Jonas Henn’s research while affiliated with University of Bonn and other places

Purpose Artificial intelligence (AI) is transforming clinical decision-making (CDM). This application of AI should be a conscious choice to avoid technological determinism. The surgeons’ perspective is needed to guide further implementation. Methods We conducted an online survey among German surgeons, focusing on digitalization and AI in CDM, specifically for acute abdominal pain (AAP). The survey included Likert items and scales. Results We analyzed 263 responses. Seventy-one percentage of participants were male, with a median age of 49 years (IQR 41–57). Seventy-three percentage of participants carried out a senior role, with a median of 22 years of work experience (IQR 13–28). AI in CDM was seen as helpful for workload management (48%) but not for preventing unnecessary treatments (32%). Safety (95%), evidence (94%), and usability (96%) were prioritized over costs (43%) for the implementation. Concerns included the loss of practical CDM skills (81%) and ethical issues like transparency (52%), patient trust (45%), and physician integrity (44%). Traditional CDM for AAP was seen as experience-based (93%) and not standardized (31%), whereas AI was perceived to assist with urgency triage (60%) and resource management (59%). On median, generation Y showed more confidence in AI for CDM ( P = 0.001), while participants working in primary care hospitals were less confident ( P = 0.021). Conclusion Participants saw the potential of AI for organizational tasks but are hesitant about its use in CDM. Concerns about trust and performance need to be addressed through education and critical evaluation. In the future, AI might provide sufficient decision support but will not replace the human component.

Objectives The integration of advanced technologies is transforming surgical practice, particularly through robotic systems. This study presents the early clinical implementation of the Dexter ® surgical robot for cholecystectomy and evaluates clinical outcomes using the IDEAL framework. Methods Twenty patients underwent elective robotic-assisted cholecystectomy using the Dexter ® robot. A thorough implementation process, including rigorous surgeon and nurse training and standardized care protocols, was established. Data on operative metrics, complications, and patient outcomes were analyzed, and patient well-being was assessed via a postoperative phone survey. Results Six surgeons and thirty nurses were trained, with surgeons completing a minimum of 20 h of simulation. Preoperative and operative times were significantly reduced through this process. Comparing the first 10 operations to the second, docking time decreased from 11.4 ± 4.1 min to 7.1 ± 2.1 min (p=0.0144) and operative time improved from 130.5 ± 25.7 min to 99.7 ± 21.8 min (p=0.0134). Mean intraoperative blood loss was minimal, averaging 19.5 ± 31.4 mL, and the average length of hospital stay was 3.1 ± 1.4 days. Postoperative pain levels were low, and patient satisfaction was high, as assessed by telephone survey. Conclusions Our findings highlight the value of the IDEAL framework in guiding the systematic evaluation and implementation of new surgical technologies such as the Dexter ® robot. A structured approach is essential to improve patient outcomes and safety in the coming digital transformation of surgery.

Acute abdominal pain is a common presenting symptom in the emergency department and represents heterogeneous causes and diagnoses. There is often a decision to be made regarding emergency surgical care. Machine learning (ML) could be used here as a decision-support and relieve the time and personnel resource shortage. Patients with acute abdominal pain presenting to the Department of Surgery at Bonn University Hospital in 2020 and 2021 were retrospectively analyzed. Clinical parameters as well as laboratory values were used as predictors. After randomly splitting into a training and test data set (ratio 80 to 20), three ML algorithms were comparatively trained and validated. The entire procedure was repeated 20 times. A total of 1357 patients were identified and included in the analysis, with one in five (n = 276, 20.3%) requiring emergency abdominal surgery within 24 hours. Patients operated on were more likely to be male (p = 0.026), older (p = 0.006), had more gastrointestinal symptoms (nausea: p < 0.001, vomiting p < 0.001) as well as a more recent onset of pain (p < 0.001). Tenderness (p < 0.001) and guarding (p < 0.001) were more common in surgically treated patients and blood analyses showed increased inflammation levels (white blood cell count: p < 0.001, CRP: p < 0.001) and onset of organ dysfunction (creatinine: p < 0.014, quick p < 0.001). Of the three trained algorithms, the tree-based methods (h2o random forest and cforest) showed the best performance. The algorithms classified patients, i.e., predicted surgery, with a median AUC ROC of 0.81 and 0.79 and AUC PRC of 0.56 in test sets. A proof-of-concept was achieved with the development of an ML model for predicting timely surgical therapy for acute abdomen. The ML algorithm can be a valuable tool in decision-making. Especially in the context of heavily used medical resources, the algorithm can help to use these scarce resources more effectively. Technological progress, especially regarding artificial intelligence, increasingly enables evidence-based approaches in surgery but requires a strictly interdisciplinary approach. In the future, the use and handling of ML should be integrated into surgical training.

