Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.

OBJECTIVES: Non-contrast computed tomography of the brain (NCCTB) is commonly used to detect intracranial pathology but is subject to interpretation errors. Machine learning can augment clinical decision-making and improve NCCTB scan interpretation. This retrospective detection accuracy study assessed the performance of radiologists assisted by a deep learning model and compared the standalone performance of the model with that of unassisted radiologists. METHODS: A deep learning model was trained on 212,484 NCCTB scans drawn from a private radiology group in Australia. Scans from inpatient, outpatient, and emergency settings were included. Scan inclusion criteria were age ≥ 18 years and series slice thickness ≤ 1.5 mm. Thirty-two radiologists reviewed 2848 scans with and without the assistance of the deep learning system and rated their confidence in the presence of each finding using a 7-point scale. Differences in AUC and Matthews correlation coefficient (MCC) were calculated using a ground-truth gold standard. RESULTS: The model demonstrated an average area under the receiver operating characteristic curve (AUC) of 0.93 across 144 NCCTB findings and significantly improved radiologist interpretation performance. Assisted and unassisted radiologists demonstrated an average AUC of 0.79 and 0.73 across 22 grouped parent findings and 0.72 and 0.68 across 189 child findings, respectively. When assisted by the model, radiologist AUC was significantly improved for 91 findings (158 findings were non-inferior), and reading time was significantly reduced. CONCLUSIONS: The assistance of a comprehensive deep learning model significantly improved radiologist detection accuracy across a wide range of clinical findings and demonstrated the potential to improve NCCTB interpretation. CLINICAL RELEVANCE STATEMENT: This study evaluated a comprehensive CT brain deep learning model, which performed strongly, improved the performance of radiologists, and reduced interpretation time. The model may reduce errors, improve efficiency, facilitate triage, and better enable the delivery of timely patient care. KEY POINTS: • This study demonstrated that the use of a comprehensive deep learning system assisted radiologists in the detection of a wide range of abnormalities on non-contrast brain computed tomography scans. • The deep learning model demonstrated an average area under the receiver operating characteristic curve of 0.93 across 144 findings and significantly improved radiologist interpretation performance. • The assistance of the comprehensive deep learning model significantly reduced the time required for radiologists to interpret computed tomography scans of the brain.

Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.

Natural language processing (NLP), a domain of artificial intelligence (AI) that models human language, has been used in medicine to automate diagnostics, detect adverse events, support decision making and predict clinical outcomes. However, applications to the clinical neurosciences appear to be limited. NLP has matured with the implementation of deep transformer models (e.g., XLNet, BERT, T5, and RoBERTa) and transfer learning. The objectives of this study were to (1) systematically review NLP applications in the clinical neurosciences, and (2) explore NLP analysis to facilitate literature synthesis, providing clear examples to demonstrate the potential capabilities of these technologies for a clinical audience. Our NLP analysis consisted of keyword identification, text summarization and document classification. A total of 48 articles met inclusion criteria. NLP has been applied in the clinical neurosciences to facilitate literature synthesis, data extraction, patient identification, automated clinical reporting and outcome prediction. The number of publications applying NLP has increased rapidly over the past five years. Document classifiers trained to differentiate included and excluded articles demonstrated moderate performance (XLNet AUC = 0.66, BERT AUC = 0.59, RoBERTa AUC = 0.62). The T5 transformer model generated acceptable abstract summaries. The application of NLP has the potential to enhance research and practice in the clinical neurosciences.

Non-Fatal Drowning: Measuring Respiratory Rate as Part of "Beach-Side" Clinical Assessment of Physiological Respiratory Stress.

An average of 115 people drown in Ireland each year. Drowning is the third commonest cause of unintentional injury-related death globally. The United Nations 'Global Drowning Prevention' resolution was adopted in April 2021. The WHO recognises almost 360,000 drownings annually. There are an estimated 8-10 non-fatal drownings for each fatal drowning. The evidence base underpinning clinical management of non-fatal drowning is sparse. The use of respiratory rate in non-fatal drowning may provide a "beach-side" objective, quantifiable clinical measure of evolving physiological respiratory stress.

Clinical outcomes associated with robotic and computer-navigated total knee arthroplasty: a machine learning-augmented systematic review.

