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Optimizing Biopsy Approach Before Precision Prostatectomy

Posted by Arvin George, MD | Sep 2023

Arvin K. George, MD, reviews the strengths and limitations of prostate magnetic resonance imaging (MRI), identifies strategies to optimize the detection of clinically significant prostate cancer, and reviews outcomes of precision prostatectomy. Dr. George begins by addressing the weak predictive value of multiparametric MRI (mpMRI,) calling it imperfect. However, data from the PROMIS study supports mpMRI over transrectal ultrasound (TRUS.)

Dr. George cites data on MRI-targeted, systematic, and combined biopsy for prostate cancer diagnosis, and defines precision prostatectomy as a subtotal prostatectomy that preserves tissue and nerves. Dr. George illustrates two scenarios to support the use of precision prostatectomy in conjunction with a 3D ultrasound to guide treatment—one for biopsy-naive patients and the other for patients with prior biopsy. He then shares data on precision prostatectomy outcomes, in which all patients maintained social continence and 85% of patients maintained potency after one year.

In regards to remission rates, only 6.6% of post-mpMRI biopsy patients presented with clinically significant prostate cancer at 36 months, with over 90% of patients requiring no secondary treatment. Dr. George reiterates that mpMRI is not perfect, but its preservative effects on patients makes it worth further exploration.

About the 26th Annual Southwest Prostate Cancer Symposium:
This conference educated attendees about advances in the management of localized and advanced prostate cancer, with a focus on imaging, technology, and training in the related devices. It included a scientific session, as well as live demonstrations of surgical techniques. You can learn more about the conference here.

PCa Commentary | Volume 181 – September 2023

Posted by Edward Weber, MD | Sep 2023

Background

The function of initial staging of prostate cancer is to accurately estimate the risk of progression in order to guide optimal therapy. The influential National Comprehensive Cancer Network (NCCN)
recommends a PSMA PET/CT as part of initial staging for men in the risk categories of intermediate- and high-risk cancer as defined by clinicopathologic features: PSA, Gleason score, clinical tumor stage and number of positive biopsy cores. For men with a life expectancy of >10 years molecular analysis (i.e., Decipher, Prolaris or OncotypeDx Prostate) is suggested by the NCCN.

PSMA PET/CT in advanced cancer identifies lesions that are missed on conventional CT and bone scans. Yaxley et al., BJU Int 2019 reported the results of primary staging by PSMA PET/CT in 1253 men, half and half with intermediate and high-risk disease in the largest published study on this subject. Metastases were identified in 12.1%; 8.2% in men with PSA values <10 ng/ml and 47% with PSA values > 20 ng/mL. Segregated by Gleason Grade, metastases were found in 6.4% with GG 2-3 (Gleason 3+3 and 3+4). Extra-pelvic lymph nodes occurred in 47%. Bone metastases were found in 5.2% in men with intermediate-risk and in 20% high-risk cancer.

Enter the Immune System — Its Influence on Cancer Behavior

The influence of immune cell infiltration within the tumor and from the surrounding microenvironment is not taken into account in assigning a Gleason score and therefore is not considered in the NCCN classifications of risk. The variety of promoter and suppressive lymphocytes and macrophages that comprise these infiltrations are not fully identified under the microscope and play no role in standard risk assessments.

The immune microenvironment of the primary tumor influences both the initiation and early progression (i.e., toward a higher Gleason score) of the developing cancer. Immune elements compete (i.e., pro-tumor and anti-tumor) to suppress malignant clones from progressing — while others promote disorganization and aggressiveness. Protective cells include immune enhancing CD8+T-cells, Killer T-cells, protective macrophages; immune suppressive cells include T-regulation cells and immune suppressive macrophages. In fact, recent studies reveal that the ratio of one particular gene in anti-tumor macrophages to a different gene in pro-tumor macrophages can by itself determine the outcome in a man’s cancer — and possibly all cancers. (Bill et al., SCIENCE, Aug 2023).

These immune cellular elements are not only found within and surrounding tumors but also can be identified in the blood to various amounts. Based on their presence in the blood, Chinese researchers have “developed and validated a machine-learning nomogram for the prediction of risk stratification of prostate cancer based on subsets of these lymphocytes in the blood.” This nomogram functioned better than the standard NCCN prognostic risk groups. (Yang et al., Journal of Translational Medicine 2023.)

The Predictive Power of Artificial Intelligence

The genomic classifier Decipher has been multiply validated to estimate prognosis based on its risk scale of 0 to 1.0. However, AI has the capability to derive a prediction — for example of an individual man’s response to a given treatment. When whole mount pathology slides, multiply stained, are digitized into a scanner, the AI process identifies standard histology but also detects the subtypes of immune cells infiltrating the tumor and the surrounding microenvironment. This comprehensive analysis presents a complete picture of a man’s cancer, its predicted behavior and supports individualized management.

