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Healthcare – with its need for advanced resources and efficiency – is seemingly a perfect home for AI. But the sector has been slow on digitalizing, let alone bringing in such game-changing technologies. Yet gradually, as healthcare facilities around the world digitalize their processes, we’re seeing not just a new way of getting results, but a new way of thinking.
This is now being demonstrated in bladder cancer care with advanced tools emerging that soon expect to become the new norm. In uro-oncology, AI can have a variety of utilities, such as aiding pre-surgical planning through 3D-imaging, and improving the quality of procedures through augmented reality guidance.1,2 In addition, utilizing AI in diagnostics can provide support through real-time tumor detection, histological categorization, risk stratification, and treatment planning.3,4
So, how can AI and diagnostic technologies help when it comes to the care pathway in non-muscle-invasive bladder cancer (NMIBC)? To see the potential in this field, it’s important to first understand the context of the disease itself.
Why is it crucial to address challenges in NMIBC?
NMIBC remains a major health concern worldwide. In fact, recurrences and progression to muscle invasive bladder cancer (MIBC) affect nearly half of the diagnosed NMIBC population, potentially due to misdiagnosis, delay of diagnosis and incomplete resection of tumors.5–7 In NMIBC, missing early recurrence of high-risk lesions may lead to substantial delay of appropriate treatments, which may have a detrimental impact on disease prognosis.8–10
NMIBC reportedly has the highest lifetime cancer treatment costs per patient due to the frequency of procedures and interventions11,12
A delay in bladder cancer diagnosis is more common among women and patients in rural or resource-poor areas13,14
So what can be done to address this? Accurate, timely diagnosis and prediction of recurrence and progression is essential in NMIBC management,12 and advanced tools that can help us to achieve this are key4 – this is where the use of AI is beginning to show promise.4,12
The need for early, accurate diagnosis and improved risk stratification
Expert consensus and NMIBC guidelines are aligned on there being a need for improving the overall quality of NMIBC care and diagnostics in particular.15,16
Identifying patients’ risk factors, or ‘risk stratification’, is vital when planning, predicting prognosis and outcomes, and managing treatment for NMIBC.17 However, current models to support risk stratification have limitations. There’s no universally accepted standard, and the significance of various risk factors used in such models isn’t always clear.18,19 Current models also still largely exclude molecular and genomic profiling of bladder tumors17,20 – factors which can be crucial for identifying a targeted treatment approach. This can lead to delayed or suboptimal treatment – resulting in worse outcomes for NMIBC patients and higher costs of care.18
Early and precise diagnosis of NMIBC is essential for accurate risk stratification, decision making and treatment planning. This in turn may enhance the effectiveness of treatment, by identifying patients who are unlikely to benefit from specific treatments and avoiding unnecessary procedures – leading to more cost-effective care.21,22
Shifting to a precision-based approach in NMIBC
Improving diagnostic precision is becoming increasingly important in NMIBC. NMIBC care is just starting to tap into modern technologies like advanced genetic testing and is expected to further shift with the emergence of new targeted treatment options and technological advancements like AI.23
What is precision diagnostics in NMIBC?
Precision diagnostics doesn’t just consider the clinical presentation and traditional risk factors, it allows a more thorough understanding of the genetic and molecular characteristics of tumors and identifies abnormalities that might be causing it to be more aggressive.24
How? By utilizing current conventional diagnostics such as radiology and cystoscopy, in combination with emerging tools including next-generation imaging techniques, biomarkers based on immunohistochemistry, next-generation sequencing (NGS), multi-omics, and leveraging artificial intelligence (AI)/machine learning (ML).24
A precision-based approach aims to get greater effectiveness from treatment and less off-target effects. The rapid advancement of technologies, the shift towards precision medicine and emerging novel targeted treatments in NMIBC all drive the renewed emphasis of the importance of the diagnostic process.
“The ability to improve the management of NMIBC is upon us with all the new technologies and medicines entering the market. Novel diagnostic tools, including AI, offer clinicians increasing amounts of information for risk assessment and decision making. Optimizing the diagnosis to identify patients who could benefit from novel therapies will have a positive impact on the prognosis for bladder cancer patients.” - Dan Schneider, President and CEO of PhotocureWhat are the benefits?
