The Emergence of Ultra-Low–Dose Computed Tomography and the Impending Obsolescence of the Plain Radiograph?

Abstract

Until recently, computed tomographic (CT) examinationsacquired at a radiation exposure equivalent to correspondingplain radiographs would be of grossly substandard imagequality, almost certainly resulting in a failure to adequatelyvisualize many anatomic structures. Over the past decade,successive technical breakthroughs have facilitateddiagnostic-quality CTs to be acquired at rapidly decliningionizing radiation exposures. Today, the mean effectivedose of a radiographic series of the abdomen at 0.7 mSv,pelvis at 0.6 mSv, thoracic and lumbar spine at 1.0 and1.5 mSv, respectively [1] appear licentious when comparedwith exposures achieved in recent low-dose CT trials(Table 1). In an era in which low-dose CT has facilitateda 20% reduction in mortality among smokers [7]. and inwhich doses continue to substantially fall, we propose thatradiologists and clinicians should critically reevaluate therisks and benefits of performing many plain radiographicexaminations.Technical BackgroundIn brief summary, there have been 3 key developments inCT dose reduction technology that have facilitated theaforementioned trend. Automated exposure control ensuresefficient dose delivery by modulating tube current accordingto patient width and attenuation profile [8e10]. Fixed tubecurrent settings were commonplace in older-generation CTsystems and resulted in wider, more attenuating areas, suchas the shoulders receiving the same exposure as narrower lessattenuating regions such as the upper lungs. More recently,algorithms that modulate CT voltage according to patientsize and CT application have also been implemented withgood success [11].After ensuring efficient dose delivery, the largest chal-lenge to obtaining diagnostically acceptable CT images atexposure levels similar to plain radiographs is the severity ofrandom variation in attenuation values that occur within thenormal anatomic structures in these images otherwiseknown as noise. The magnitude of image noise at low CTexposure is fundamentally related to the image reconstruc-tion process [12]. Iterative reconstruction algorithms usea varyingly complex model of the physical characteristics ofthe x-ray tube, beam, and the 3-dimensional interaction ofthe x-ray beam within the patient to reduce noise and areclearly better than more traditional methods of reconstruc-