast-enhanced cross-sectional imaging. PET/CT with somatostatin analogs should be used as the subsequent method.
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CLINICAL/METHODICAL ISSUE: Radiological procedures play a crucial role in the diagnosis of small bowel disease. Due to a broad and quite nonspecific spectrum of symptoms, clinical evaluation is often difficult, and endoscopic procedures require significant manpower, are time-consuming and expensive. In contrast, radiologic imaging can provide important information about morphologic and functional variations of the small bowel and help to identify various disease entities, such as inflammation, tumors, vascular problems, and obstruction. STANDARD RADIOLOGICAL METHODS: The most common radiological modalities in small bowel diagnostics include ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), and fluoroscopy. Each of these modalities has its own advantages and limitations, and the choice of imaging modality depends on clinical symptoms and suspected diagnosis in addition to availability. METHODOLOGICAL INNOVATIONS: In recent years, significant progress has been made, especially in cross-sectional imaging modalities, as a result of new and further technical developments. PERFORMANCE: These range from increasing detail resolution to functional and molecular imaging techniques that go far beyond simple morphology. In addition, information technology (IT) applications, which include artificial intelligence and radiomics, are assuming an increasing role. ACHIEVEMENTS: Many of the methods mentioned are still in early stages and need to be further developed for daily practice, but some have already found their way into clinical routine. PRACTICAL RECOMMENDATIONS: The aim of this work is to provide a review of the most important disease entities of the small intestine, including new and innovative diagnostic approaches.
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Inteligência Artificial , Enteropatias , Humanos , Imageamento por Ressonância Magnética , Tomografia Computadorizada por Raios X , Radiografia , Ultrassonografia , Enteropatias/diagnóstico por imagemRESUMO
The imaging evaluation of computed tomography (CT), CT angiography (CTA), and CT perfusion (CTP) is of crucial importance in the setting of each emergency department for suspected cerebrovascular impairment. A fast and clear assignment of characteristic imaging findings of acute stroke and its differential diagnoses is essential for every radiologist. Different entities can mimic clinical signs of an acute stroke, thus the knowledge and fast identification of stroke mimics is important. A fast and clear assignment is necessary for a correct diagnosis and a rapid initiation of appropriate therapy. This pictorial review describes the most common imaging findings in CTP with clinical signs for acute stroke or other acute neurological disorders. The knowledge of these pictograms is therefore essential and should also be addressed in training and further education of radiologists.
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Due to the increasing use of cross-sectional imaging techniques and new technical possibilities, the number of incidentally detected cystic lesions of the pancreas is rapidly increasing in everyday radiological routines. Precise and rapid classification, including targeted therapeutic considerations, is of essential importance. The new European guideline should also support this. This review article provides information on the spectrum of cystic pancreatic lesions, their appearance, and a comparison of morphologic and histologic characteristics. This is done in the context of current literature and clinical value. The recommendations of the European guidelines include statements on conservative management as well as relative and absolute indications for surgery in cystic lesions of the pancreas. The guidelines suggest surgical resection for mucinous cystic neoplasm (MCN) ≥ 40 mm; furthermore, for symptomatic MCN or imaging signs of malignancy, this is recommended independent of its size (grade IB recommendation). For main duct IPMNs (intraductal papillary mucinous neoplasms), surgical therapy is always recommended; for branch duct IPMNs, a number of different risk criteria are applicable to evaluate absolute or relative indications for surgery. Based on imaging characteristics of the most common cystic pancreatic lesions, a precise diagnostic classification of the tumor, as well as guidance for further treatment, is possible through radiology.