Precision diagnosis, along with increasing support from AI, may bring us closer to addressing the challenges faced in NMIBC care. It can identify patients who are more likely to respond, or unlikely to benefit, to particular treatment. Plus, more individualized and targeted therapies can increase the chance of a response to treatment while reducing side effects as opposed to more general approaches like chemotherapy.24
A shift towards precision diagnostics and personalized treatment is clearly already underway, with approvals of targeted drugs such as erdafitinib and pembrolizumab in NMIBC,27 as well as AI-based diagnostic tools being explored in several areas of uro-oncology, including prostate and bladder cancer.23,28
Transforming NMIBC care with AI
Advancement in technology, with the use AI and ML, has the potential to dramatically shape medical procedures in the near future. AI and ML have the potential to revolutionize NMIBC management and are increasingly being used to analyze images and other data, and can help identify tumors more accurately, highlighting high-risk patients, enhancing clinical decision making, and fast-tracking patients to more effective targeted treatments.3,4
AI-supported software can enhance current surgical procedures. It can integrate findings from imaging, such as blue light cystoscopy (BLC), with other patient data, such as medical history and pathology grading, to identify patients at risk and predict outcomes.58 There are also increasing advancements in AI-based tools to support clinical decision making, with one tool already available and recommended by NCCN guidelines for prostate cancer. This tool, ArteraAI Prostate Test, analyzes digital pathology images to help identify patients who will benefit from therapy and guide treatment decisions.23
In NMIBC specifically, AI is being increasingly explored in clinical trials, with one tool evaluated in a recent clinical study that uses more comprehensive molecular profiling to evaluate pre- and post-treatment responses to BCG immunotherapy. It aims to create a personalized model to show presence of NMIBC and predict response to BCG.28 Another tool, PROGRxN-BCa (PROGression Risk assessment in NMIBC), presented at the 2024 AUA congress exceeded current tools in NMIBC when predicting disease progression, demonstrating a benefit in avoiding unnecessary treatment escalation.59 In addition, a recent systematic review of AI studies in NMIBC found AI models to generally outperform non-AI models overall when predicting NMIBC outcomes.12
“AI is intended to complement clinical practice, not replace decision making by clinicians. By combining AI with enhanced imaging technology and biomarkers, it can help achieve more precise diagnoses, help analyze and integrate the increasing amount of data, support decision making and improve overall outcomes for patients in the long term.” - Anders Neijber, Chief Medical Officer of PhotocureAs we look to the future, there are still hurdles to overcome when it comes to broader implementation of these technologies and shifting to precision diagnostics. This includes limited-quality clinical data, lack of guideline recommendations, high equipment costs and lack of regulatory approvals.60
Despite rapid increases in evidence around the use of these tools, there is still room for improvement, and there is a clear need for collaboration between healthcare and AI communities to develop higher quality models, allowing us to reach the next step in NMIBC care.12
Conclusion
With NMIBC remaining a significant health concern globally, the integration of novel diagnostic technologies and AI promises to revolutionize diagnosis and treatment. By enhancing accuracy, integration of data, aiding risk stratification, and guiding personalized treatment approaches, these advancements offer hope for improved patient outcomes and more efficient disease management overall. While challenges such as data quality, cost, utility and regulatory hurdles exist, the trajectory is clear: the combination of AI and precision diagnostics procedures holds immense promise for transforming the landscape of NMIBC care in the years to come.
References
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Read More
Reno, Nevada (UroToday.com) -- Photocure ASA, The Bladder Cancer Company, announces that its collaborations with capital equipment providers support the most advanced technologies including recent blue light system upgrades. Read More
As part of the rollout, Karl Storz plans to host a Virtual Launch event for the medical community streamed from its El Segundo, California office where Sia Daneshmand M.D. and Kristin Scarpato M.D. M.P.H. will discuss the clinical benefits of using blue light cystoscopy (BLC®) with Cysview® for NBMIC*,
Read MoreRead More
The therapeutic benefit of intravesical instillation of hexaminolevulinate (HAL) at the time of transurethral resection of bladder tumor (TURBT) has been demonstrated in multiple studies. The purpose of this study was to prospectively assess the safety of repeated administration of HAL from a phase III pre-trial planned analysis.
Read MoreThe utility of blue light cystoscopy (BLC) in patients receiving Bacillus Calmette Guerin (BCG) during post-treatment cystoscopy is not well understood. Our objective was to determine if BLC improves recurrence detection in non-muscle invasive bladder cancer (NMIBC) patients undergoing BCG.
Read MoreMATERIALS AND METHODS: Patients at high risk for recurrence received hexaminolevulinate intravesically before white light flexible cystoscopy and randomization to blue light flexible cystoscopy. Read More
Blue light cystoscopy (BLC) during transurethral resection of bladder tumor (TURBT) is guideline-recommended as it improves cancer detection and decreases recurrence of the disease. However, the extent to which BLC is used has not been established.
Read MoreBlue light cystoscopy (BLC) for the management of non-muscle invasive bladder cancer (NMIBC) is an evidence- and guideline-supported intervention that has been shown to increase cancer detection and decrease recurrence.
