Proposed Methodology to Evaluate Unnecessary Imaging

Richard C. Semelka1, MD; Jorge Elias Jr2, MD, PhD; Diego R. Martin3, MD

1 From the Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, 27599-7510, U.S.A
2 From the Division of Radiology of the Department of Internal Medicine, University of Sao Paulo, School of Medicine of Ribeirao Preto, Sao Paulo, 14049-900, Brazil

3 From the Department of Radiology, Emory University School of Medicine, Atlanta, GA 30322, U.S.A

Address correspondence to: 
Richard C. Semelka, MD
Department of Radiology 
University of North Carolina at Chapel Hill 
CB# 7510 101 Manning Drive 
Chapel Hill, North Carolina 27599-7510 
phone: (919) 966-9676 
fax: (919) 843-7147 

There is general agreement that a considerable number of imaging procedures performed are unnecessary (1-5). In one publication it was estimated that 1/3 of CTs are unnecessary (6). Unfortunately, the current circumstance is aptly comparable to Mark Twai’s observation: 
“many people talk about the weather, but nobody is doing anything about it”.

Many authorities discuss the problem (7), but concrete proposals are lacking. Hence we have created a heightened environment of anxiety, but with no solutions in sight. We herein propose methodology to determine if imaging procedures are likely to be unnecessary, with guidance for future rational and prudent modification in health care delivery.

The component elements to evaluate whether studies are likely to be unnecessary include all of the following:

1. The pretest probability that the study will be positive.
2. The seriousness of the disease entity.
3. The treatability of the disease process (taking into consideration lesion size and stage of disease).
4. The sensitivity, specificity, predictive values and accuracy of the test.
5. The safety of the procedure: incidence and severity of complications (taking into consideration use of intravenous contrast agents and single study vs multiple study safety).
6. The comparative effectiveness with other approaches, including doing no test.

It should be possible then to create simple numerical scores of the likelihood that the study will be unnecessary. Each of the above mentioned 6 points can have a different weighting. 

Our suggestion would also be to use a body of medical experts who do not have a vested interest in these procedures to render an opinion on these determinations, with the obvious requirement that they will solicit input from experts in the field. A logical specialty to render opinions on radiology would be pathologists.

We will illustrate models of disease processes that we have published research on as examples of how this scoring system would occur, and will also venture estimates of other processes that we do not have direct research experience in. 

Example 1
We have published research that has shown that young adults, ages 18 – 45 years, who undergo pulmonary embolism CT, have a low, 5%, incidence of PE (8). A recent larger study by Mamlouk et al, showed a similar low positive result for PE of 9% (9). So the pretest probability is low – we will use the figure .05. Pulmonary embolism can be life-threatening, so for pt 2 above, we would estimate .8. The treatability of the condition is high, we estimate .8. The accuracy of CT is high, we estimate .8. The safety of CT is moderate with an estimate of .4 (taking into consideration both ionizing radiation and intravenous contrast). 

The comparative effectiveness for CT is high, with an estimate of .8. So the total value of CT in a young adult investigated for PE is .05 x .8 x .8 x .8 x .4 x .8 = .0082.
Using the same disease process if we substitute MR as the imaging modality. The numbers look as follows: pt 1 = .05, pt 2 = .8, pt 3 = .8, pt 4 = .7, pt 5 = .8, pt 6 = .7.

Note the difference in these ratings from CT is that MRI is safer (pt 4 = .7, reflecting the higher safety of the modality and the contrast agents used). The accuracy and the comparative effectiveness are lower (10), but only marginally so (.7 vs .8), which would be different in an elderly population, who would be expected to hold their breath for MRI less well and MRI would therefore score lower. The total value of MR in a young adult population investigated for PE = .0130.

If we now use nuclear medicine V/Q scan as the imaging modality our estimates are as follows: .05 x .8 x .8 x .6 x .4 x .6, for a total = .0046.
For this model of PE in the young adult, all modalities suffer from the very low pretest probability, but we estimate that overall MRI may be the best approach. Although the numerical score is so low that even MRI may not be indicated, as PEs are currently evaluated for in clinical practice. The major need is to increase the pretest probability of a positive result.