BACKGROUND: Robotic (RTKA) and computer-navigated total knee arthroplasty (CNTKA) are increasingly replacing manual techniques in orthopaedic surgery. This systematic review compared clinical outcomes associated with RTKA and CNTKA and investigated the utility of natural language processing (NLP) for the literature synthesis. METHODS: A comprehensive search strategy was implemented. Results of included studies were combined and analysed. A transfer learning approach was applied to train deep NLP classifiers (BERT, RoBERTa and XLNet), with cross-validation, to partially automate the systematic review process. RESULTS: 52 studies were included, comprising 5,067 RTKA and 2,108 CNTKA. Complication rates were 0-22% and 0-16% and surgical time was 70-116 and 77-102 min for RTKA and CNTKA, respectively. Technical failures were more commonly associated with RTKA (8%) than CNTKA (2-4%). Patient satisfaction was equivalent (94%). RTKA was associated with a higher likelihood of achieving target alignment, less femoral notching, shorter operative time and shorter length of stay. NLP models demonstrated moderate performance (AUC = 0.65-0.68). CONCLUSIONS: RTKA and CNTKA appear to be associated with similarly positive clinical outcomes. Further work is required to determine whether the two techniques differ significantly with regard to specific outcome measures. NLP shows promise for facilitating the systematic review process.

Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review.

Machine learning (ML) involves algorithms learning patterns in large, complex datasets to predict and classify. Algorithms include neural networks (NN), logistic regression (LR), and support vector machines (SVM). ML may generate substantial improvements in neurosurgery. This systematic review assessed the current state of neurosurgical ML applications and the performance of algorithms applied. Our systematic search strategy yielded 6866 results, 70 of which met inclusion criteria. Performance statistics analyzed included area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity. Natural language processing (NLP) was used to model topics across the corpus and to identify keywords within surgical subspecialties. ML applications were heterogeneous. The densest cluster of studies focused on preoperative evaluation, planning, and outcome prediction in spine surgery. The main algorithms applied were NN, LR, and SVM. Input and output features varied widely and were listed to facilitate future research. The accuracy (F(2,19) = 6.56, p < 0.01) and specificity (F(2,16) = 5.57, p < 0.01) of NN, LR, and SVM differed significantly. NN algorithms demonstrated significantly higher accuracy than LR. SVM demonstrated significantly higher specificity than LR. We found no significant difference between NN, LR, and SVM AUC and sensitivity. NLP topic modeling reached maximum coherence at seven topics, which were defined by modeling approach, surgery type, and pathology themes. Keywords captured research foci within surgical domains. ML technology accurately predicts outcomes and facilitates clinical decision-making in neurosurgery. NNs frequently outperformed other algorithms on supervised learning tasks. This study identified gaps in the literature and opportunities for future neurosurgical ML research.

Foundation for an evidence-informed algorithm for treating pelvic floor mesh complications: a review.

To address evidence gaps on the management of complications related to mesh in pelvic floor surgery, we created an evidence-based algorithm that includes defining evidence gaps. We utilized the Delphi method within a panel of surgeons treating mesh complications to define a treatment strategy. The first round provided a list of clinically based postulates that informed a review expanding postulates to recommendations and included grading of the quality of evidence. A second round informed the final algorithm. While the quality of the available evidence is low, it provides a framework for planning diagnosis and management of mesh-related complications. TWEETABLE ABSTRACT: Removal of mesh must balance resolution of complications with the risk of removal and recurrence of pelvic floor symptoms.

Patient Texting in General Practice: Who, Why, Why Not? A National Survey of Text Messaging in Irish General Practice.

Introduction The benefits of text messaging patients are well documented. The General Medical Council recently published guidance endorsing text messaging. The use of text messaging by GPs in Ireland is currently unknown. The survey aims to address this knowledge deficit and ascertain the extent, benefits, risks, barriers and clinical role of text messaging in Irish general practice. Methods An online survey was emailed to 1,375 members of the Irish College of General Practitioners (ICGP). Results A total of 536 GPs completed the questionnaire; a response rate of 40%. Overall, 66% (n=353) of respondents text patients and 27% have a written policy for texting patients. Texting is used primarily to send test results (71%), to advise the patient to phone the practice (52%) and as appointment reminders (43%). Discussion GPs text messaging patients is widespread. Complex issues to resolve include consent, confidentiality, children/young adults and the clinical content of text messages. Guidance is required to enable GPs and patients harness the benefits of text messaging, while minimising potential risks.