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BACKGROUND: Sarcopenia is an age-related syndrome characterized by a loss of muscle mass and strength. As a result, the independence of the elderly is reduced and the hospitalization rate and mortality increase. The onset of sarcopenia often begins in middle age due to an unbalanced diet or malnutrition in association with a lack of physical activity. This effect is intensified by concomitant diseases such as obesity or metabolic diseases including diabetes mellitus. METHOD: With effective preventative diagnostic procedures and specific therapeutic treatment of sarcopenia, the negative effects on the individual can be reduced and the negative impact on health as well as socioeconomic effects can be prevented. Various diagnostic options are available for this purpose. In addition to basic clinical methods such as measuring muscle strength, sarcopenia can also be detected using imaging techniques like dual X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and sonography. DXA, as a simple and cost-effective method, offers a low-dose option for assessing body composition. With cross-sectional imaging techniques such as CT and MRI, further diagnostic possibilities are available, including MR spectroscopy (MRS) for noninvasive molecular analysis of muscle tissue. CT can also be used in the context of examinations performed for other indications to acquire additional parameters of the skeletal muscles (opportunistic secondary use of CT data), such as abdominal muscle mass (total abdominal muscle area - TAMA) or the psoas as well as the pectoralis muscle index. The importance of sarcopenia is already well studied for patients with various tumor entities and also infections such as SARS-COV2. RESULTS AND CONCLUSION: Sarcopenia will become increasingly important, not least due to demographic changes in the population. In this review, the possibilities for the diagnosis of sarcopenia, the clinical significance, and therapeutic options are described. In particular, CT examinations, which are repeatedly performed on tumor patients, can be used for diagnostics. This opportunistic use can be supported by the use of artificial intelligence. KEY POINTS: · Sarcopenia is an age-related syndrome with loss of muscle mass and strength.. · Early detection and therapy can prevent negative effects of sarcopenia.. · In addition to DEXA, cross-sectional imaging techniques (CT, MRI) are available for diagnostic purposes.. · The use of artificial intelligence (AI) offers further possibilities in sarcopenia diagnostics.. CITATION FORMAT: · Vogele D, Otto S, Sollmann N etâal. Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. Fortschr Röntgenstr 2023; 195: 393â-â405.
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COVID-19 , Sarcopenia , Pessoa de Meia-Idade , Humanos , Idoso , Sarcopenia/diagnóstico por imagem , Sarcopenia/patologia , Inteligência Artificial , Relevância Clínica , RNA Viral , SARS-CoV-2 , Músculo Esquelético/diagnóstico por imagem , Músculo Esquelético/patologia , Absorciometria de Fóton/métodos , Teste para COVID-19RESUMO
BACKGROUND: Diagnosing synovial inflammation by administration of gadolinium-based contrast agents is limited by invasiveness and possible side effects, especially in children and adolescents. PURPOSE: We investigated diagnostic accuracy of diffusion-weighted (DWI) MRI with intravoxel incoherent motion (IVIM) imaging compared to contrast-enhanced MRI for detecting synovitis of the knee in a population of pediatrics and young adults. In addition we compared quantitative measures of synovial diffusion and perfusion to a group of healthy volunteers. METHODS: In this prospective study, 8 pediatric patients with 10 symptomatic knees (6 girls and 2 boys, mean age 13 years) with known or suspected synovitis underwent pre- and post-contrast 3.0 T MRI of the knee joint and additional DWI sequences between October 2016 and July 2019. For comparison we enrolled 5 healthy young adults (2 women and 3 men, median age 27 years) with contrast-free MRI of both knees. Post-contrast T1w images and DWI images at b = 1000s/mm2 with apparent diffusion coefficient (ADC) maps of patients were separately rated by two independent and blinded readers with different levels of experience for the presence or absence and degree of synovitis along with the level of confidence. We measured signal intensity on DWI of synovium, joint effusion and muscle with regions of interests and calculated the IVIM-parameters tissue diffusion coefficient (D) and perfusion fraction (f) for patients and volunteers. RESULTS: All patients showed at least some synovial contrast enhancement, 8 (80%) children knees were diagnosed with synovitis on contrast-enhanced (= ce)-T1w, the diagnostic standard. Ratings by the first and second reader on ce-T1w and DWI showed full agreement (kappa = 1) in diagnosing synovitis and substantial agreement (k = 0,655) for the degree of synovial enhancement. Interobserver agreement on DWI showed fair agreement (k = 0,220) between both readers. Diagnostic confidence was lower on DWI. Mean D- and f-values of muscle was comparable between patients and volunteers. Effusion mean D was higher, mean f was lower, synovial mean D was lower, mean f higher in patients than in volunteers. All differences were statistically significant (p < 0.001). CONCLUSIONS: Diffusion-weighted MRI with IVIM imaging remains a promising, though reader-dependent alternative to i.v. contrast-enhanced imaging in pediatric patients to reliably diagnose, or rule out, synovitis of the knee joint. We detected significantly restricted synovial diffusion and increased perfusion in patients compared to healthy volunteers. TRIAL REGISTRATION: Ethical Comitee University Hospital Ulm, Nr. 320/16.
