Robots down-under: the current climate of robotic-assisted surgery education in Australia.

Australia has seen a significant rise in the use of Robotic-Assisted Surgery (RAS), with general surgery being the fastest-growing field in this technology. The proportion of general surgical RAS has grown from 1% to 17% of all RAS between 2008 and 2023 in Australasia. As of May 2023, there were 162 robotic platforms in Australasia, with 26 of them in the public sector. As the cost of establishing RAS decreases over time, public hospital robotics systems are expected to become more accessible. Despite the increasing demand, many specialties, including general surgery, do not have an agreed RAS curriculum for trainees. It is imperative for Australia to develop its own curriculum akin to our overseas colleagues to match this growth.

Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients.

INTRODUCTION: This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) region in colorectal cancer (CRC) patients. METHODS: A total of 541 axial CT slices at the L3 vertebra were retrospectively collected from 319 patients with CRC diagnosed during 2012-2019 at a single Australian tertiary institution, Western Health in Melbourne. A two-dimensional U-Net convolutional network was trained on 338 slices to segment muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Manual reading of these same slices of muscle, VAT and SAT was created to serve as ground truth data. The Dice similarity coefficient was used to assess the U-Net-based segmentation performance on both a validation dataset (68 slices) and a test dataset (203 slices). The measurement of cross-sectional area and Hounsfield unit (HU) density of muscle, VAT and SAT were compared between two methods. RESULTS: The segmentation for muscle, VAT and SAT demonstrated excellent performance for both the validation (Dice similarity coefficients >0.98, respectively) and test (Dice similarity coefficients >0.97, respectively) datasets. There was a strong positive correlation between manual and AI segmentation measurements of body composition for both datasets (Spearman's correlation coefficients: 0.944-0.999, P < 0.001). CONCLUSIONS: Compared to the gold standard, this fully automated segmentation system exhibited a high accuracy for assessing segmentation and quantification of abdominal muscle and adipose tissues of CT slices at the L3 in CRC patients.

Ostomy Information on the Internet-Is It Good Enough?

PURPOSE: The aim of this study was to determine which internet search engines and keywords patients with ostomies utilize, to identify the common websites using these terms, to determine what aspects of information they wanted, and to perform a quality and readability assessment for these websites. DESIGN: A cross-sectional survey of persons with ostomies to identify search engines and terms, followed by a structured assessment of the quality and readability of the identified web pages. SUBJECT AND SETTINGS: The sample comprised 20 hospitalized patients with ostomies cared for on a colorectal surgical ward of a tertiary care hospital located in Melbourne, Australia. There were 15 (75%) adult males and 5 (25%) adult females; their mean age was 52.2 years. Participants were surveyed between August and December 2020. METHODS: Patients with newly formed ostomies were surveyed about which search engines and keywords they would use to look for information and for which questions regarding ostomies they wanted answers. In addition, 2 researchers then performed independent searches using the search terms identified by patient participants. These searches were conducted in August 2021, with the geographical location set to Australia. The quality of the websites was graded using the DISCERN, Ensuring Quality Information for Patients, and Quality Evaluation Scoring Tool scoring assessments, and their readability was graded using the Flesch Reading Ease Score tool. RESULTS: Participants used Google as their primary search engine. Four keywords/phrases were identified: stoma for bowel surgery, ileostomy, colostomy, and caring for stoma. Multiple web pages were identified, 8 (21%) originated from Australia, 7 (18%) were from the United Kingdom, and 23 (61%) were from the United States. Most web pages lacked recent updates; only 18% had been undated within the last 12 months. The overall quality of the online information on ostomies was moderate with an average level of readability, deemed suitable for patient educational purposes. CONCLUSIONS: Information for persons living with an ostomy can be obtained from multiple web pages, and many sites have reasonable quality and are written at a suitable level. Unfortunately, these websites are rarely up-to-date and may contain advice that may not be applicable to individual patients.

Digital health and medical technology for perioperative sarcopenia optimisation and prehabilitation - Where to go from here?

Sarcopenia has been shown to cause poorer outcomes in surgical oncology. With the advancement of artificial intelligence technology, body composition analysis can be obtained with ease. Given the lead time between cancer diagnosis and surgery, selected patients at risk of complications secondary to sarcopenia may be amenable to prehabilitation. The COVID-19 pandemic has led to the rapid adaptation of digital health and medical technology. Our perspective piece will review the current available evidence and propose innovative ways to incorporate technology into physical and nutritional prehabilitation.

Body composition assessment by artificial intelligence can be a predictive tool for short-term postoperative complications in Hartmann's reversals.

