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Cine MRI shows high sensitivity but modest specificity for chest wall invasion in lung cancerCine MRI helps doctors find lung cancer chest wall invasion

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Key Takeaway
Consider cine MRI to rule out chest wall invasion, but confirm positive findings invasively.

This meta-analysis evaluated the diagnostic performance of cine MRI for detecting chest wall invasion in patients with suspected invasion, using surgical and histopathologic analysis as the reference standard. The analysis included 190 patients.

The pooled sensitivity was 99% (95% CI: 34%-100%), and the negative predictive value was 100% (95% CI: 52%-100%), suggesting a high ability to rule out invasion when cine MRI is negative. However, specificity was 74% (95% CI: 64%-82%) and positive predictive value was 50% (95% CI: 39%-61%), indicating that positive findings are often false positives.

The authors note that the wide confidence intervals, particularly for sensitivity and negative predictive value, reflect a limited evidence base. No data on adverse events or tolerability were reported, and funding or conflicts of interest were not disclosed.

In practice, cine MRI may be a useful noninvasive tool for preoperative assessment, especially when CT or static MRI is inconclusive. However, given the modest specificity and positive predictive value, invasive confirmation should be considered before definitive therapeutic decisions. The high sensitivity and negative predictive value support its use for ruling out invasion, but the imprecision of these estimates warrants caution.

How this fits prior evidence

This meta-analysis extends prior coverage of lung cancer diagnostics, which has focused on prediction models for postoperative pneumonia and on biomarkers such as periostin and CDKN3. Unlike those efforts, which address risk stratification or prognosis, this review evaluates a preoperative imaging tool for chest wall invasion. The finding of high sensitivity but modest specificity aligns with the broader theme that no single test is definitive, as seen in the high risk of bias noted in pneumonia prediction models. The wide confidence intervals underscore the need for cautious interpretation, consistent with the context-specific performance of biomarkers like CDKN3.

When doctors treat lung cancer, they must know if the tumor has spread into the chest wall. This information is vital for planning surgery and deciding on the best treatment path. Sometimes, standard scans are not clear enough to give a certain answer, leaving doctors and patients in a difficult spot.

A review of 190 patients found that a specific imaging technique called cine MRI is very effective at ruling out chest wall invasion. It showed a 99 percent sensitivity and a 100 percent negative predictive value. This means that if the scan looks clear, doctors can be very confident that the cancer has not spread into the chest wall.

While the tool is great at ruling out issues, it has a lower positive predictive value of 50 percent. This means that if the scan shows an issue, doctors still need to confirm it with a physical tissue sample before making final decisions. Because the evidence base is still limited, this tool is best used as a helpful guide when other scans are unclear.

What this means for you:
Cine MRI is highly reliable for ruling out chest wall invasion in lung cancer, but invasive tests are still needed for confirmation.

Common questions

How accurate is cine MRI at ruling out chest wall invasion?

Cine MRI is very reliable for ruling out chest wall invasion. It showed a 99 percent sensitivity and a 100 percent negative predictive value. This means that if the scan is clear, it is highly likely that the cancer has not spread into the chest wall.

Can doctors rely on cine MRI alone to confirm a diagnosis?

Not entirely. While the tool is great at ruling out issues, it has a positive predictive value of 50 percent. Because of this, doctors still need to use invasive confirmation, like a tissue sample, before making final treatment decisions.

When is cine MRI most useful for lung cancer patients?

Cine MRI is a helpful noninvasive tool for checking the chest wall before surgery. It is especially useful in cases where standard CT scans or regular MRI scans provide unclear results.

Study Details

Study typeMeta analysis
Sample sizen = 190
EvidenceLevel 1
PublishedNov 2026
View Original Abstract ↓
PURPOSE: To conduct a meta-analysis assessing the effectiveness of cine MRI in evaluating tumor invasion of the chest wall, using surgical and histopathologic analysis as the reference standard. MATERIALS AND METHODS: This systematic review and meta-analysis was conducted following the recommendations of the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy and Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Diagnostic Test Accuracy (PRISMA-DTA) guidelines. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD420250654330. RESULTS: Five prospective studies comprising 190 patients with suspected chest wall invasion were included. The pooled sensitivity of cine MRI for detecting chest wall invasion was 99% (95% CI: 34%-100%), with a specificity of 74% (95% CI: 64%-82%), a negative predictive value of 100% (95% CI: 52%-100%), and a positive predictive value of 50% (95% CI: 39%-61%). No substantial heterogeneity was observed across studies. CONCLUSIONS: Cine MRI showed high sensitivity and excellent negative predictive value for ruling out chest wall invasion in lung cancer. These findings suggest cine MRI may be a useful noninvasive tool for preoperative assessment, particularly in cases with inconclusive CT or static MRI; however, CIs were wide due to the limited evidence base. Conversely, when cine MRI suggests invasion, the modest specificity and positive predictive value highlight the importance of invasive confirmation before definitive therapeutic decisions. Further prospective, multicenter studies using standardized protocols are warranted to validate and expand its clinical application.
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