Example 2
A second example is a topic that we have considerable experience with (11-18). Imaging of the liver in patients with chronic liver disease. In this patient group a primary diagnostic end-point is detecting small hepatocellular carcinomas. Using contrast-enhanced MRI as the diagnostic test, the following are the evaluations: pt 1 : .30, pt 2 : 1.0, pt 3 : 1.0, pt 4 : .9, pt 5 : .9, pt 6 : 1.0. The rating for MR is .24. Substituting in contrast-enhanced CT as the diagnostic test, the evaluations are : pt 1 = .3, pt 2 : 1.0, pt 3 : 1.0, pt 4 : .7, pt 5 : .3, pt 6 : .8. The rating for CT is .05. Substituting in noncontrast ultrasound, the evaluations are : pt 1 = .3, pt 2 : 1.0, pt 3 : 1.0, pt 4 : .4, pt 5 : 1.0, pt 6 : .4, for a total of 0.048.

Other Examples:
Areas that we do not have expertise in, but taking an educated estimation, may perform especially poorly on a value for patient management scale would be many of the neuroimaging tests. Using headache as the clinical picture, our estimations for contrast enhanced CT are as follows: pt 1 : .01, pt 2 : .5, pt 3 : .1, pt 4 : .3, pt 5 : .5, pt 6 : .5, for a total of .00004. Contrast-enhanced MRI would rate as follows : pt 1 : .01, pt 2 : .5, pt 3 : .1, pt 4 : .7, pt 5 : .9, pt 6 : .9, for a total of .00028.

A final example is evaluation of cardiac disease in the 18-45 year old patient. There may be insignificant differences in population-based outcomes between the following approaches:

1. Clinical history, blood pressure reading, diet and exercise behavior modification
2. Clinical history, blood pressure reading, exercise stress test, diet and exercise behavior modification
3. Clinical history, blood pressure reading, exercise stress test, echocardiography, diet and exercise behavior modification
4. Clinical history, blood pressure reading, exercise stress test, nuclear scintigraphy, diet and exercise behavior modification
5. Clinical history, blood pressure reading, exercise stress test, coronary artery CT, diet and exercise modification
6. Clinical history, blood pressure reading, exercise stress test, MRI, diet and exercise modification.

Assuming then approximate equivalence on a population-based approach, the safest strategies above should be preferred, taking as the secondary consideration cost. Approaches 1 and 2 may be approximately equivalent, with 3 superior to 6, superior to 5, and 4 being the least attractive strategy. Perhaps the most important factor is the behavior modification, which as a treatment approach is likely vastly superior to medication, itself superior to various types of interventional and surgical procedures, except in the most severe cases.

This novel description of using a numerical grading system to assess for the potential value of an imaging procedure, or the corollary of whether a study does not add value to patient care, is readily calculable and implementable. These numbers could undergo continued refinement as our approaches to measure population-based assessments improve. We would recommend that educated individuals, preferably physicians, and preferably physicians who do not have a vested interest in any of the decision outcomes, should be enlisted to calculate these numerical scores. We would anticipate considerable opposition from stake-holders, as recently observed with the debacle over decisions about the age at which women should be screened with mammography (19, 20). There may be no reasonable, prudent, logical alternative though to contain the health care costs which continue to spiral out of control, with no clear benefit to patient outcome (21).

1. Donnelly LF. Reducing Radiation Dose Associated with Pediatric CT by Decreasing Unnecessary Examinations. Am. J. Roentgenol. 2005; 184:655-657.

2. Brenner DJ, Hall EJ. Computed tomography--an increasing source of radiation exposure. N Engl J Med 2007; 357:2277-2284.

3. Stein SC, Fabbri A, Servadei F, Glick HA. A critical comparison of clinical decision instruments for computed tomographic scanning in mild closed traumatic brain injury in adolescents and adults. Ann Emerg Med 2009; 53:180-188.