BACKGROUND: Hartmann's reversal, a complex elective surgery, reverses and closes the colostomy in individuals who previously underwent a Hartmann's procedure due to colonic pathology like cancer or diverticulitis. It demands careful planning and patient optimisation to help reduce postoperative complications. Preoperative evaluation of body composition has been useful in identifying patients at high risk of short-term postoperative outcomes following colorectal cancer surgery. We sought to explore the use of our in-house derived Artificial Intelligence (AI) algorithm to measure body composition within patients undergoing Hartmann's reversal procedure in the prediction of short-term postoperative complications. METHODS: A retrospective study of all patients who underwent Hartmann's reversal within a single tertiary referral centre (Western) in Melbourne, Australia and who had a preoperative Computerised Tomography (CT) scan performed. Body composition was measured using our previously validated AI algorithm for body segmentation developed by the Department of Surgery, Western Precinct, University of Melbourne. Sarcopenia in our study was defined as a skeletal muscle index (SMI), calculated as Skeletal Muscle Area (SMA) /height2 < 38.5 cm2/m2 in women and < 52.4 cm2/m2 in men. RESULTS: Between 2010 and 2020, 47 patients (mean age 63.1 ± 12.3 years; male, n = 28 (59.6%) underwent body composition analysis. Twenty-one patients (44.7%) were sarcopenic, and 12 (25.5%) had evidence of sarcopenic obesity. The most common postoperative complication was surgical site infection (SSI) (n = 8, 17%). Sarcopenia (n = 7, 87.5%, p = 0.02) and sarcopenic obesity (n = 5, 62.5%, p = 0.02) were significantly associated with SSIs. The risks of developing an SSI were 8.7 times greater when sarcopenia was present. CONCLUSION: Sarcopenia and sarcopenic obesity were related to postoperative complications following Hartmann's reversal. Body composition measured by a validated AI algorithm may be a beneficial tool for predicting short-term surgical outcomes for these patients.

Two cases of atraumatic adrenal hemorrhage: A review of active management, conservative management, and challenges faced.

Adrenal hemorrhage (AH) is an uncommon and potentially disastrous affliction that carries an accepted mortality risk of 15%. Variable symptomatology can cause a diagnostic dilemma and may be missed. We present 2 cases of right-sided AH; both cases were initially presumed to be renal colic. Case 1 was an 86-year-old gentleman, presenting with right flank pain found to have a right-sided atraumatic AH. He presented with hemorrhagic shock, requiring angioembolization of the bleeding vessel. Case 2 was a 62-year-old gentleman who presented with right flank pain and was found to have a right-sided atraumatic AH. He was hemodynamically stable and successfully managed conservatively. Adrenal hemorrhage is a potentially fatal affliction that may be missed. CT scans are the recommended imaging modality during an acute presentation due to wider availability and fast assessment. We demonstrate a hemodynamically stable patient managed with a 'watch and wait' approach and an unstable patient managed with resuscitation followed by urgent angioembolization.

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

BACKGROUND: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender. The primary aim of the study was to determine if artificial intelligence (AI) derived body composition variables can predict pCR in patients with LARC. METHODS: LARC patients who underwent NAT followed by surgery from 2012 to 2023 were identified from the Australian Comprehensive Cancer Outcomes and Research Database registry (ACCORD). A validated in-house pre-trained 3D AI model was used to measure body composition via computed tomography images of the entire Lumbar-3 vertebral level to produce a volumetric measurement of visceral fat (VF), subcutaneous fat (SCF) and skeletal muscle (SM). Multivariate analysis between patient body composition and histological outcomes was performed. RESULTS: Of 214 LARC patients treated with NAT, 22.4% of patients achieved pCR. SM volume (P = 0.015) and age (P = 0.03) were positively associated with pCR in both male and female patients. SCF volume was associated with decreased likelihood of pCR (P = 0.059). CONCLUSION: This is the first study in the literature utilizing AI-measured 3D Body composition in LARC patients to assess their impact on pathological response. SM volume and age were positive predictors of pCR disease in both male and female patients following NAT for LARC. Future studies investigating the impact of body composition on clinical outcomes and patients on other neoadjuvant regimens such as TNT are potential avenues for further research.

Colorectal cancer treatment outcomes during the pandemic: Our experience of COVID-19 at a tertiary referral center.

