Point Counter Point: The Case for Cognitive

Описание: Alexander Kenigsberg, MD, Assistant Professor, Director of Urologic Oncology, Virginia Commonwealth University Health, Massey Comprehensive Cancer Center, Richmond, Virginia, presents a detailed comparison of cognitive fusion and software fusion, reviewing accuracy data, workflow considerations, and focal therapy requirements. He begins by outlining the rationale for focal therapy, which aims to ablate the index lesion while avoiding the morbidity associated with whole-gland treatment. He explains the definitions of focal, partial gland, and quadrant-based ablation and positions his discussion within the context of partial gland ablation.

He describes software fusion as the overlay of previously acquired magnetic resonance imaging (MRI) onto real-time ultrasound with either rigid or elastic registration. He states that while software fusion offers three-dimensional reconstruction, deformation of the prostate limits the accuracy of registration. He highlights research showing that, despite technological sophistication, software platforms introduce targeting error.

Dr. Kenigsberg reviews biopsy evidence demonstrating that MRI-targeted biopsies improve the detection of clinically significant disease and reduce the identification of indolent disease. He then notes that equivalence studies show similar performance between cognitive and software fusion for biopsy targeting. He explains that even expert users of software platforms demonstrate a targeting error of three to six millimeters, and that novices have a greater error. He emphasises that millimeters matter.

He argues that these compounding errors make extreme precision unrealistic and that anatomic ablation strategies remain appropriate. He notes that hemiablation has declined over time but continues to be used. He presents evidence that anatomic ablation yields comparable quality of life and improved oncologic outcomes in some settings. He notes that cognitive fusion is dependable when paired with anatomic understanding, margin-based planning, and the use of simple tools that measure lesion size and treatment boundaries.

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