Two Examples of Clinically Useful Applications of AI for Intensifying or De-intensifying
Therapy

Commentary #180 discusses a study assessing the relative benefits of adding ADT to
radiation therapy in men with advanced cancer based on a derived biomarker.
At the 2023 annual meeting of the American Society of Clinical Oncology, Armstrong and
colleagues from Duke University presented their abstract, “Development and validation of an
AI-derived digital pathology-based biomarker to predict benefit of long-term androgen deprivation therapy with radiotherapy in men with localized high-risk prostate cancer across
multiple phase III NRG/RTOG trials,” i.e., a goal “to guide ADT duration to maximize benefits
and minimize risks.”
“Pre-treatment prostate biopsy slides were digitized from six randomized trials evaluating the
benefit of radiation therapy +/- ADT” in men with localized high-risk prostate cancer with end
points of distant metastases (DM) and prostate cancer-specific mortality. The data from this
training set was then validated in a major trial comparing radiation plus 4 vs. 28 months of ADT and determined a distinguishing biomarker. Their study found that 28 months of ADT was 13% better than 4 months in the biomarker-positive group as compared to only 2% better in the biomarker-negative group, a finding that could influence clinical decision-making.
[A spokesman for Artera AI.com said the company is working on developing a test based on this
study for commercial availability.]

BOTTOM LINE

PSMA PET/CT scans and applications of AI in prostate cancer management are aiding individualized patient management.

Physics of HDR Brachytherapy for Urologists

Posted by Firas Mourtada, MSE, PhD, DABR | Sep 2023

Firas Mourtada, MSE, PhD, DABR, discusses the physics of high-dose rate (HDR) brachytherapy in this talk sponsored by the American Brachytherapy Society (ABS). Dr. Mourtada enumerates prostate cancer treatment options before identifying HDR brachytherapy as the ultimate approach for dose escalation, asserting that with image guidance, HDR for prostate can be implemented safely and result in an increase in biochemical disease-free survival.

Dr. Mourtada describes the advantages of HDR brachytherapy technology and illustrates how brachytherapy delivers high dose within the prostate, with less dose to surrounding normal tissue. He enumerates advantages such as bringing the source close to the target, using inverse-planning, and the potential for high-efficacy combined with lower-risk of toxicity or secondary malignancy.

Dr. Mourtada reviews common radionuclides in brachytherapy before defining HDR and addressing methodology, workflow, and equipment involved in using transrectal ultrasound (TRUS) for prostate brachytherapy. He explains the feedback loop and illustrates the iterative contouring and reconstruction of the gland that takes place during this workflow and the optimization settings involved.

Dr. Mourtada turns to radiation safety, emphasizing the importance of time, distance, and shielding and citing regulatory radiation safety programs, ALARA (as low as reasonably achievable,) and QMP (Quality Management Program.) He reviews radiation terminology and emphasizes the importance of radiation dosimeters and required radiation area signs.

Dr. Mourtada then concludes that prostate HDR with real-time image guidance provides high-quality implants with an efficient process using inverse planning, HDR radiation exposure is minimal due to the afterloading technology and ALARA controls, and quality management steps are essential to providing high-quality HDR implants.

Future Prospects of AI Technology in the Lower Urinary Tract

Posted by Arnulf Stenzl, MD | Aug 2023

Arnulf Stenzl, MD, discusses the future prospects of artificial intelligence (AI) combined with precision surgery and robotics in the diagnosis and treatment of the lower urinary tract. He outlines an intraoperative multisensory approach for tissue differentiation involving sensor development with mechanical, optical, and electric properties. Combined with AI modeling, the result is a scoring system for intraoperative identification of tissue characteristics based on multimodal/multiscale data with tissue differentiation by optical emission spectroscopy.

Dr. Stenzl displays data on the discrimination of tissue based on electrical impedance. He points out the value of discrimination of deeper tissue layers using model-based optical sensors to see and avoid, for example, vessels and nerves. Dr. Stenzl then describes a device for intraoperative real-time elastography, even at the cellular level.

He emphasizes the importance of consistent AI tissue modeling, covering multiple physical domains to combine different sensors and inform the best actions. Dr. Stenzl explains that AI can extract and reproduce features for navigation during surgery. Dr. Stenzl re-emphasizes the importance of precision surgery moving toward intraoperative diagnostics that builds on the traditional standard of frozen section and predicts the further development of precision surgery and AI technologies in the coming years.