Correction of severe spinopelvic mismatch: decreased blood loss with lateral hyperlordotic interbody grafts as compared with pedicle subtraction osteotomy.

OBJECTIVE Pedicle subtraction osteotomy (PSO) provides extensive correction in patients with fixed sagittal plane imbalance but is associated with high estimated blood loss (EBL). Anterior column realignment (ACR) with lateral graft placement and sectioning of the anterior longitudinal ligament allows restoration of lumbar lordosis (LL). The authors compare peri- and postoperative measures in 2 groups of patients undergoing correction of a sagittal plane imbalance, either through PSO or the use of lateral lumbar fusion and ACR with hyperlordotic (20°-30°) interbody cages, with stabilization through standard posterior instrumentation in all cases. METHODS The authors performed a retrospective chart review of cases involving a lumbar PSO or lateral lumbar interbody fusion and ACR (LLIF-ACR) between 2010 and 2015 at the authors' institution. Patients who had a PSO in the setting of a preexisting fusion that spanned more than 4 levels were excluded. Demographic characteristics, spinopelvic parameters, EBL, operative time, and LOS were analyzed and compared between patients treated with PSO and those treated with LLIF-ACR. RESULTS The PSO group included 14 patients and the LLIF-ACR group included 13 patients. The mean follow-up was 13 months in the LLIF-ACR group and 26 months in the PSO group. The mean EBL was significantly lower in the LLIF-ACR group, measuring approximately 50% of the mean EBL in the PSO group (1466 vs 2910 ml, p < 0.01). Total LL correction was equivalent between the 2 groups (35° in the PSO group, 31° in the LLIF-ACR group, p > 0.05), as was the preoperative PI-LL mismatch (33° in each group, p > 0.05) and the postoperative PI-LL mismatch (< 1° in each group, p = 0.05). The fusion rate as assessed by the need for reoperation due to pseudarthrosis was lower in the LLIF-ACR group but not significantly so (3 revisions in the PSO group due to pseudarthrosis vs 0 in the LLIF-ACR group, p > 0.5). The total operative time and LOS were not significantly different in the 2 groups. CONCLUSIONS This is the first direct comparison of the LLIF-ACR technique with the PSO in adult spinal deformity correction. The study demonstrates that the LLIF-ACR provides equivalent deformity correction with significantly reduced blood loss in patients with a previously unfused spine compared with the PSO. This technique provides a powerful means to avoid PSO in selected patients who require spinal deformity correction.

Predictive value of PI-RADS classification in MRI-directed transrectal ultrasound guided prostate biopsy.

AIM: To correlate the results of transrectal ultrasound (TRUS)-guided targeted prostate biopsies (performed in the setting of at least one previous negative biopsy) with the Prostate Imaging Reporting and Data System (PI-RADS). MATERIAL AND METHODS: Fifty-two patients (mean age 64 years, range 52-76 years), with previous negative prostate biopsy underwent magnetic resonance imaging (MRI)-directed TRUS-guided targeted and sectoral biopsy. A retrospective review of MRI examinations was carried out, blinded to biopsy results. PI-RADS scores (T2, diffusion-weighted imaging [DWI] and overall) were assigned on a per lesion basis, and localised to sextants. The scores were correlated with biopsy results, and the positive predictive values (PPV) of PIRADS scores for positive biopsies were calculated. RESULTS: Overall, biopsies were positive in 23/52 (44.2%) patients. Eighty-one areas were targeted in 52 patients. On a per lesion basis, there was significant correlation between positive targeted biopsy and both T2 and overall PI-RADS score (p<0.001). The correlation between biopsy and DWI score was significant for peripheral zone tumours only, not for transitional zone tumours. The PPV of overall PI-RADS scores of 3, 4, and 5 were 10.6%, 44%, and 100%, respectively. The PPV of T2 PI-RADS scores of 3, 4, and 5 were 19.6%, 60%, and 100%, respectively. The PPV of DWI PI-RADS scores of 3, 4, and 5 were 50%, 27.3%, and 33%, respectively. When transitional tumours were excluded, the PPV of DWI PI-RADS 3, 4, and 5 were 40%, 43%, and 78%. CONCLUSION: The PIRADS score provides an effective framework for determining the likelihood of prostate cancer on MRI. The DWI PI-RADS score correlates well with the presence of peripheral zone tumour on targeted biopsy, but not with transitional zone tumours.

