Considerable emphasis is being placed on the introduction of artificial intelligence (AI) and quantification of diagnostic imaging—both for the purpose of initial diagnosis and treatment monitoring. In an era focusing on improving our decision making results, it is important to recognize the difference between qualitative, semi-quantitative and quantitative imaging. Qualitative imaging—the visual review of imaging by a clinician from which a rendering of disease is present or absent—is flawed with errors in finding diseases (sensitivity) and correctly eliminating (specificity) disease. The focus on quantification has been brought forward by SNMMI, ASNC, and CMS—all calling for quantification of nuclear imaging. This has resulted in the erroneous use of the term quantification for SUV results , when at best SUV is a semi-quantitative method —in contrast to true quantification [3, 4]. These differences can best be appreciated as explained in Table 1 and Fig. 1.
The ability to quantitatively measure the extent of metabolic and regional blood flow differences (RBFDs) makes it possible to determine exactly where (Fig. 2) the patient is on their Health-Spectrum , providing not only for accurate diagnostics but also the ability to provide patient-specific, patient-directed, and patient-oriented treatment—improving treatment outcomes while reducing time, costs, and lives lost from ineffective or harmful treatments.
The introduction of tools has separated humanity from the other animal species for thousands of years. The ability to visually determine the extent of a problem precedes the development of tools used to measure the extent of the problem under consideration; measurements which also make possible the exchange of information that is reproducible, consistent, and accurate.
The development of nuclear imaging has seen several changes over the decades; it has been utilized in medical diagnostics, including the visual interpretation and in recent years, semi-quantitative modeling, which is premised upon assumptions thereby limiting its outcomes as noted by the continued publication of sensitivity and specificity data.
True quantification, however, does not miss disease when present and does not attribute disease to be present when it is not. While qualitative and semi-quantification may be close—close only counts in a game of horseshoes. Close is not acceptable for the practice of medicine and the treatment of patients. True quantification through FMTVDM provides the doorway through which nuclear imaging leaves the world-of-close behind and enters the scientific realm of true measurement, diagnostics, and treatment monitoring of patients.
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The Fleming method for tissue and vascular differentiation and metabolism (FMTVDM) using same state single or sequential quantification comparisons. Patent Number 9566037. Issued 02/14/2017.
Fleming RM, Fleming MR. The importance of thinking about and quantifying disease like cancer and heart disease on a “Health-Spectrum” Continuum. J Compr Cancer Rep. 2019;3(1):1–3 (100011).
FMTVDM is a utility patent that quantitatively measures changes in metabolism and regional blood flow differences (RBFD) present across the transitional tissue changes occurring in heart disease, cancer and other tissues. It is issued to the first author. Figures reproduced by expressed consent of first author.
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Fleming, R.M., Fleming, M.R., Dooley, W.C. et al. The importance of differentiating between qualitative, semi-quantitative, and quantitative imaging—close only counts in horseshoes. Eur J Nucl Med Mol Imaging 47, 753–755 (2020). https://doi.org/10.1007/s00259-019-04668-y