Medical imaging is vital for diagnosing and monitoring health conditions. However, images can contain unintended features or distortions called artifacts. These anomalies are introduced during image acquisition or processing, not actual anatomical structures. Recognizing them is important for accurate interpretation, though their presence doesn’t always indicate a problem with the patient or equipment.
Patient-Related Factors
Patient movement during a scan frequently causes image artifacts. Voluntary actions like fidgeting, or involuntary ones such as breathing or heartbeats, can blur or distort images, often appearing as “ghosting” or smearing. This happens because movement disrupts the precise spatial alignment of data, making it difficult for the system to reconstruct a clear picture.
Metallic objects within or on the patient’s body also introduce artifacts. Implants like dental fillings, surgical clips, prostheses, or jewelry interact with imaging energy, causing distortions. In MRI, metal can lead to signal loss, distorted geometry, or bright signal pile-up due to differences in magnetic susceptibility. In CT scans, metal absorbs X-rays differently than body tissues, resulting in streaks or shading artifacts.
The body’s own physiological processes can also create apparent artifacts. Functions like blood flow or gas in the bowel cause signal variations. For instance, cerebrospinal fluid pulsation or chemical shift between fat and water can appear as subtle MRI distortions. Medical professionals typically recognize these as normal physiological phenomena, not errors.
Imaging System and Physics Factors
Every medical imaging system has inherent limitations contributing to image imperfections. Factors like resolution (smallest distinguishable detail) and signal-to-noise ratio (image clarity relative to background interference) define achievable quality. These physical constraints mean some “noise” or less-than-perfect image quality is always present.
Converting raw data into a visible image can introduce specific artifacts. For example, “ringing” or Gibbs artifacts in MRI appear as oscillations near sharp boundaries due to mathematical image reconstruction. In CT, beam hardening occurs when X-rays pass through dense tissues like bone or metal; lower-energy X-rays are absorbed more readily, leaving a “harder” beam of higher-energy photons. This can cause dark streaks between dense objects or a “cupping” effect.
Though less common due to stringent quality control, equipment malfunction can lead to artifacts. Detector issues, such as a single element providing erroneous readings, can result in circular or “ring” artifacts in CT scans. Tube arcing in X-ray tubes can manifest as random bright streaks. Regular maintenance and calibration minimize these hardware issues.
Operator and External Factors
The technologist’s technique influences image quality. Incorrect patient positioning can lead to misaligned or incomplete images. Inappropriate scanning parameters, such as a low CT dose or improper timing in contrast studies, can degrade image quality and introduce artifacts that obscure diagnostic information.
External environmental factors can interfere with imaging systems. MRI is particularly sensitive to external electrical signals or radio frequencies. Interference from nearby medical devices or a leaky radiofrequency shielded room can produce “zipper” artifacts (linear bright or dark lines). Such interferences disrupt the delicate magnetic fields and radio signals used to generate MRI images.
Infrequent software glitches during image reconstruction can also generate artifacts. These errors might arise from programming flaws or unexpected data interactions, leading to distortions not present in the raw data. While modern systems are sophisticated, such anomalies can result in misleading features on the final image.
Addressing Artifacts and Their Impact
Artifacts can obscure anatomical details or mimic medical conditions, potentially complicating diagnosis. However, experienced radiologists and technologists are trained to recognize these distortions and differentiate them from true pathology. This expertise helps ensure artifacts do not necessarily lead to misdiagnosis.
Various mitigation strategies minimize or eliminate artifacts. For patient motion, technologists provide clear instructions for stillness; sedation may be used for children or uncooperative patients. Specialized scanning sequences, like motion compensation techniques or faster acquisition times, also reduce motion effects. For metallic implants, specific software algorithms, such as MARS in MRI or iterative reconstruction in CT, suppress metal-induced distortions.
Patients play a part in minimizing artifacts by following instructions carefully. Disclosing metallic implants, jewelry, or permanent makeup beforehand allows the medical team to adjust protocols or take precautions. Artifacts are a common, expected aspect of medical imaging, and medical teams manage them effectively, ensuring diagnostic image quality.