Peri-operative management in urinary diversion surgery: A time for change?

INTRODUCTION: Bowel preparation was established as part of the pre-operative course for patients undergoing ileal conduit formation since the late 1970's. Rationales for its use include reduction in infection and wound complications, technically easier anastomosis and earlier return to bowel function. However, recent reports have challenged this practice. Traditionally antibiotics were also administered for several days prior to surgery with the assumption that bacterial load was reduced. Modification of antibiotic protocols resulted from evidence-based findings. Furthermore, publications emphasizing the benefit of Enhanced Recovery Protocols/Programmes (ERP) have become contemporary. METHODS: An online multiple-choice questionnaire (via Monkey Survey) was administered to all consultant urologists in Ireland. This national cross-sectional study evaluated the use of bowel preparation and antibiotic prophylaxis prior to urinary diversion. In addition, we also assessed consultant urologists' awareness of ERP and their views on the introduction and implementation of such a national program. RESULTS: Of the 41 consultant urologists surveyed, 80.4% (n = 33) responded. 63.6% routinely used bowel preparation. Klean Prep was the most commonly used bowel preparation. 80.9% of urologists admit their patient's one-day pre-operatively for bowel preparation, with 87.8% using antibiotic prophylaxis at anesthesia induction, and 18.1% continuing the antibiotics for 24-48 h post-operatively. Although 74% of consultants are aware of ERP, only 66.6% are in favor of their national implementation. CONCLUSION: The majority of Irish urologists use bowel preparation prior to ileal conduit formation. Substantial recent evidence has emerged showing no difference in infective complications or anastomotic leakage when bowel preparation was not used. National guidelines would be beneficial regarding the use of bowel preparation, antibiotic prophylaxis and ERP for urinary diversion surgery.

Incidentalology: A developing urological sub-specialty.

OBJECTIVE: To identify the incidence and features of significant incidental findings discussed at our departmental multidisciplinary team meeting (MDM). The improved quality of radiological imaging has resulted in increased rates of incidental findings. Although some may be trivial, many have clinical significance and early diagnosis and treatment may be beneficial. METHODS: A retrospective analysis was performed of all cases discussed at the MDM between January 2012 and February 2013. Cases were divided into two groups--Group 1 consisted of patients whose initial imaging was performed for a urological presentation which resulted in a synchronous finding; Group 2 consisted of patients who were referred with a synchronous urological finding for discussion following investigation of an initial benign urological condition or a non-urological condition. RESULTS: 696 patients were discussed at 53 MDMs. 109 (15.7%) patients had incidental findings. 61 (56%) of these were in Group 1. 16 (26.2%) were synchronous malignant diagnoses, 25 (41%) were benign and 20 (32.8%) were indeterminate. 48 (44%) patients in Group 2 - 40 (83.3%) were renal in origin and 30 (75%) of these proceeded to surgery. The median tumour size was 3.2 cm (Range: 1.2 cm-10 cm). One patient had radio-frequency ablation. Two were referred for palliative care. Seven patients are under ongoing surveillance--the median size of these lesions is 3.6 cm (Range: 2.1 cm-8.3 cm). CONCLUSION: A substantial workload is generated from the investigation of incidental findings discussed at MDM--these now represent the majority of the caseload for renal cancer surgery.

Autotransplantation of a single functioning kidney following rupture of renal artery aneurysm.

Renal artery aneurysms (RAA) are the second most common visceral artery aneurysm. In cases of rupture they pose a significant and emergent surgical challenge. Extracorporeal arterial reconstruction and autotransplantation is often necessary in certain complex cases that are not amenable to aneurysm repair in vivo. We report a case of a 35 year old female with a RAA in a solitary functioning kidney, requiring ex vivo reconstruction and autotransplantation to the iliac vessels.

The lost art of intergenerational mentorship in health services research and teaching in pharmacy: The CRoME lab example.

