Automated Color-Coding of Lesion Changes in Contrast-Enhanced 3D T1-Weighted Sequences for MRI Follow-up of Brain
D Zopfs1, K Laukamp2, R Reimer2
1From the Institute for Diagnostic and Interventional Radiology (D.Z., K.L., R.R., N.G.H., C.K., L.P., A.C.B., M.S., S.L.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany David.zopfs@uk-koeln.de.
Background And Purpose:
MR imaging is the technique of choice for follow-up of patients with brain metastases, yet the radiologic assessment is often tedious and error-prone, especially in examinations with multiple metastases or subtle changes. This study aimed to determine whether using automated color-coding improves the radiologic assessment of brain metastases compared with conventional reading.
Materials And Methods:
One hundred twenty-one pairs of follow-up examinations of patients with brain metastases were assessed. Two radiologists determined the presence of progression, regression, mixed changes, or stable disease between the follow-up examinations and indicated subjective diagnostic certainty regarding their decisions in a conventional reading and a second reading using automated color-coding after an interval of 8 weeks.
Results:
The rate of correctly classified diagnoses was higher (91.3%, 221/242, versus 74.0%, 179/242, P < .01) when using automated color-coding, and the median Likert score for diagnostic certainty improved from 2 (interquartile range, 2-3) to 4 (interquartile range, 3-5) (P < .05) compared with the conventional reading. Interrater agreement was excellent (κ = 0.80; 95% CI, 0.71-0.89) with automated color-coding compared with a moderate agreement (κ = 0.46; 95% CI, 0.34-0.58) with the conventional reading approach. When considering the time required for image preprocessing, the overall average time for reading an examination was longer in the automated color-coding approach (91.5 [SD, 23.1] seconds versus 79.4 [SD, 34.7 ] seconds, P < .001).
Conclusions:
Compared with the conventional reading, automated color-coding of lesion changes in follow-up examinations of patients with brain metastases significantly increased the rate of correct diagnoses and resulted in higher diagnostic certainty.
Insights
Automated color-coding significantly improved the accuracy and certainty of radiologic assessments for brain metastases follow-up compared to conventional methods. This technique enhances diagnostic performance in MR imaging for patients with brain metastases.
Area of Science:
- Radiology
- Medical Imaging
- Oncology
Background:
- Magnetic resonance (MR) imaging is crucial for monitoring brain metastases.
- Conventional radiologic assessment can be challenging due to complexity and subtle changes.
- Objective evaluation of treatment response is vital for patient management.
Purpose of the Study:
- To evaluate if automated color-coding enhances radiologic assessment of brain metastases.
- To compare diagnostic accuracy and certainty between automated color-coding and conventional reading.
- To assess interrater agreement and reading time with the new method.
Main Methods:
- 121 pairs of follow-up MR examinations of brain metastases patients were reviewed.
- Two radiologists performed assessments using conventional reading and automated color-coding.
- Diagnostic certainty was rated using a Likert scale; interrater agreement was calculated.
Main Results:
- Automated color-coding increased correct diagnoses from 74.0% to 91.3% (P < .01).
- Diagnostic certainty improved significantly (median Likert score 4 vs. 2, P < .05).
- Interrater agreement was excellent (κ = 0.80) with color-coding versus moderate (κ = 0.46) conventionally.
Conclusions:
- Automated color-coding significantly improves diagnostic accuracy for brain metastases follow-up.
- This method enhances radiologist diagnostic certainty and interrater reliability.
- Despite slightly longer reading times, the benefits in accuracy and certainty are substantial.