Purpose The detection of pancreatic cystic lesions (PCL) causes uncertainty for physicians and patients, and international guidelines are based on low evidence. The extent and perioperative risk of resections of PCL in Germany needs comparison with these guidelines to highlight controversies and derive recommendations. Methods Clinical data of 1137 patients who underwent surgery for PCL between 2014 and 2019 were retrieved from the German StuDoQ|Pancreas registry. Relevant features for preoperative evaluation and predictive factors for adverse outcomes were statistically identified. Results Patients with intraductal papillary mucinous neoplasms (IPMN) represented the largest PCL subgroup ( N = 689; 60.6%) while other entities (mucinous cystic neoplasms (MCN), serous cystic neoplasms (SCN), neuroendocrine tumors, pseudocysts) were less frequently resected. Symptoms of pancreatitis were associated with IPMN ( OR , 1.8; P = 0.012) and pseudocysts ( OR , 4.78; P < 0.001), but likewise lowered the likelihood of MCN ( OR , 0.49; P = 0.046) and SCN ( OR , 0.15, P = 0.002). A total of 639 (57.2%) patients received endoscopic ultrasound before resection, as recommended by guidelines. Malignancy was histologically confirmed in 137 patients (12.0%), while jaundice ( OR , 5.1; P < 0.001) and weight loss ( OR , 2.0; P = 0.002) were independent predictors. Most resections were performed by open surgery ( N = 847, 74.5%), while distal lesions were in majority treated using minimally invasive approaches ( P < 0.001). Severe morbidity was 28.4% ( N = 323) and 30d mortality was 2.6% ( N = 29). Increased age ( P = 0.004), higher BMI ( P = 0.002), liver cirrhosis ( P < 0.001), and esophageal varices ( P = 0.002) were independent risk factors for 30d mortality. Conclusion With respect to unclear findings frequently present in PCL, diagnostic means recommended in guidelines should always be considered in the preoperative phase. The therapy of PCL should be decided upon in the light of patient-specific factors, and the surgical strategy needs to be adapted accordingly.

Purpose An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various medical fields capitalized the application of machine learning (ML), and preliminary research suggests promising implications in surgeons’ workflow. Hence, we evaluated ML’s contemporary and possible future role in clinical decision-making (CDM) focusing on abdominal surgery. Methods Using the PICO framework, relevant keywords and research questions were identified. Following the PRISMA guidelines, a systemic search strategy in the PubMed database was conducted. Results were filtered by distinct criteria and selected articles were manually full text reviewed. Results Literature review revealed 4,396 articles, of which 47 matched the search criteria. The mean number of patients included was 55,843. A total of eight distinct ML techniques were evaluated whereas AUROC was applied by most authors for comparing ML predictions vs. conventional CDM routines. Most authors ( N = 30/47, 63.8%) stated ML’s superiority in the prediction of benefits and risks of surgery. The identification of highly relevant parameters to be integrated into algorithms allowing a more precise prognosis was emphasized as the main advantage of ML in CDM. Conclusions A potential value of ML for surgical decision-making was demonstrated in several scientific articles. However, the low number of publications with only few collaborative studies between surgeons and computer scientists underpins the early phase of this highly promising field. Interdisciplinary research initiatives combining existing clinical datasets and emerging techniques of data processing may likely improve CDM in abdominal surgery in the future.

Biliary tract cancer (BTC) refers to a heterogenous group of epithelial malignancies arising along the biliary tree. The highly aggressive nature combined with its silent presentation contribute to the dismal prognosis of this tumor. Tumor-infiltrating immune cells (TIICs) are frequently present in BTC and there is growing evidence regarding their role as therapeutic targets. In this study, we analyzed the immune cell infiltration in BTC and developed a promising immune signature score to predict prognosis in BTC. Immunohistochemistry (IHC) was carried out on tissue microarray sections from 45 patients with resectable cholangiocarcinoma for the detection of 6-sulfoLacNAc+ monocytes (slanMo), BDCA-2+ plasmacytoid dendritic cells (pDC), CD8+ or CD4+T-lymphocytes, CD103+ cells, GATA3+ cells, Toll-like receptor (TLR) 3, 7 and 9-expressing cells as well as programmed cell death protein 1 and programmed cell death ligand 1 positive cells. Data from the IHC staining were analyzed and correlated with clinicopathological and survival data. High expression of TLR7, TLR9, and GATA3 was associated with improved overall survival (OS, Log-rank p < 0.05). In addition, TLR9 was associated with better disease-free survival (Log-rank p < 0.05). In the multivariate Cox proportional-hazards model for OS, the TLR/TLR9/GATA3 score was found to be an independent prognostic factor for OS (“Score 2” vs. “Score 0”: HR 11.17 95% CI 2.27–54.95, p < 0.01).