4. Kuppermann N, Holmes JF, Dayan PS, et al. Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study. Lancet 2009; 374:1160-1170.

5. Holmes JF, Wisner DH, McGahan JP, Mower WR, Kuppermann N. Clinical prediction rules for identifying adults at very low risk for intra-abdominal injuries after blunt trauma. Ann Emerg Med 2009; 54:575-584.

6. Slovis TL, Berdon WE. Panel discussion. Pediatric Radiology 2002; 32:242-244.

7. Brenner DJ, Hricak H. Radiation exposure from medical imaging: time to regulate? Jama 2010; 304:208-209.

8. Heredia V, Ramalho M, Zapparoli M, Semelka RC. Incidence of pulmonary embolism and other chest findings in younger patients using multidetector computed tomography. Acta Radiol 2010; 51:402-406.

9. Mamlouk MD, vanSonnenberg E, Gosalia R, et al. Pulmonary embolism at CT angiography: implications for appropriateness, cost, and radiation exposure in 2003 patients. Radiology 2010; 256:625-632.

10. Altun E, Heredia V, Pamuklar E, Zapparoli M, Semelka RC. Feasibility of post-gadolinium three-dimensional gradient-echo sequence to evaluate the pulmonary arterial vasculature. Magn Reson Imaging 2009; 27:1198-1207.

11. Kanematsu M, Semelka RC, Leonardou P, et al. Angiogenesis in hepatocellular nodules: correlation of MR imaging and vascular endothelial growth factor. J Magn Reson Imaging 2004; 20:426-434.

12. Kanematsu M, Semelka RC, Leonardou P, Mastropasqua M, Lee JK. Hepatocellular carcinoma of diffuse type: MR imaging findings and clinical manifestations. J Magn Reson Imaging 2003; 18:189-195.

13. Karadeniz-Bilgili MY, Braga L, Birchard KR, et al. Hepatocellular carcinoma missed on gadolinium enhanced MR imaging, discovered in liver explants: retrospective evaluation. J Magn Reson Imaging 2006; 23:210-215.

14. Kelekis NL, Semelka RC, Worawattanakul S, et al. Hepatocellular carcinoma in North America: a multiinstitutional study of appearance on T1-weighted, T2-weighted, and serial gadolinium-enhanced gradient-echo images. AJR Am J Roentgenol 1998; 170:1005-1013.

15. Kierans AS, Leonardou P, Hayashi P, et al. MRI findings of rapidly progressive hepatocellular carcinoma. Magn Reson Imaging 2010; 28:790-796.

16. Mastropasqua M, Braga L, Kanematsu M, et al. Hepatic nodules in liver transplantation candidates: MR imaging and underlying hepatic disease. Magn Reson Imaging 2005; 23:557-562.

17. Shah TU, Semelka RC, Pamuklar E, et al. The risk of hepatocellular carcinoma in cirrhotic patients with small liver nodules on MRI. Am J Gastroenterol 2006; 101:533-540.

18. Tsurusaki M, Semelka RC, Uotani K, Sugimoto K, Fujii M, Sugimura K. Prospective comparison of high- and low-spatial-resolution dynamic MR imaging with sensitivity encoding (SENSE) for hypervascular hepatocellular carcinoma. Eur Radiol 2008; 18:2206-2212.

19. Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2009; 151:716-726, W-236.

20. When evidence collides with anecdote, politics, and emotion: breast cancer screening. Ann Intern Med 2010; 152:531-532.

21. Korley FK, Pham JC, Kirsch TD. Use of advanced radiology during visits to US emergency departments for injury-related conditions, 1998-2007. Jama 2010; 304:1465-1471.


Corresponding author :
Richard C. Semelka, M.D.

Department of Radiology  UNC
Chapel Hill
CB 7510 – 2001 Old Clinic Bldg 
Chapel Hill, NC 27599-7510
Phone: (919) 966-9676
Fax: (919) 843-7147
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