Background and Objectives: Postoperative pancreatic fistula after cephalic pancreatoduodenectomy (CPD) is still the leading cause of postoperative morbidity, entailing long hospital stay and costs or even death. The aim of this study was to propose the use of morphologic parameters based on a preoperative multisequence computer tomography (CT) scan in predicting the clinically relevant postoperative pancreatic fistula (CRPF) and a risk score based on a multiple regression analysis. Materials and Methods: For 78 consecutive patients with CPD, we measured the following parameters on the preoperative CT scans: the density of the pancreas on the unenhanced, arterial, portal and delayed phases; the unenhanced density of the liver; the caliber of the main pancreatic duct (MPD); the preoperatively estimated pancreatic remnant volume (ERPV) and the total pancreatic volume. We assessed the correlation of the parameters with the clinically relevant pancreatic fistula using a univariate analysis and formulated a score using the strongest correlated parameters; the validity of the score was appreciated using logistic regression models and an ROC analysis. Results: When comparing the CRPF group (28.2%) to the non-CRPF group, we found significant differences of the values of unenhanced pancreatic density (UPD) (44.09 ± 6.8 HU vs. 50.4 ± 6.31 HU, p = 0.008), delayed density of the pancreas (48.67 ± 18.05 HU vs. 61.28 ± 16.55, p = 0.045), unenhanced density of the liver (UDL) (44.09 ± 6.8 HU vs. 50.54 ± 6.31 HU, p = 0.008), MPD (0.93 ± 0.35 mm vs. 3.14 ± 2.95 mm, p = 0.02) and ERPV (46.37 ± 10.39 cm³ vs. 34.87 ± 12.35 cm³, p = 0.01). Based on the odds ratio from the multiple regression analysis and after calculating the optimum cut-off values of the variables, we proposed two scores that both used the MPD and the ERPV and differing in the third variable, either including the UPD or the UDL, producing values for the area under the receiver operating characteristic curve (AUC) of 0.846 (95% CI 0.694–0.941) and 0.774 (95% CI 0.599–0.850), respectively. Conclusions: A preoperative CT scan can be a useful tool in predicting the risk of clinically relevant pancreatic fistula.

Objectives: Presently, data on the vascularization of the superficial musculoaponeurotic system of the face (SMAS) are lacking. Thus, the present study aimed to provide new conclusive data about the topography, density, and relationship of the SMAS blood vessels with other components, namely, the fibrous connective tissue and muscles. Methods: The study included a control lot of 42 cases from the archive of the radiology department. In this group, nuclear magnetic resonance angiography (MRA) was performed in order to identify the main sources of vascular supply. In the second group, tissue samples were collected from the midfacial region of 45 patients from the Oro-Maxillo-Facial and Plastic and Reconstructive Surgery clinics of ‘St. Spiridon’ County Clinical Emergency Hospital, Iasi. These patients received surgery for excision of tumoral formations that did not involve SMAS components. These samples underwent micro-CT analysis, hematoxylin and eosin (HE) staining, as well as immunohistochemical (IHC) staining for collagen type III, muscle tissue, and the vascular endothelium. Results: We discovered the particular way in which the SMAS components interrelate with vascularization and the regional differences between them. We have discovered a new vascular network specific to the SMAS, highlighted by both the micro-CT technique and microscopy on slides with special IHC staining. Significant differences were observed in the topographic arrangement, density, and relationships of the microscopic vasculature across midfacial regions. IHC staining provided morphological and functional information about the structure and vascularization of SMAS. Conclusions: The MRA technique could not detect the structural blood vessels of the SMAS and other methods for their in vivo visualization must be sought. The blood vessels of the SMAS mainly follow the topography of the muscle fibers. From the SMAS layer where they are found, the distribution branches reach the stroma of the region and the hypoderm. Our data can contribute to the development of surgical techniques tailored to each individual patient, as well as the enhancement of methods for stimulating cutaneous angiogenesis, improving scarring in this region, and advancing biotissue engineering techniques.