Background: Perforator mapping has been well described in the literature. Once the suprafascial plane is reached, the course of perforators is considered constant. However, the surgeon must be aware of whether an anastomosis exists between perforators superficially to the fascia, in order to choose the best vessel upon which to base the reconstruction. Our retrospective in vivo anatomical study of lower leg perforator flaps presents the first description of variations in the suprafascial path of perforators, which may influence preoperative flap design. Methods: An anatomical study of lower limb perforators was performed on 46 nonconsecutive patients who were referred to our department from June 2012 to October 2018. Reconstruction with perforator-based propeller flaps was planned for each of the patients. In total, 72 perforators were preoperatively identified and surgically isolated. The suprafascial course of each perforator was reported. Results: During suprafascial surgical exploration, branching patterns were observed in four perforators. These perforators had been classified as single vessels in the preoperative ultrasonographic analysis. However, after surgical dissection, distal converging branches were noted in two of them. Conclusions Our study is the first description in the literature of suprafascial converging perforators, which might constitute an obstacle to planned reconstruction procedures. Despite the accuracy of preoperative evaluations, anatomical variations were present. Knowledge of suprafascial perforator variations may help surgeons to choose the correct perforator upon which to base a planned flap.

Upper limb nerve damage is a common condition, and evidence suggests that functional recovery may be limited following peripheral nerve repair in cases of delayed reconstruction or reconstruction of long nerve defects. A 26-year-old man presented with traumatic injury from a wide, blunt wound of the right forearm caused by broken glass, with soft tissue loss, complete transection of the radial and ulnar arteries, and a large median nerve gap. The patient underwent debridement and subsequent surgery with a microsurgical free radial fasciocutaneous flap to provide a direct blood supply to the hand; the cephalic vein within the flap was employed as a venous vascularized chamber to wrap the sural nerve graft and to repair the wide gap (14 cm) in the median nerve. During the postoperative period, the patient followed an intensive rehabilitation program and was monitored for functional performance over 5 years of follow-up. Our assessment demonstrated skin tropism and sufficient muscle power to act against strong resistance (M5) in the muscles previously affected by paralysis, as well as a good localization of stimuli in the median nerve region and an imperfect recovery of two-point discrimination (S3+). We propose a novel and efficient procedure to repair >10-cm peripheral nerve gap injuries related to upper limb trauma.

BACKGROUND: Breast cancer is complicated by a high incidence of chronic postoperative pain (25%–60%). Regional anesthesia might play an important role in lowering the incidence of chronic pain; however it is not known if the pectoral nerve block (PECS block), which is commonly used for breast surgery, is able to prevent this complication. Our main objective was therefore to detect any association between the PECS block and chronic pain at 3, 6, 9, and 12 months in patients undergoing breast surgery. METHODS: We conducted a prospective, monocentric, observational study. We enrolled 140 consecutive patients undergoing breast surgery and divided them in patients receiving a PECS block and general anesthesia (PECS group) and patients receiving only general anesthesia (GA group). Then we considered both intraoperative variables (intravenous opioids administration), postoperative data (pain suffered by the patients during the first 24 postoperative hours and the need for additional analgesic administration) and development and persistence of chronic pain (at 3, 6, 9, and 12 mo). RESULTS: The PECS group had a lower incidence of chronic pain at 3 months (14.9% vs. 31.8%, P = 0.039), needed less intraoperative opioids (fentanyl 1.61 μg/kg/hr vs. 3.3 μg/kg/hr, P < 0.001) and had less postoperative pain (3 vs. 4, P = 0.017). CONCLUSIONS: The PECS block might play an important role in lowering incidence of chronic pain, but further studies are needed.
Analgesics, Opioid ; Anesthesia, Conduction ; Anesthesia, General ; Anesthesia, Local ; Breast Neoplasms ; Breast ; Chronic Pain ; Clinical Study ; Humans ; Incidence ; Nerve Block ; Observational Study ; Pain, Postoperative ; Prospective Studies ; Thoracic Nerves

No abstract available.
Dermoscopy* ; Nipples* ; Paget's Disease, Mammary*

OBJECTIVES: We analyzed the outcomes following clinical management of parotid masses that were determined to be malignant tumors after parotidectomy. METHODS: We evaluated data from 70 patients with parotid malignancies between November 1994 and December 2005. RESULTS: Among salivary histotypes (n=49), the most significant prognostic parameter was cT4 stage at diagnosis (P=0.0055, log-rank) both for clinical involvement of the facial nerve and for invasion of other structures. The main cause of cancer-related death was a distant metastasis. CONCLUSION: The present series confirms that the main prognostic parameter in salivary parotid malignancies was cT4 classification at diagnosis, often due to clinical involvement of the facial nerve. The oncological outcome of salivary malignancies was influenced by distant metastasis more than most other head and neck sites. We recommend dissecting and preserving the functioning VIIth cranial nerve during surgery for parotid malignancies.
Classification ; Cranial Nerves ; Diagnosis ; Facial Nerve* ; Head ; Humans ; Neck ; Neoplasm Metastasis ; Parotid Gland*

