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Enfermedad de Erdheim-Chester , Histiocitosis Sinusal , Humanos , Enfermedad de Erdheim-Chester/diagnóstico por imagen , Enfermedad de Erdheim-Chester/tratamiento farmacológico , Histiocitosis Sinusal/diagnóstico , Biopsia Líquida , Mutación/genética , Proteínas Proto-Oncogénicas B-raf/genéticaRESUMEN
We report an uncommon, infratentorial localization of adult H3 K27M-altered diffuse midline glioma arising in a particularly rare site (medulla oblongata). In addition to this unusual presentation, the lesion exhibited a substantial contrast enhancement and size decrease after dexamethasone, generating diagnostic dilemmas. Histology, molecular details, advanced Magnetic Resonance imaging features and differential diagnoses are here described and discussed, as well as common misconceptions about steroid-sensitive mass lesions, and practical difficulties for clinicians involved in the process of making diagnosis.
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Objective: The aim of the current review is to summarize the available evidence to aid clinicians in the surveillance, treatment and follow-up of the different primary tumors developed by patients diagnosed with von Hippel-Lindau (VHL) syndrome. Methods: A non-systematic narrative review of original articles, meta-analyses, and randomized trials was conducted, including articles in the pre-clinical setting to support relevant findings. Results: VHL disease is the most common rare hereditary disorder associated with clear cell renal cell carcinoma. Affected individuals inherit a germline mutation in one VHL allele, and any somatic event that disrupt the other allele can trigger mutations, chromosomal rearrangements, or epigenetic regulations leading to oncogenesis. From a clinical perspective, patients continuously develop multiple primary tumors. Conclusion: Because VHL is considered a rare disease, very limited evidence is available for diagnosis, surveillance, active treatment with local or systemic therapy and follow-up.
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Endoscopic ultrasound-ablation with HybridTherm-Probe (EUS-HTP) significantly reduces tumour volume (TV) in locally-advanced pancreatic ductal adenocarcinoma (LA-PDAC). We aimed at investigating the clinical efficacy of EUS-HTP plus chemotherapy versus chemotherapy (HTP-CT and CT arms) in LA- and borderline-resectable (BR) PDAC, with 6-months progression-free survival (6-PFS) rate as primary endpoint. In a phase-II randomized-controlled-trial, 33 LA/BR-PDAC patients per-arm were planned to verify 20% improved 6-PFS rate. Radiological response (Choi criteria), TV and serum CA19.9 were assessed up to 6-months. Seventeen and 20 LA/BR-PDAC patients were randomized to HTP-CT or CT. Baseline and CT-related features were balanced. At 6-months, 6-PFS rate was 41.2% and 30% in HTP-CT and CT arms (p = 0.48), respectively. A decrease ≥50% of serum CA19.9 was achieved in 75% and 64.3% of HTP-CT and CT patients (p = 0.53), respectively. TV reduced up to 6-months in 64.3% and 47.1% of HTP-CT and CT patients (p = 0.35), respectively. Resection rate, PFS-time and overall survival (OS-time) were similar. HTP-CT achieves a non-significant 11.2%, 10.7% and 17.2% improved 6-PFS, CA19.9 decrease ≥50% and TV reduction rates over CT, without any impact on resection rate, PFS-time and OS-time. As the study was underpowered, these results suggest further investigation of EUS-local ablation in selected patients with localized disease after induction CT.