INTRODUCTION: Intergenerational mentorship (IM) promotes collaborative learning while challenging traditional hierarchies by promoting bidirectional knowledge exchange between experienced professionals and students. The IM model emphasizes "reverse mentoring" to foster relationships based on respect, responsibility, reciprocity, and resiliency while enhancing education and mentorship quality in the pharmacy and health services research. PERSPECTIVE: The Collaborative Research on Medication use & family health (CRoME) Lab at the University of Wisconsin-Madison School of Pharmacy showcases intergenerational mentorship in health services research in pharmacy. With a diverse team, including faculty, research scientists, and students, this research Lab specifically applies IM principle into every aspect of teaching and research with a unique focus on building students' skills in community-engaged leadership. For example, student members of the CRoME Lab are mentored to integrate youth perspectives into all aspects of their research and collaborate with multiple advisory boards to improve the quality of their health services research projects. All student members are provided various opportunities to practice community-based and scientific presentations and publication skills. Emphasizing community-engaged leadership extends impact beyond academia, highlighting intergenerational mentorship's influence on community engagement in the field of pharmacy. IMPLICATIONS: The CRoME Lab highlights the profound impact of intergenerational mentorship in pharmacy, fostering collaboration and developing highly skilled pharmacists. This approach is crucial for shaping a blend of tradition and innovation, while benefiting the pharmacy profession by facilitating knowledge transfer, continuous learning, and leadership development among successful alumni.

Opportunities for developing neural stem cell treatments for acute ischemic stroke: A systematic review and gap analysis.

Ischemic stroke is a leading cause of disability and death. Current treatments are limited. Stem cell therapy has been highlighted as a potentially effective treatment to mitigate damage and restore function, but efficacy results are mixed. This study aimed to systematically review the literature on stem cell therapies for early acute ischemic stroke; and identify opportunities for future research to facilitate the development of an effective stem cell-based treatment. Original research published within the last 10 years that focused on the evaluation of a stem cell-based treatment for acute ischemic stroke in adult patients or subjects was included. Risk of bias was assessed using the SYRCLE and Cochrane risk of bias tools for animal and human studies, respectively. 3,396 articles were screened, 58 full-text articles were reviewed and 33 met inclusion criteria. Many studies appeared to be at risk of bias. Study designs and results were heterogeneous. Most studies were preclinical and involved stem cell administration within 24 hours. Seven studies tested the effects of multiple administration timepoints and one investigated repeat dosing. Six studies were conducted in humans and stem cell administration ranged from 24 hours to 90 days post stroke. Most studies employed the use of mesenchymal stem cells. The most appropriate cell delivery method appeared to be intra-arterial. Evidence suggests that stem cell therapy may be associated with beneficial effects. A literature gap analysis identified numerous opportunities for treatment development.

Predicting Acoustic Hearing Preservation Following Cochlear Implant Surgery Using Machine Learning.

OBJECTIVES: The aim of the study was to train and test supervised machine-learning classifiers to predict acoustic hearing preservation after CI using preoperative clinical data. STUDY DESIGN: Retrospective predictive modeling study of prospectively collected single-institution CI dataset. METHODS: One hundred and seventy-five patients from a REDCap database including 761 patients >18 years who underwent CI and had audiometric testing preoperatively and one month after surgery were included. The primary outcome variable was the lowest quartile change in acoustic hearing at one month after CI using various formulae (standard pure tone average, SPTA; low-frequency PTA, LFPTA). Analysis involved applying multivariate logistic regression to detect statistical associations and training and testing supervised learning classifiers. Classifier performance was assessed with numerous metrics including area under the receiver operating characteristic curve (AUC) and Matthews correlation coefficient (MCC). RESULTS: Lowest quartile change (indicating hearing preservation) in SPTA was positively associated with a history of meningitis, preoperative LFPTA, and preoperative SPTA. Lowest quartile change in SPTA was negatively associated with sudden hearing loss, noise exposure, aural fullness, and abnormal anatomy. Lowest quartile change in LFPTA was positively associated with preoperative LFPTA. Lowest quartile change in LFPTA was negatively associated with tobacco use. Random forest demonstrated the highest mean classification performance on the validation dataset when predicting each of the outcome variables. CONCLUSIONS: Machine learning demonstrated utility for predicting preservation of residual acoustic hearing in patients undergoing CI surgery, and the detected associations facilitated the interpretation of our machine-learning models. The models and statistical associations together may be used to facilitate improvements in shared clinical decision-making and patient outcomes. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:926-936, 2024.

Percutaneous transhepatic cholecystoscopic gallstone fragmentation: a novel approach for the medically unfit patient?

