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Volumetric Imaging Follow up of Patients With Liver Metastases of Small Intestinal Neuroendocrine Tumors (NETs).

ABSTRACT: More than 50% of intestinal NETs are metastatic at the time of diagnosis, the liver being the main affected organ in 50-90% of cases. Initial liver tumor burden and slope of the tumor growth rate are two major prognostic factors in patients with intestinal NETs, followed by tumor grade at pathology. They are used in routine practice by oncologists to adapt patient treatment. Unlike other tumors, most NETs metastases are slow-growing tumors. Previous studies have shown that approximately half of the patients diagnosed with liver metastases showed no progression over a period of 3 to 6 months. The aim of this non randomised retrospective cohort study is to investigate whether the volumetric monitoring of the total tumor burden compared to the RECIST 1.1 criteria (used in routine practice by radiologists) at baseline and early follow-up (3 to 6 months) is more suitable for NETs, making possible to predict the prognosis at the onset of the disease, and also allowing a better adaptation of the treatment. The secondary objectives are to evaluate if the initial volume of the liver tumor is a prognostic factor of time to progression, to correlate the initial liver tumor volume and the number of liver lesions to the blood concentration of Chromogranin A (CgA), the presence of extra-abdominal disease and to correlate the tumor growth rate (TGR) and KI 67 (%) at base-line.

DISEASE(S): Neuroendocrine Tumors,Neoplasm Metastasis,Liver Metastases,Liver Neoplasms

PROVIDER: 2285529 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models Natalie Kronik1¤, Yuri Kogan1, Moran Elishmereni1, Karin Halevi-Tobias1, Stanimir Vuk-Pavlovic ́2.,Zvia Agur1*.1Institute for Medical BioMathematics, Bene Ataroth, Israel,2College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America Abstract Background:Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients.We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simplemathematical models.Methodology/Principal Findings:We developed a general mathematical model encompassing the basic interactions of avaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cellvaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes inprostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were dividedinto each patient’s training set and his validation set. The training set, used for model personalization, contained thepatient’s initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized modelswere simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set.The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients(the coefficient of determination between the predicted and observed PSA values wasR2= 0.972). The model could notaccount for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validatedpersonalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccinationregimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Conclusions/Significance:Using a few initial measurements, we constructed robust patient-specific models of PCaimmunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value andfeasibility of individualized model-suggested immunotherapy protocols.

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Volumetric Imaging Follow up of Patients With Liver Metastases of Small Intestinal Neuroendocrine Tumors (NETs).

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