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Background Missing MRI sequences represent an obstacle in the development and use of deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing brain MRI scans using generative adversarial networks (GANs) allows for the use of a DL model for brain lesion segmentation that requires T1-weighted images, postcontrast T1-weighted images, fluid-attenuated inversion recovery (FLAIR) images, and T2-weighted images. Materials and Methods In this retrospective study, brain MRI scans obtained between 2011 and 2019 were collected, and scenarios were simulated in which the T1-weighted images and FLAIR images were missing. Two GANs were trained, validated, and tested using 210 glioblastomas (GBMs) (Multimodal Brain Tumor Image Segmentation Benchmark [BRATS] 2017) to generate T1-weighted images from postcontrast T1-weighted images and FLAIR images from T2-weighted images. The quality of the generated images was evaluated with mean squared error (MSE) and the structural similarity index (SSI). The segmentations obtained with the generated scans were compared with those obtained with the original MRI scans using the dice similarity coefficient (DSC). The GANs were validated on sets of GBMs and central nervous system lymphomas from the authors' institution to assess their generalizability. Statistical analysis was performed using the Mann-Whitney, Friedman, and Dunn tests. Results Two hundred ten GBMs from the BRATS data set and 46 GBMs (mean patient age, 58 years ± 11 [standard deviation]; 27 men [59%] and 19 women [41%]) and 21 central nervous system lymphomas (mean patient age, 67 years ± 13; 12 men [57%] and nine women [43%]) from the authors' institution were evaluated. The median MSE for the generated T1-weighted images ranged from 0.005 to 0.013, and the median MSE for the generated FLAIR images ranged from 0.004 to 0.103. The median SSI ranged from 0.82 to 0.92 for the generated T1-weighted images and from 0.76 to 0.92 for the generated FLAIR images. The median DSCs for the segmentation of the whole lesion, the FLAIR hyperintensities, and the contrast-enhanced areas using the generated scans were 0.82, 0.71, and 0.92, respectively, when replacing both T1-weighted and FLAIR images; 0.84, 0.74, and 0.97 when replacing only the FLAIR images; and 0.97, 0.95, and 0.92 when replacing only the T1-weighted images. Conclusion Brain MRI scans generated using generative adversarial networks can be used as deep learning model inputs in case MRI sequences are missing. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Zhong in this issue. An earlier incorrect version of this article appeared online. This article was corrected on April 12, 2021.
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Neoplasias Encefálicas/diagnóstico por imagen , Aprendizaje Profundo , Glioblastoma/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Linfoma/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Anciano , Medios de Contraste , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estudios RetrospectivosRESUMEN
PURPOSE: To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET). METHODS: panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann-Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF. RESULTS: Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27 mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80-0.85). Conventional CT 'necrosis' could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and 'arterial vascular invasion' for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion. CONCLUSIONS: Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization. TRIAL REGISTRATION NUMBER: NCT03967951, 30/05/2019.
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Ganglios Linfáticos/patología , Estadificación de Neoplasias/métodos , Neoplasias Pancreáticas/diagnóstico , Adulto , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Metástasis Linfática , Masculino , Persona de Mediana Edad , Neoplasias Pancreáticas/secundario , Curva ROC , Estudios Retrospectivos , Tomografía Computarizada por Rayos X/métodosRESUMEN
Emapalumab, a fully human anti-IFNγ monoclonal antibody, has been approved in the US as second-line treatment of primary hemophagocytic lymphohistiocytosis (HLH) patients and has shown promise in patients with graft failure (GF) requiring a second allogeneic hematopoietic stem cell transplantation (HSCT). The blockade of IFNγ activity may increase the risk of severe infections, including fatal mycobacteriosis. We report a case of secondary HLH-related GF in the context of HLA-haploidentical HSCT successfully treated with emapalumab in the presence of concomitant life-threatening infections, including disseminated tuberculosis (TB). A 4 years old girl with Adenosine Deaminase-Severe Combined Immunodeficiency complicated by disseminated TB came to our attention for ex-vivo hematopoietic stem cell-gene therapy. After engraftment failure of gene corrected cells, she received two HLA-haploidentical T-cell depleted HSCT from the father, both failed due to GF related to concomitant multiple infections and secondary HLH. Emapalumab administration allowed to control HLH, as well as to prevent GF after a third haplo-HSCT from the mother. Remarkably, all infections improved with antimicrobial medications and disseminated TB did not show any reactivation. This seminal case supports emapalumab use for treatment of secondary HLH and prevention of GF in patients undergoing haplo-HSCT even in the presence of multiple infections, including TB.