BACKGROUNDS: The coronavirus disease 2019 (COVID-19) has led to major shifts in the management of colorectal cancer (CRC). This study aims to identify the impact and early outcomes of COVID-19 following CRC management at a tertiary referral center in Victoria, Australia. METHODS: This was a retrospective study, utilizing the Australian Comprehensive Cancer Outcomes and Research Database and inpatient records. Patients presenting for CRC management at our institution were identified coinciding with the first Victorian outbreak of COVID-19 (March 26 to September 26, 2020) (COVID). Management decisions including chemoradiotherapy utilization and surgical outcomes were analyzed within 6 months and compared with the corresponding period in 2019 (pre-COVID). RESULTS: A total of 276 patients were included in this study (147 pre-COVID period, 129 COVID period). During the COVID period, more patients (47.6% vs. 60.5%; p = 0.033) presented symptomatically and less for surveillance (10.9% vs. 2.3%; p < 0.01). Eighty-four pre-COVID and 69 COVID period patients proceeded to surgery. The average time from diagnosis date to surgery was 15.6 days less during the COVID period. There were no significant differences in postoperative utilization of higher care (p = 0.74), complications (p = 0.93), median hospital length of stay (p = 0.67), 30-day readmission (p = 0.50), or 30-day reoperation (p = 0.74). In 1.6% of cases, pandemic impacts resulted in a change in management. CONCLUSION: Presentation of patients with CRC varied, with a significant increase in symptomatic presentations and decreased numbers for surveillance. Through flexibility and change in practice, our institution helped improve access to surgical intervention and oncological therapies. Further prospective work is required to identify long-term outcomes and characterize the effects of ongoing disruptions.

Adjuvant Chemotherapy for Older Patients With Stage III Colorectal Cancer: A Real-World Analysis of Treatment Recommendations, Treatment Administered and Impact on Cancer Recurrence.

BACKGROUND: A substantial proportion of patients with stage III colorectal cancer (CRC) are older than 70 years. Optimal adjuvant chemotherapy (AC) for older patients (OP) continues to be debated, with subgroup analyses of randomized trials not demonstrating a survival benefit from the addition of oxaliplatin to a fluoropyrimidine backbone. PATIENTS AND METHODS: We analyzed the multisite Australian ACCORD registry, which prospectively collects patient, tumor and treatment data along with long term clinical follow-up. We compared OP (≥70) with stage III CRC to younger patients ([YP] <70), including the proportion recommended AC and any reasons for not prescribing AC. AC administration, regimen choice, completion rates, and survival outcomes were also examined. RESULTS: One thousand five hundred twelve patients enrolled in the ACCORD registry from 2005 to 2018 were included. Median follow-up was 57.0 months. Compared to the 827 YP, the 685 OP were less likely to be offered AC (71.5% vs. 96.5%, P < .0001) and when offered, were more likely to decline treatment (15.1% vs. 2.8%, P < .0001). Ultimately, 60.0% of OP and 93.7% of YP received AC (P < .0001). OP were less likely to receive oxaliplatin (27.5% vs. 84.7%, P < .0001) and to complete AC (75.9% vs. 85.7%, P < .0001). The probability of remaining recurrence-free was significantly higher in OP who received AC compared to those not treated (HR 0.73, P = .04) but not significantly improved with the addition of oxaliplatin (HR 0.75, P = .18). CONCLUSION: OP were less likely than YP to receive AC. Receipt of AC reduced recurrences in OP, supporting its use, although no significant benefit was observed from the addition of oxaliplatin.

The association of body composition on chemotherapy toxicities in non-metastatic colorectal cancer patients: a systematic review.

BACKGROUND: In recent years, certain body composition measures, assessed by computed tomography (CT), have been found to be associated with chemotherapy toxicities. This review aims to explore available data on the relationship between skeletal muscle and adiposity, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular and intermuscular adipose tissue and their association with chemotherapy toxicity in non-metastatic colorectal cancer (CRC) patients. METHODS: A systematic literature search following PRISMA guidelines was conducted in Medline, Embase, Cochrane and Web of Science, for papers published between 2011 and 2023. The search strategy combined keywords and MESH terms relevant to 'body composition', 'chemotherapy toxicities', and 'non-metastatic colorectal cancer'. RESULTS: Out of 3868 studies identified, six retrospective studies fulfilled the inclusion criteria with 1024 eligible patients. Low skeletal muscle mass was strongly associated with increased incidence of both chemotherapy toxicities and dose-limiting toxicity (DLT). The association of VAT, intramuscular and intermuscular adiposity was heterogeneous and inconclusive. There was no association between SAT and chemotherapy intolerance. No universal definitions or cut-offs for sarcopenia and obesity were noted. All studies utilized 2-dimensional (2D) CT slices for CT body composition assessment with varied selection on the vertebral landmark and inconsistent reporting of tissue-defining Hounsfield unit (HU) measurements. CONCLUSION: Low skeletal muscle is associated with chemotherapy toxicities in non-metastatic CRC. However, quality evidence on the role of adiposity is limited and heterogeneous. More studies are needed to confirm these associations with an emphasis on a more coherent body composition definition and an approach to its assessment, especially regarding sarcopenia.