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Sinovite , Masculino , Adolescente , Adulto Jovem , Humanos , Criança , Feminino , Adulto , Estudos Prospectivos , Projetos Piloto , Sinovite/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Articulação do Joelho/diagnóstico por imagemRESUMO
Orbital masses include a broad spectrum of benign and malignant entities. Often these masses are asymptomatic or show a slow growth rate, so that emergence of clinical symptoms is prolonged. In this context, cross-sectional imaging plays an elementary role in the characterization of these lesions. Aside from the characterization of the underlying entity, an evaluation of the involved compartments is possible by sufficient imaging, which also facilitates optimal treatment and surgery planning. The purpose of this review is to explore different benign and malignant orbital tumors and their typical appearance in imaging together with histopathologic findings.
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OBJECTIVES: Formalin-fixed paraffin-embedded (FFPE) tissue is the standard material for diagnostic pathology but poses relevant hurdles to accurate protein extraction due to cross-linking and chemical alterations. While numerous extraction protocols and chemicals have been described, systematic comparative analyses are limited. Various parameters were thus investigated in their qualitative and quantitative effects on protein extraction (PE) efficacy. Special emphasis was put on preservation of membrane proteins (MP) as key subgroup of functionally relevant proteins. METHODS: Using the example of urothelial carcinoma, FFPE tissue sections were subjected to various deparaffinization, protein extraction and antigen retrieval protocols and buffers as well as different extraction techniques. Performance was measured by protein concentration and western blot analysis of cellular compartment markers as well as liquid chromatography-coupled mass spectrometry (LC-MS). RESULTS: Commercially available extraction buffers showed reduced extraction of MPs and came at considerably increased costs. On-slide extraction did not improve PE whereas several other preanalytical steps could be simplified. Systematic variation of temperature and exposure duration demonstrated a quantitatively relevant corridor of optimal antigen retrieval. CONCLUSIONS: Preanalytical protein extraction can be optimized at various levels to improve unbiased protein extraction and to reduce time and costs.
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Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best.
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Benchmarking , Proteômica , Humanos , Proteoma/análise , Proteômica/métodos , Software , Fluxo de TrabalhoRESUMO
Osteoporosis is a highly prevalent systemic skeletal disease that is characterized by low bone mass and microarchitectural bone deterioration. It predisposes to fragility fractures that can occur at various sites of the skeleton, but vertebral fractures (VFs) have been shown to be particularly common. Prevention strategies and timely intervention depend on reliable diagnosis and prediction of the individual fracture risk, and dual-energy X-ray absorptiometry (DXA) has been the reference standard for decades. Yet, DXA has its inherent limitations, and other techniques have shown potential as viable add-on or even stand-alone options. Specifically, three-dimensional (3âD) imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), are playing an increasing role. For CT, recent advances in medical image analysis now allow automatic vertebral segmentation and value extraction from single vertebral bodies using a deep-learning-based architecture that can be implemented in clinical practice. Regarding MRI, a variety of methods have been developed over recent years, including magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) that enable the extraction of a vertebral body's proton density fat fraction (PDFF) as a promising surrogate biomarker of bone health. Yet, imaging data from CT or MRI may be more efficiently used when combined with advanced analysis techniques such as texture analysis (TA; to provide spatially resolved assessments of vertebral body composition) or finite element analysis (FEA; to provide estimates of bone strength) to further improve fracture prediction. However, distinct and experimentally validated diagnostic criteria for osteoporosis based on CT- and MRI-derived measures have not yet been achieved, limiting broad transfer to clinical practice for these novel approaches. KEY POINTS:: · DXA is the reference standard for diagnosis and fracture prediction in osteoporosis, but it has important limitations.. · CT- and MRI-based methods are increasingly used as (opportunistic) approaches.. · For CT, particularly deep-learning-based automatic vertebral segmentation and value extraction seem promising.. · For MRI, multiple techniques including spectroscopy and chemical shift imaging are available to extract fat fractions.. · Texture and finite element analyses can provide additional measures for vertebral body composition and bone strength.. CITATION FORMAT: · Sollmann N, Kirschke JS, Kronthaler S etâal. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. Fortschr Röntgenstr 2022; 194: 1088â-â1099.