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NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

PRIMAGE is a European Commission-financed project dealing with medical imaging and artificial intelligence aiming to create an imaging biobank in oncology. The project includes a task dedicated to the interoperability between imaging and standard biobanks. We aim at linking Digital imaging and Communications in Medicine (DICOM) metadata to the Minimum Information About BIobank data Sharing (MIABIS) standard of biobanking. A very first integration model based on the fusion of the two existing standards, MIABIS and DICOM, has been developed. The fundamental method was that of expanding the MIABIS core to the imaging field, adding DICOM metadata derived from CT scans of 18 paediatric patients with neuroblastoma. The model was developed with the relational database management system Structured Query Language. The integration data model has been built as an Entity Relationship Diagram, commonly used to organise data within databases. Five additional entities have been linked to the “Image Collection” subcategory in order to include the imaging metadata more specific to the particular type of data: Body Part Examined, Modality Information, Dataset Type, Image Analysis, and Registration Parameters. The model is a starting point for the expansion of MIABIS with further DICOM metadata, enabling the inclusion of imaging data in biorepositories.

BACKGROUND ‘Splenosis’ is defined as the autotransplantation of splenic tissue following trauma or surgery, usually in the form of intraperitoneal nodules. The proliferation of imaging techniques has resulted in increased unexpected discoveries of splenosis nodules, and achieving a differential diagnosis can be challenging. Nuclear medicine studies have been playing an increasingly important role in this process, but the clinical significance of asymptomatic nodules remains uncertain. CASE SUMMARY We present a case of pelvic splenosis in a 73-year-old man diagnosed 56 years after a splenectomy during a computed tomography (CT) follow-up for B-cell lymphoma, presenting intense contrast enhancement of an 18 mm nodule in the right recto-vesical space. 18F-fluorodeoxyglucose demonstrated weak metabolic activity. Since histological diagnosis was deemed necessary, the nodule was easily removed with robotically assisted laparoscopy, together with another 6 mm left a paracolic lesion. The latter was previously undiagnosed but retrospectively visible on the CT scan. CONCLUSION In a patient requiring differential diagnosis of splenosis nodules from lymphoma recurrence, the robotic approach provided a safe en bloc removal with short hospitalization. The Da Vinci Xi robot was particularly helpful because its optics can be introduced from all ports, facilitating visualization and lysis of multiple intra-abdominal adhesions