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Trasplante de Células Madre Hematopoyéticas , Linfohistiocitosis Hemofagocítica , Inmunodeficiencia Combinada Grave , Tuberculosis , Adenosina Desaminasa , Agammaglobulinemia , Anticuerpos Monoclonales/uso terapéutico , Anticuerpos Neutralizantes , Vacuna BCG , Preescolar , Femenino , Trasplante de Células Madre Hematopoyéticas/efectos adversos , Humanos , Linfohistiocitosis Hemofagocítica/tratamiento farmacológico , Linfohistiocitosis Hemofagocítica/etiología , Inmunodeficiencia Combinada Grave/complicaciones , Inmunodeficiencia Combinada Grave/tratamiento farmacológico , Tuberculosis/complicaciones , Tuberculosis/tratamiento farmacológicoRESUMEN
Background and study aims Endoscopic ultrasound (EUS)-guided ablation of pancreatic ductal adenocarcinoma (PDAC) with HybridTherm-Probe (EUS-HTP) is feasible and safe, but the radiological response and ideal tool to measure it have not been investigated yet. The aims of this study were to: 1) assess the radiological response to EUS-HTP evaluating the vital tumor volume reduction rate, Response Evaluation Criteria in Solid Tumors (RECIST1.1) and Choi criteria; 2) determine the prognostic predictive yield of these criteria. Patients and methods A retrospective analysis was performed of patients with locally advanced PDAC after primary treatment or unfit for chemotherapy prospectively treated by EUS-HTP. Computed tomography scan was performed 1 month after EUS-HTP to evaluate: 1) vital tumor volume reduction rate (VTVRR) by measuring necrosis and tumor volumes through a computer-aided detection system; and 2) RECIST1.1 and Choi criteria. Results EUS-HTP was feasible in 22 of 31 patients (71â%), with no severe adverse events. Median post-HTP survival was 7 months (1â-â35). Compared to pre-HTP tumor volume, a significant 1-month VTVRR (mean 21.4â%) was observed after EUS-HTP ( P â=â0.005). We identified through ROC analysis a VTVRRâ>â11.46â% as the best cut-off to determine post-HTP 6-month survival outcome (AUCâ=â0.733; sensitivityâ=â70.0â%, specificityâ=â83.3â%). This cut-off was significantly associated with longer overall survival (HRâ=â0.372; P â=â0.039). According to RECIST1.1 and Choi criteria, good responders to EUS-HTP were 60â% and 46.7â%, respectively. Good responders according to Choi, but not to RECIST1.1, had longer survival (HRâ=â0.407; P â=â0.04). Conclusions EUS-HTP induces a significant 1-month VTVRR. This effect is assessed accurately by evaluation of necrosis and tumor volumes. Use of VTVRR and Choi criteria, but not RECIST 1.1 criteria, might identify patients who could benefit clinically from EUS-HTP.
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In the present case, we report the first experience of a patient with high-grade glioma who underwent dual F-FAZA PET/CT imaging for intratumoral hypoxia assessment, before treatment, and for therapy monitoring in the suspicious of recurrence, as part of a clinical research protocol. In addition, despite the diagnosis of glioblastoma, the patient at 3 years from diagnosis was alive and underwent C-methionine simultaneous PET/MRI for disease monitoring after treatment, showing stability of disease. The multitracer capability of PET in assessing different and complementary metabolic features along with the use of a last-generation scanner as PET/MRI in brain oncology are here enlighten.
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Aminoácidos/metabolismo , Glioma/diagnóstico por imagen , Imagen por Resonancia Magnética , Metionina , Nitroimidazoles , Tomografía Computarizada por Tomografía de Emisión de Positrones , Hipoxia Tumoral , Adulto , Femenino , Glioma/metabolismo , Glioma/patología , Humanos , Masculino , Persona de Mediana Edad , Clasificación del TumorRESUMEN
PURPOSE: The aim of this study was to quantify the impact of CT delineation uncertainty of pancreatic neuroendocrine neoplasms (panNEN) on Radiomic features (RF). METHODS: Thirty-one previously operated patients were considered. Three expert radiologists contoured panNEN lesions on pre-surgical high-resolution contrast-enhanced CT images and contours were transferred onto pre-contrast CT. Volume agreement was quantified by the DICE index. After images resampling and re-binning, 69 RF were extracted and the impact of inter-observer variability was assessed by Intra-Class Correlation (ICC): ICCâ¯>â¯0.80 was considered as a threshold for "very high" inter-observer agreement. RESULTS: The median volume was 1.3â¯cc (range: 0.2-110â¯cc); a satisfactory inter-observer volume agreement was found (mean DICEâ¯=â¯0.78). Only 4 RF showed ICCâ¯<â¯0.80 (0.48-0.73), including asphericity and three RFs (of five) of the neighborhood intensity difference matrix (NID). CONCLUSIONS: The impact of inter-observer variability in delineating panNEN on RF was minimum, with the exception of the NID family and asphericity, showing a moderate agreement. These results support the feasibility of studies aiming to assess CT radiomic biomarkers for panNEN.