1. |
2. Tumor size and effectiveness of electrochemotherapyBarbara Mali, Damijan Miklavčič, Luca Giovanni Campana, Maja Čemažar, Gregor Serša, Marko Snoj, Tomaž Jarm, 2013, original scientific article Keywords: electrochemotherapy, cutaneous tumors, effectiveness, tumor size, meta-analysis
Published in DiRROS: 22.03.2024; Views: 95; Downloads: 30
 Full text (665,53 KB) |
3. Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometryTadej Tomanič, Luka Rogelj, Jošt Stergar, Boštjan Markelc, Tim Božič, Simona Kranjc Brezar, Gregor Serša, Matija Milanič, 2022, original scientific article Abstract: Understanding tumors and their micro-environment are essential for successfuland accurate disease diagnosis. Tissuephysiology and morphology are altered intumors compared to healthy tissues, andthere is a need to monitor tumors and their surrounding tissues, includingblood vessels, non-invasively. This preliminary study utilizes a multimodaloptical imaging system combining hyperspectral imaging (HSI) and three-dimensional (3D) optical profilometry (OP) to capture hyperspectral imagesand surface shapes of subcutaneously grown murine tumor models. Hyper-spectral images are corrected with 3D OP data and analyzed using the inverse-adding doubling (IAD) method to extract tissue properties such as melaninvolume fraction and oxygenation. Blood vessels are segmented using theB-COSFIRE algorithm from oxygenation maps. From 3D OP data, tumor vol-umes are calculated and compared to manual measurements using a verniercaliper. Results show that tumors can be distinguished from healthy tissuebased on most extracted tissue parameters (p<0:05). Furthermore, blood oxy-genation is 50% higher within the blood vessels than in the surrounding tissue,and tumor volumes calculated using 3D OP agree within 26% with manualmeasurements using a vernier caliper. Results suggest that combining HSI andOP could provide relevant quantitative information about tumors and improvethe disease diagnosis.
Keywords: medical physics, hyperspectral imaging, diffuse reflectance spectroscopy, blood vessels, tumors
Published in DiRROS: 08.09.2022; Views: 542; Downloads: 186
Full text (3,79 MB) |
4. Automated analysis of proliferating cells spatial organisation predicts prognosis in lung neuroendocrine neoplasmsMatteo Bulloni, Giada Sandrini, Irene Stacchiotti, M. Barberis, Fiorella Calabrese, Lina Carvalho, Gabriella Fontanini, Greta Alì, Francesco Fortarezza, Paul Hofman, Izidor Kern, 2021, original scientific article Keywords: neuroendocrine tumors, lung neoplasms, carcinoma, prognosis, pathology, histology, Ki-67 antigen, machine learning, image enhancement, lung cancer, neuroendocrine neoplasms
Published in DiRROS: 09.11.2021; Views: 802; Downloads: 344
 Link to file |
5. Morphologic and molecular classification of lung neuroendocrine neoplasmsJasna Metovic, Marco Barella, Fabrizio Bianchi, Paul Hofman, Veronique Hofman, Myriam Remmelink, Izidor Kern, Lina Carvalho, Linda Pattini, Angelica Sonzogni, 2021, original scientific article Abstract: Neuroendocrine neoplasms (NENs) of the lung encompass neuroendocrine tumors (NETs) composed of typical (TC) and atypical (AC) carcinoids and full-fledged carcinomas (NECs) inclusive of large cell neuroendocrine carcinoma (LCNEC) and small cell carcinoma (SCLC). NETs and NECs are thought to represent distinct and separate lesions with neither molecular overlap nor common developmental continuum. Two perspectives were addressed regarding the morphologic and molecular classification of lung NENs: (i) a supervised approach by browsing the traditional classification, the relevant gene alterations, and their clinical implications; and (ii) an unsupervised approach, by reappraising neoplasms according to risk factors and natural history of disease to construct an interpretation model relied on biological data. We herein emphasize lights and shadows of the current classification of lung NENs and provide an alternative outlook on these tumors focused on what we currently know about the biological determinants and the natural history of disease.
Keywords: neuroendocrine tumors, lung neoplasms, carcinoma, lung tumors, morphologic classification, molecular classification
Published in DiRROS: 02.02.2021; Views: 1152; Downloads: 763
Full text (2,60 MB)
This document has many files! More... |
6. Dynamic contrast-enhanced MRI of malignant pleural mesothelioma : a comparative study of pharmacokinetic models and correlation with mRECIST criteriaMartina Vivoda Tomšič, Sotirios Bisdas, Viljem Kovač, Igor Serša, Katarina Šurlan Popović, 2019, original scientific article Abstract: BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive thoracic malignancy that is difficult to cure. Dynamic contrast-enhanced (DCE) MRI is a functional imaging technique used to analyze tumor microvascular properties and to monitor therapy response. Purpose of this study was to compare two tracer kinetic models, the extended Tofts (ET) and the adiabatic approximation tissue homogeneity model (AATH) for analysis of DCE-MRI and examine the value of the DCE parameters to predict response to chemotherapy in patients with MPM. METHOD: This prospective, longitudinal, single tertiary radiology center study was conducted between October 2013 and July 2015. Patient underwent DCE-MRI studies at three time points: prior to therapy, during and after cisplatin-based chemotherapy. The images were analyzed using ET and AATH models. In short-term follow-up, the patients were classified as having disease control or progressive disease according to modified response evaluation criteria in solid tumors (mRECIST) criteria. Receiver operating characteristic curve analysis was used to examine specificity and sensitivity of DCE parameters for predicting response to therapy. Comparison tests were used to analyze whether derived parameters are interchangeable between the two models. RESULTS: Nineteen patients form the study population. The results indicate that the derived parameters are not interchangeable between the models. Significant correlation with response to therapy was found for AATH-calculated median pre-treatment efflux rate (kep) showing sensitivity of 83% and specificity of 100% (AUC 0.9). ET-calculated maximal pre-treatment kep showed 100% sensitivity and specificity for predicting treatment response during the early phase of the therapy and reached a favorable trend to significant prognostic value post-therapy. CONCLUSION: Both models show potential in predicting response to therapy in MPM. High pre-treatment kep values suggest MPM disease control post-chemotherapy.
Keywords: biomarker, magnetic resonance imaging, mesothelioma, perfusion, response evaluation criteria in solid
tumors, prognosis
Published in DiRROS: 23.09.2020; Views: 1293; Downloads: 950
Full text (3,44 MB)
This document has many files! More... |
