The impact of the field of view (FOV) on image quality in MDCT angiography of the lower extremities

Abstract

Objectives To evaluate the impact of the reconstructed field-of-view (FOV) on image quality in computed-tomography angiography (CTA) of the lower extremities. Methods A total of 100 CTA examinations of the lower extremities were acquired on a 2 × 192-slice multidetector CT (MDCT) scanner. Three different datasets were reconstructed covering both legs (standard FOV size) as well as each leg separately (reduced FOV size). The subjective image quality was evaluated for the different vessel segments (femoral, popliteal, crural, pedal) by three readers using a semi-quantitative Likert scale. Additionally, objective image quality was assessed using an automated image quality metric on a per-slice basis. Results The subjective assessment of the image quality showed an almost perfect interrater agreement. The image quality of the small FOV datasets was rated significantly higher as compared to the large datasets for all patients and vessel segments (p < 0.05) with a tendency towards a higher effect in smaller vessels. The difference of the mean scores between the group with the large FOV and small FOV was 0.68 for the femoral level, 0.83 for the popliteal level, 1.12 for the crural level, and 1.08 for the pedal level. The objective image quality metric also demonstrated a significant improvement of image quality in the small FOV datasets. Conclusions Side-separated reconstruction of each leg in CTA of the lower extremities using a small reconstruction FOV significantly improves image quality as compared to a standard reconstruction with a large FOV covering both legs. Key Points • In CT angiography of the lower legs, the side-separated reconstruction of each leg using a small field-of-views improves image quality as compared to a standard reconstruction covering both legs. • The side-separated reconstruction can be readily implemented at every commercially available CT scanner. • There is no need for additional hardware or software and no additional burden to the patient.

Can small-field-of-view reconstruction CT better evaluate lung nodule than conventional CT analyzed by multi-instance learning lung nodule system ?

“…Smaller FOVs of CT images are usually associated with clearer images and higher resolution [12] . As reported that a small FOV reconstruction in CT angiography of lower extremities signi cantly improved image quality compared with a large FOV reconstruction covering two legs [13] . In order to explore a better approach to present pulmonary nodules.…”

“…On the premise of maintaining diagnostic performance and refusing excessive radiation, the small-eld-of-view reconstruction CT images (sFOV-CT) increased pixel density across airway structures and reduced partial volume effects [8] . As is well-known that the decrease of reconstructed FOV has a bene cial impact on image quality using both subjective and objective measures [9] . The sFOV reconstruction approach via reducing FOV has been widely studied in the diffusing-weighted sequence in prostate cancer [10] , rectal carcinoma [11] , and so on.…”

Multi-instance learning based lung nodule system for assessment of CT quality after small-field-of-view reconstruction

“…Smaller FOVs in CT images are often associated with clearer and higher resolution images 12 . Studies have reported that a small FOV reconstruction in CT angiography of the lower extremities significantly improved image quality compared to a large FOV reconstruction covering two legs 9 . In order to explore a better approach to presenting pulmonary nodules, we applied an sFOV reconstruction algorithm to c-CT images and compared their difference statistically.…”

“…Moreover, sFOV in CT are proved to be associated with higher spatial resolution and clearer images after subjective evaluation by radiologists. It has been demonstrated that reducing the reconstructed field of view (FOV) has a beneficial impact on increasing diagnostic image quality in CTA run-off examinations, regardless of vessel size 9 . Furthermore, a smaller and adjusted FOV or an increased matrix was well established to improve the spatial resolution in other part of body in CT 8 .…”

CT angiography of the lower limbs: combining small field of view with large matrix size and iterative reconstruction further improves image quality of below-the-knee arteries

“…Approaches to increase the image quality and diagnostic accuracy include optimization of acquisition parameters (10)(11)(12) and optimization of reconstruction parameters, including the use of innovative reconstruction algorithms beyond filtered back projection (FBP) (2,13). In addition to these algorithms, it is also possible to improve the image quality and spatial resolution by reducing the reconstruction field of view (FOV) with side-separate reconstruction of the legs, which results in sharper images (14). Another approach to improve the spatial resolution and sharpness of structures is to increase the size of the reconstruction matrix (15)(16)(17).…”