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan.

Purpose: Body composition analysis in colorectal cancer (CRC) typically utilises a single 2D-abdominal axial CT slice taken at the mid-L3 level. The use of artificial intelligence (AI) allows for analysis of the entire L3 vertebra (non-mid-L3 and mid-L3). The goal of this study was to determine if the use of an AI approach offered any additional information on capturing body composition measures. Methods: A total of 2203 axial CT slices of the entire L3 level (4-46 slices were available per patient) were retrospectively collected from 203 CRC patients treated at Western Health, Melbourne (97 males; 47.8%). A pretrained artificial intelligence (AI) model was used to segment muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) on these slices. The difference in body composition measures between mid-L3 and non-mid-L3 scans was compared for each patient, and for males and females separately. Results: Body composition measures derived from non-mid-L3 scans exhibited a median range of 0.85% to 6.28% (average percent difference) when compared to the use of a single mid-L3 scan. Significant variation in the VAT surface area (p = 0.02) was observed in females compared to males, whereas male patients exhibited a greater variation in SAT surface area (p < 0.001) and radiodensity (p = 0.007). Conclusion: Significant differences in various body composition measures were observed when comparing non-mid-L3 slices to only the mid-L3 slice. Researchers should be aware that considering only the use of a single midpoint L3 CT scan slice will impact the estimate of body composition measurements.

Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy?

PURPOSE: Gold standard chemotherapy dosage is based on body surface area (BSA); however many patients experience dose-limiting toxicities (DLT). We aimed to evaluate the effectiveness of BSA, two-dimensional (2D) and three-dimensional (3D) body composition (BC) measurements derived from Lumbar 3 vertebra (L3) computed tomography (CT) slices, in predicting DLT in colon cancer patients. METHODS: 203 patients (60.87 ± 12.42 years; 97 males, 47.8%) receiving adjuvant chemotherapy (Oxaliplatin and/or 5-Fluorouracil) were retrospectively evaluated. An artificial intelligence segmentation model was used to extract 2D and 3D body composition measurements from each patients' single mid-L3 CT slice as well as multiple-L3 CT scans to produce a 3D BC report. DLT was defined as any incidence of dose reduction or discontinuation due to chemotherapy toxicities. A receiver operating characteristic (ROC) analysis was performed on BSA and individual body composition measurements to demonstrate their predictive performance. RESULTS: A total of 120 (59.1%) patients experienced DLT. Age and BSA did not vary significantly between DLT and non-DLT group. Females were significantly more likely to experience DLT (p = 4.9 × 10-3). In all patients, the predictive effectiveness of 2D body composition measurements (females: AUC = 0.50-0.54; males: AUC = 0.50-0.61) was equivalent to that of BSA (females: AUC = 0.49; males: AUC = 0.58). The L3 3D skeletal muscle volume was the most predictive indicator of DLT (AUC of 0.66 in females and 0.64 in males). CONCLUSION: Compared to BSA and 2D body composition measurements, 3D L3 body composition measurements had greater potential to predict DLT in CRC patients receiving chemotherapy and this was sex dependent.

Can sarcopenia predict survival in locally advanced rectal cancer patients?

BACKGROUND: There is mounting evidence that suggests sarcopenia can be used to predict survival outcomes in patients with colon cancer. However, the effect on locally advanced rectal cancer (LARC) is less clear. We sought to determine the association between sarcopenia on Overall Survival and Recurrence-free Survival (OS and RFS) in patients with LARC undergoing multimodal treatment. METHODS: A retrospective study was undertaken of all pre-treatment stage 2-3 rectal cancer patients who underwent neo-adjuvant treatment and surgery with curative intent between January 2010 and September 2016 at Western Health. Sarcopenia was measured on pre-treatment staging scans at the third lumbar vertebrae and defined using cohort-derived, sex-specific thresholds. Primary outcomes were OS and RFS. RESULTS: A total of 132 patients with LARC were analysed. Sarcopenia: Hazard ratio (HR) 3.71; 95% CI, 1.28-10.75, P = 0.016 was independently associated with worse Overall Survival following multivariate analysis. There was no significant relationship between sarcopenia and RFS: Time ratio (TR) 1.67; 95% CI 0.52-5.34, P = 0.386. CONCLUSION: Sarcopenia was found to be an independent risk factor for worse overall survival, but not recurrence free survival, in patients with locally advanced rectal cancer undergoing neo-adjuvant chemo-radiotherapy and surgery with curative intent.