Biliary tract cancer (BTC) is characterized by an intense stromal reaction and a complex landscape of infiltrating immune cells. Evidence is emerging that tumor-infiltrating neutrophils (TINs) have an impact on carcinogenesis and tumor progression. TINs have also been associated with outcomes in various solid malignant tumors but their possible clinical role in BTC is largely unknown. Tissue samples from patients with sporadic BTC (“spBTC” cohort, N = 53) and BTC in association with primary sclerosing cholangitis (“PSC-BTC” cohort, N = 7) were collected. Furthermore, tissue samples from 27 patients with PSC who underwent liver transplantation (“PSC-LTX” cohort) were investigated. All specimens were assessed for TIN density in invasive and precancerous lesions (biliary intraepithelial neoplasia, BilIN). Most spBTC showed low TIN density (LD, 61%). High TIN density (HD) was detected in 16% of the tumors, whereas 23% were classified as intermediate density (ID); the majority of both HD and ID groups were in T1–T2 tumors (83% and 100%, p = 0.012). TIN density in BilIN lesions did not significantly differ among the three groups. The HD group had a mean overall survival (OS) of 53.5 months, whereas the mean OS in the LD and ID groups was significantly shorter (LD 29.5 months vs. ID 24.6 months, log-rank p < 0.05). The results of this study underline the possible prognostic relevance of TINs in BTC and stress the complexity of the immune cell landscape in BTC. The prognostic relevance of TINs suggests a key regulator role in inflammation and immune landscape in BTC.

Background: Severe acute pancreatitis (SAP) is a heterogeneous and life-threatening disease. While recent guidelines recommend a stepwise approach starting with non-surgical techniques, emergency laparotomy remains inevitable in certain situations. Open abdomen treatment (OAT) may follow, potentially resulting in additional risks for severe morbidity. Causative factors and clinical impact of OAT in SAP are poorly understood and therefore issue of the present study. Materials and Methods: A retrospective analysis of patients admitted to the Department of General, Visceral, Thoracic and Vascular Surgery at University of Bonn suffering from acute pancreatitis (ICD K.85) between 2005 and 2020 was performed. Medical records were screened for demographic, clinical and outcome parameters. Patients who received primary fascial closure (PFC) were compared to those patients requiring OAT. SAP-specific scores were calculated, and data statistically analyzed ( P = 0.05). Results: Among 430 patients included, 54 patients (13%) had to undergo emergency laparotomy for SAP. Patients were dominantly male (72%) with a median age of 51 years. Indications for surgery were infected necrosis (40%), suspected bowel perforation (7%), abdominal compartment syndrome (5%), and acute intra-abdominal hemorrhage (3%). While 22 patients (40%) had PFC within initial surgery, 33 patients (60%) required OAT including a median of 12 subsequent operations (SD: 6, range: 1–24). Compared to patients with PFC, patients in the OAT group had significantly fewer biliary SAP ( P = 0.031), higher preoperative leukocyte counts ( P = 0.017), higher rates of colon resections ( P = 0.048), prolonged ICU stays ( P = 0.0001), and higher morbidity according to Clavien–Dindo Classification ( P = 0.002). Additionally, BISAP score correlated positively with the number of days spent at ICU and morbidity ( P = 0.001 and P = 0.000002). Both groups had equal mortality rates. Discussion: Our data suggest that preoperative factors in surgically treated SAP may indicate the need for OAT. The procedure itself appears safe with equal hospitalization days and mortality rates compared to patients with PFC. However, OAT may significantly increase morbidity through longer ICU stays and more bowel resections. Thus, minimally invasive options should be promoted for an uncomplicated and rapid recovery in this severe disease. Emergency laparotomy will remain ultima ratio in SAP while patient selection seems to be crucial for improved clinical outcomes.