PCa Commentary | Volume 180 – August 2023

Posted by Edward Weber, MD | Aug 2023

Background

Ever since 1675 when the Dutch lens maker, Leeuwenhoek, looked down the newly invented microscope at rainwater and reported seeing ‘animalcules – tiny dancing creatures” (bacteria), pathologists have been similarly looking down their scopes and guiding prostate management by applying their expertise in pattern recognition.

In the 1960s, Dr. Donald Gleason organized those patterns into doublets of 3, 4 (i.e., 3+4) and 5 to create the prognostic Gleason Score — now further refined. Anthony D’Amico, professor of Radiation Oncology at Harvard Medical School is credited for establishing prognostic categories segregating “risk of recurrence” into low-, intermediate- and high-risk prostate cancer (with intermediate-risk now subdivided into favorable” and “unfavorable.”)

[Google reminds us that “A prognostic biomarker provides information about the patient’s overall cancer outcome, regardless of therapy, whilst a predictive biomarker gives information about the effect of a therapeutic intervention.”]

Feng, Spratt et al., have now advanced the art by generating a personalized precision predictive model by utilizing large data sets, machine learning and the less human-dependent “deep learning” — both components of artificial intelligence. Their analysis was directed toward discovering a biomarker that can predict which men with intermediate-risk prostate cancer benefit from the addition of ADT to radiotherapy.

Their study found that some men gained much, but others only minimally. Previous data has found that only 60% of men with intermediate-risk cancer benefit from the addition of ADT to radiotherapy — although those with “unfavorable” intermediate-risk benefit more so. The challenge was identifying who benefits and who does not.

The Spratt AI Study

“Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer,” NEJM Evidence, June 29, 2023., by Dr. Daniel Spratt with many collaborators on behalf of NRG Prostate Cancer AI Consortium.

Dr. Spratt: “With the first-ever predictive biomarker of ADT benefit in prostate cancer, created with AI, we are able to further realize the ability to create a personalized approach for the treatment of cancer.” (Quoted in Precision Medicine News, 2023).

The study was based on “digitized pathology images of pretreatment prostate tissue and clinical data of 5727 patients enrolled in 5 phase 3 randomized trials in which treatment was radiotherapy with or without ADT.” The goal was to develop a binary model to predict the benefit from short-term ADT regarding the likelihood of developing distant metastases.

The article notes that androgen deprivation therapy (ADT) is customarily combined with radiation treatment in this setting. These were trials of radiation treatment for higher grades of prostate cancer, in which there are “no validated predictive models to guide its use.”

Spratt’s colleagues endeavored to establish such a guide – a binary determinant for men with localized intermediate-risk cancer predicting whether “a given patient will benefit from ADT or not“ based on the risk of time to developing distant metastases. They generated such a model by analyzing 4 major randomized clinical trials comparing radiation therapy alone or combined with ADT.

“Data from these trials were acquired and digitized and then were used to train a predictive AI model” to predict the differential benefit of ADT according to their biomarker status. Their image extraction method was described: “For each patient, the tissue across all available digital slides was divided into 256 x 256-pixel patches. … [and the] model was trained on image patches using self-supervised learning. Over 2.5 million tissue patches across four trials … were fed through the model 200 times to train the model.”

The next step was to take this predictive model and validate it using data from RTOG trial 9408 which randomized men with intermediate-risk cancer to radiation treatment plus or minus 4 months of ADT. By applying the AI-derived model, the 15-year estimate for developing distant metastases for biomarker-positive patients treated with ADT was 4% v 14.4% for biomarker-negative ADT patients. In developing their biomarker, they found the best cut-point was 67% for segregating biomarker-positive from biomarker-negative.

By applying the biomarker established in the development model, 543 men were biomarker-positive, indicating that ADT “significantly reduced (by 10.5 percentage points) the risk of distant metastases at 15 years compared to radiotherapy alone.” For 1051 biomarker-negative patients ADT conferred minimal benefit (percentage point benefit 0.5%). For prostate cancer-specific mortality, the comparison of benefits was 10.2% and 1.2%, respectively.

Dr. Spratt concluded, “Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT.” In an interview with ‘News Wise’ Dr. Spratt said: “We are fortunate to be already offering this test at UH Seidman Cancer Center, Case Western Reserve University, to our patients from Northwest Ohio, our nation, and around the world.” (Quoted in News Wise, June 2023)

BOTTOM LINE

The article reviewed in this Commentary is a prime example of how Artificial Intelligence can benefit the clinical management of prostate cancer.

From Artera.ai: “The ArteraAI Prostate Test is a Laboratory Developed Test that is now clinically available through a single CLIA-certified laboratory in Jacksonville, FL. Clinicians who would like to order the ArteraAI Prostate Test can contact us at support@artera.ai. Soon after, a member of our Customer Success team will reach out to set up an account in the ArteraAI Portal to enable order submission.”

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