Management of the surgically unfit patient with symptomatic cholelithiasis can be fraught with difficulty. We describe the case of on such gentleman in whom percutaneous transhepatic cholecystoscopy was used to completely fragment a large gallbladder calculus through the use of a nephroscope and Swiss lithoclast Master.

Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review.

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy. An understanding of the capabilities and limitations of modern machine learning systems is necessary for clinicians as these tools begin to permeate practice. This systematic review aimed to provide an overview of machine learning applications designed to facilitate CXR interpretation. A systematic search strategy was executed to identify research into machine learning algorithms capable of detecting >2 radiographic findings on CXRs published between January 2020 and September 2022. Model details and study characteristics, including risk of bias and quality, were summarized. Initially, 2248 articles were retrieved, with 46 included in the final review. Published models demonstrated strong standalone performance and were typically as accurate, or more accurate, than radiologists or non-radiologist clinicians. Multiple studies demonstrated an improvement in the clinical finding classification performance of clinicians when models acted as a diagnostic assistance device. Device performance was compared with that of clinicians in 30% of studies, while effects on clinical perception and diagnosis were evaluated in 19%. Only one study was prospectively run. On average, 128,662 images were used to train and validate models. Most classified less than eight clinical findings, while the three most comprehensive models classified 54, 72, and 124 findings. This review suggests that machine learning devices designed to facilitate CXR interpretation perform strongly, improve the detection performance of clinicians, and improve the efficiency of radiology workflow. Several limitations were identified, and clinician involvement and expertise will be key to driving the safe implementation of quality CXR machine learning systems.

Analysis of Line and Tube Detection Performance of a Chest X-ray Deep Learning Model to Evaluate Hidden Stratification.

This retrospective case-control study evaluated the diagnostic performance of a commercially available chest radiography deep convolutional neural network (DCNN) in identifying the presence and position of central venous catheters, enteric tubes, and endotracheal tubes, in addition to a subgroup analysis of different types of lines/tubes. A held-out test dataset of 2568 studies was sourced from community radiology clinics and hospitals in Australia and the USA, and was then ground-truth labelled for the presence, position, and type of line or tube from the consensus of a thoracic specialist radiologist and an intensive care clinician. DCNN model performance for identifying and assessing the positioning of central venous catheters, enteric tubes, and endotracheal tubes over the entire dataset, as well as within each subgroup, was evaluated. The area under the receiver operating characteristic curve (AUC) was assessed. The DCNN algorithm displayed high performance in detecting the presence of lines and tubes in the test dataset with AUCs > 0.99, and good position classification performance over a subpopulation of ground truth positive cases with AUCs of 0.86-0.91. The subgroup analysis showed that model performance was robust across the various subtypes of lines or tubes, although position classification performance of peripherally inserted central catheters was relatively lower. Our findings indicated that the DCNN algorithm performed well in the detection and position classification of lines and tubes, supporting its use as an assistant for clinicians. Further work is required to evaluate performance in rarer scenarios, as well as in less common subgroups.

Management of synchronous rectal and prostate cancer.

PURPOSE: Although well described, there is limited published data related to management on the coexistence of prostate and rectal cancer. The aim of this study was to describe a single institution's experience with this and propose a treatment algorithm based on the best available evidence. METHODS: From 2000 to 2011, a retrospective review of institutional databases was performed to identify patients with synchronous prostate and rectal cancers where the rectal cancer lay in the lower two thirds of the rectum. Operative and non-operative outcomes were analysed and a management algorithm is proposed. RESULTS: Twelve patients with prostate and rectal cancer were identified. Three were metachronous diagnoses (>3-month time interval) and nine were synchronous diagnoses. In the synchronous group, four had metastatic disease at presentation and were treated symptomatically, while five were treated with curative intent. Treatment included pelvic radiotherapy (74 Gy) followed by pelvic exenteration (three) and watchful waiting for rectal cancer (one). The remaining patient had a prostatectomy, long-course chemoradiotherapy and anterior resection. There were no operative mortalities and acceptable morbidity. Three remain alive with two patients disease-free. CONCLUSIONS: Synchronous detection of prostate cancer and cancer of the lower two thirds of the rectum is uncommon, but likely to increase with rigorous preoperative staging of rectal cancer and increased awareness of the potential for synchronous disease. Treatment must be individualized based on the stage of the individual cancers taking into account the options for both cancers including EBRT (both), surgery (both), hormonal therapy (prostate), surgery (both) and watchful waiting (both).