Read MorePhotodynamic diagnosis using hexaminolevulinate (HAL)-guided BL-TURB may reduce the recurrence risk in non-muscle invasive BCa compared to standard WL-TURB due to more sensitive tumor detection. The impact of the initial use of WL- vs.
Read MoreTo determine the estimated budget impact to practices that incorporate blue light cystoscopy (BLC) with hexaminolevulinate HCl (HAL) for the surveillance of non-muscle-invasive bladder cancer (NMIBC) in the clinic setting.
With the introduction of advanced technologies in the clinic setting such as HAL, further cost comparative research is needed to justify HAL as a high value option.
Read MoreSmoking has a strong causal association with bladder cancer but the relationship with recurrence is not well established. We sought to assess the association of smoking status on recurrence of non-muscle invasive bladder cancer (NMIBC) in a contemporary cohort of patients with predominantly high-risk, recurrent NMIBC managed with photodynamic enhanced cystoscopy.
Read MoreBlue light cystoscopy (BLC) with hexaminolevulinate (HAL) during transurethral resection of bladder cancer improves detection of non-muscle-invasive bladder cancer (NMIBC) and reduces recurrence rates.
Read MorePurpose: To evaluate the utility of blue light flexible cystoscopy (BLFC) for surveillance of non-muscle invasive bladder cancer (NMIBC). This was a prospective cohort of consecutive patients who underwent office BLFC for NMIBC. Clinical information was collected including cystoscopic findings and pathologic data.
Read MorePhotodynamic diagnosis using the optical imaging agent hexaminolevulinate (HAL, Hexvix®, Ipsen Pharma GmbH, Ettlingen, Germany) as an adjunct to white light cystoscopy (WLC) during the initial transurethral resection of bladder tumours (TURB) improves the detection rate of bladder cancer and leads to fewer recurrences.
Read MoreDiagnosis:
Clinical PresentationThere are no reliable screening tests available for detecting bladder cancer; hence the diagnosis is usually made based on clinical signs and symptoms. Painless hematuria – microscopic or gross – is the most common presentation and a hematuria investigation in an otherwise asymptomatic patient detects bladder neoplasm in roughly 20% of gross and 5% of microscopic cases.1,2 Read More
Read More
Surveilling recurrent urothelial carcinoma (UC) requires frequent cystoscopy, which is invasive, expensive and time-consuming. An accurate urinary biomarker has the potential to reduce the number of cystoscopies required during post-treatment surveillance.
Read MoreIn 2020, approximately 81,000 cases of urothelial carcinoma of the bladder will be diagnosed in the United States, with nearly 18,000 associated deaths.1 Bladder cancer disproportionally affects men and is associated with well-defined environmental risk factors—tobacco use underlies approximately 50% of cases.2 Nonmuscle-invasive bladder cancer (NMIBC) is primarily managed by transurethral resection, risk-stratified use of intravesical chemotherapeutic or immunotherapeutic agents, and close surveillance. Read More
Published Date: September 2018
More than 81,000 individuals are diagnosed with bladder cancer in the United States every year, of whom 75% have non-muscle invasive disease.1,2 Unfortunately, half these cases recur despite transurethral resection of bladder tumor (TURBT), and from 5% to 25% of repeated recurrences progress to muscle-invasive disease.3,4,5
Blue light cystoscopy (BLC) using hexaminolevulinate (HAL/Cysview/Hexvix) has been previously shown to improve detection of non-muscle-invasive bladder cancer (NMIBC). Herein, we evaluated the detection of malignant lesions in a heterogenous group of patients in the real world setting and documented the change in risk category due to upstaging or upgrading.
Read MoreA 90-year old man with no significant past medical history presented to urology clinic complaining of gross hematuria, urinary frequency, and dysuria. Previous urine cytology was atypical but two white-light cystoscopies failed to show any lesions.
Read MoreThe 23rd Annual Meeting of the SUO was host to a session on the real life impact of CxBladder tests for the diagnosis and surveillance of bladder cancer. Dr. Sima Porten began her presentation by noting that there has been an “explosion” of “at home” tests, many of which have been approved by the US FDA. The most prominent example of this is the Cologuard stool DNA tests for colorectal cancer screening that has seen widespread adoption in the United States.
Read MoreThe 23rd Annual Meeting of the SUO was host to a session on the real life impact of CxBladder tests for the diagnosis and surveillance of bladder cancer. Dr. John Sfakianos began his presentation by noting that current guidelines for surveillance provide little concrete guidance for when surveillance may be stopped. The AUA currently provides the following guidance by risk category
Read MoreThere have been several recent single-arm trials in the Bacillus Calmette-Guerin (BCG) unresponsive non-muscle invasive bladder cancer (NMIBC) setting. The first question that arises is whether these single-arm trials are enough or do we need to randomize patients for our future trials.
Read More