Colorectal cancer is an important cause of morbidity and mortality worldwide. Optical colonoscopy (OC) is widely accepted as the reference standard for the screening of colorectal polyps and cancers, and computed tomography colonography (CTC) is a valid alternative to OC. The purpose of this review was to assess the diagnostic accuracy of OC and CTC for colorectal lesions. A literature search was performed in PubMed, Embase, and Cochrane Library, and 18 articles were included. CTC has emerged in recent years as a potential screening examination with high accuracy for the detection of colorectal lesions. However, the clinical application of CTC as a screening technique is limited because it is highly dependent on the size of the lesions and has poor performance in detecting individual lesions <5 mm or flat lesions, which, although rarely, can have a malignant potential.

Purpose: To explore the role of artificial intelligence and machine learning (ML) techniques in oncological urology. In recent years, our group investigated the prostate cancer gene 3 (PCA3) score, prostate-specific antigen (PSA), and free-PSA predictive role for prostate cancer (PCa), using the classical binary logistic regression (LR) modeling. In this research, we approached the same clinical problem by several different ML algorithms, to evaluate their performances and feasibility in a real-world evidence PCa detection trial. Materials and Methods: The occurrence of a positive biopsy has been studied in a large cohort of 1,246 Italian men undergoing first or repeat biopsy. Seven supervised ML algorithms were selected to build biomarkers-based predictive models: generalized linear model, gradient boosting machine, eXtreme gradient boosting machine (XGBoost), distributed random forest/ extremely randomized forest, multilayer artificial Deep Neural Network, naïve Bayes classifier, and an automatic ML ensemble function. Results: All the ML models showed better performances in terms of area under curve (AUC) and accuracy, when compared to LR model. Among them, an XGBoost model tuned by the autoML function reached the best metrics (AUC, 0.830), well overtaking LR results (AUC, 0.738). In the variable importance ranking coming from this XGBoost model (accuracy, 0.824), the PCA3 score importance was 3-fold and 4-fold larger, when compared to that of free-PSA and PSA, respectively. Conclusions The ML approach proved to be feasible and able to achieve good predictive performances with reproducible results: it may thus be recommended, when applied to PCa prediction based on biomarkers fluctuations.

We reported a successful case management of G3 skin acute dermatitis in a 32-year-old woman affected by locally advanced breast cancer underwent adjuvant chest wall irradiation. Skin acute toxicity with dry desquamation areas was treated daily with dressing medication using physiological solution, oxygen therapy and applying hyaluronic acid gauze. At the end of radiotherapy treatment, G3 skin acute dermatitis with moist desquamation was observed, so the patient continued advanced wound dressing shifted to twice weekly with physiological solution, oxygen therapy and applying hydrocolloid dressing. The patient completed radiotherapy treatment without interruption and one month after treatment acute skin toxicity was resolved with pain relief. We suggest that advanced dressing with trained nursing staff is essential in this sub-set of patients due to guaranteed continuation of radiotherapy treatment, indispensable to ensure patient cure.

Purpose: To explore the role of artificial intelligence and machine learning (ML) techniques in oncological urology. In recent years, our group investigated the prostate cancer gene 3 (PCA3) score, prostate-specific antigen (PSA), and free-PSA predictive role for prostate cancer (PCa), using the classical binary logistic regression (LR) modeling. In this research, we approached the same clinical problem by several different ML algorithms, to evaluate their performances and feasibility in a real-world evidence PCa detection trial. Materials and Methods: The occurrence of a positive biopsy has been studied in a large cohort of 1,246 Italian men undergoing first or repeat biopsy. Seven supervised ML algorithms were selected to build biomarkers-based predictive models: generalized linear model, gradient boosting machine, eXtreme gradient boosting machine (XGBoost), distributed random forest/ extremely randomized forest, multilayer artificial Deep Neural Network, naïve Bayes classifier, and an automatic ML ensemble function. Results: All the ML models showed better performances in terms of area under curve (AUC) and accuracy, when compared to LR model. Among them, an XGBoost model tuned by the autoML function reached the best metrics (AUC, 0.830), well overtaking LR results (AUC, 0.738). In the variable importance ranking coming from this XGBoost model (accuracy, 0.824), the PCA3 score importance was 3-fold and 4-fold larger, when compared to that of free-PSA and PSA, respectively. Conclusions The ML approach proved to be feasible and able to achieve good predictive performances with reproducible results: it may thus be recommended, when applied to PCa prediction based on biomarkers fluctuations.