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Original Research |
1 Department of Radiology, Ohme Municipal General Hospital, 4-16-5,
Higashi-Ohme, Ohme City, Tokyo 198-0042, Japan.
2 Department of Pulmonary Medicine, Ohme Municipal General Hospital, Ohme City,
Tokyo, Japan.
3 Present address: Department of Pulmonary Medicine, National Printing Bureau
Tokyo Hospital, Tokyo, Japan.
4 Department of Pathology, Ohme Municipal General Hospital, Ohme City, Tokyo,
Japan.
5 Present address: Department of Pathology, Kurashiki Medical Center, Kurashiki,
Japan.
6 Present address: Department of Pulmonary Medicine, Graduate School of Tokyo
Medical and Dental University, Tokyo, Japan.
Received September 10, 2007;
accepted after revision February 15, 2008.
Address correspondence to S. Satoh.
Abstract
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MATERIALS AND METHODS. This study included 54 pulmonary nodules
(
5 mm in diameter) in 51 consecutive patients (37 men, 14 women; mean
age, 65.7 years; age range, 31–88 years). Thirty-six (67%) of the 54
pulmonary nodules were malignant, and 18 (33%) were benign. Two radiologists
independently reviewed the signal intensity of the nodules on DWI with a b
factor of 1,000 s/mm2 using a 5-point rank scale without knowledge
of clinical data. This scale was based on the following scores: 1, nearly no
signal intensity; 2, signal intensity between 1 and 3; 3, signal intensity
almost equal to that of the thoracic spinal cord; 4, higher signal intensity
than that of the spinal cord; and 5, much higher signal intensity than that of
the spinal cord. The Mann-Whitney U test and the receiver operating
characteristic (ROC) curve were used to calculate the difference between the
scores of malignant and benign nodules.
RESULTS. On DWI, the mean score of malignant pulmonary nodules (4.03 ± 1.16 [SD]) was significantly higher (p < 0.01) than that of benign nodules (2.50 ± 1.47), with an area under the ROC curve of 0.796 (95% CI, 0.665–0.927). When a score of 3 was considered as a threshold, the sensitivity, specificity, and accuracy were 88.9% (95% CI, 78.6–99.2%), 61.1% (38.6–83.6%), and 79.6% (68.9–90.3%), respectively. Three small metastatic nodules (13, 16, and 20 mm) and one bronchioloalveolar carcinoma scored 1 or 2 on the 5-point rank scale. Three granulomas, two active inflammatory lung nodules, and one fibrous nodule scored 4 or 5.
CONCLUSION. The signal intensity of pulmonary nodules may be useful for malignant and benign differentiation on DWI. However, the interpretation of small metastatic nodules, nonsolid adenocarcinoma, some granulomas, and active inflammatory nodules should be approached with caution.
Keywords: b factor • diffusion-weighted imaging • lung cancer • MRI • pulmonary nodules
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Morphologic analysis based on the assessment of size, shape, and internal characteristics using CT has been the mainstay in evaluating pulmonary nodules. A nodule having a corona radiata appearance is likely to be malignant, whereas the presence of intranodular fat is a reliable indicator of a hamartoma [4]. In general, the smaller the nodule, the more likely it is to be benign, especially nodules less than 5 mm in diameter [4, 5]. Findings of both calcification and lack of growth for at least 2 years are generally accepted as reliable signs of a benign nodule, but other findings have not proven useful for malignant and benign differentiation [4]. The evaluation of tumor vascularity using contrast-enhanced CT has proven to be useful for distinguishing malignant nodules from benign nodules [6]. In particular, the absence of significant lung nodule enhancement on CT is strongly predictive of benignancy [7]. However, when the nodules had significant enhancement, some overlap was found especially between active granulomas or hypervascular benign tumors and malignant nodules [8, 9].
Although MRI is used relatively infrequently because of its comparatively high cost, it has an inherent advantage in terms of tissue characterization. Indeed, some investigators have tried to discriminate malignancy from benign lung tumors by measuring their relaxation times, although the results have not been satisfactory because of a significant overlap of values [10, 11]. Tissue contrast attained using diffusion-weighted imaging (DWI) is different from that attained using conventional MR sequences. The diffusion technique reflects the diffusion motion of water protons in the tissues, producing different contrast in different kinds of tissues. Promising results have been achieved using this technique for differentiation between malignant and benign nodules in the liver [12, 13], bone marrow [14], and head and neck [15]. However, to our knowledge, there have been no reports about DWI applied to pulmonary nodules for differentiating malignancy from benignancy because the images in this area are likely to have susceptibility artifacts [16].
Takahara et al. [17] introduced a new technique of DWI using a STIR sequence with a high b factor and free breathing with 10 excitations and concluded that this technique allows screening for malignancies in the entire body. Their results showed that a free-breathing technique with 10 excitations and STIR produced a higher contrast-to-noise ratio and good fat suppression compared with a breath-hold technique with 2 excitations and a chemical shift–selective pulse [17, 18]. The purpose of our study was to perform DWI of pulmonary nodules and evaluate whether DWI can be used to differentiate malignant from benign nodules and to analyze pulmonary nodules that are difficult to characterize as benign or malignant.
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Subjects
In this study, between November 2004 and April 2006, patients were selected
according to the following criteria: one or two pulmonary nodules or masses
detected on CT that needed further evaluation; absence of calcification or
definite fat attenuation of the nodule or mass on CT; absence of histologic
diagnosis; absence of history of immunodeficiency; and ability to undergo the
procedure. Single-detector CT (X-Vigor, Toshiba Medical) was performed with
the patient in the supine position. Contiguous 10-mm scans were obtained
during breath-holding and full inspiration from the lung apex to the lung base
in all patients. The tube current was 120 kVp at 200 mA.
This study included 54 pulmonary nodules in 51 consecutive patients (37 men, 14 women; mean age, 65.7 years; age range, 31–88 years) who underwent DWI in the department of radiology in our hospital. Three patients had two pulmonary nodules, and the remaining 48 patients had solitary pulmonary nodules.
MRI Techniques
All MR examinations were performed with a commercially available 1.5-T
whole-body MR unit (Intera NovaDual, Philips Healthcare) with a maximum
gradient strength of 33 mT/m and a slew rate of 160 mT/m/s using a
sensitivity-encoding (SENSE) body coil. All patients were examined in the
supine position throughout the examination. Before DWI, dual-echo T1-weighted
fast-field echo MRI or T1-weighted turbo spin-echo MRI was performed. The
dual-echo T1-weighted fast-field echo sequence was performed with the
following parameters: TR range/opposed-phase TE, in-phase TE,
70–150/2.3, 4.6; flip angle, 80°; matrix size, 208 x 256;
SENSE reduction factor, 1.7; field of view, 25–30 x 25–30
cm; number of signals acquired, 2; section thickness, 5 mm; section gap, 1 mm;
number of sections acquired, 18–40; and acquisition time, 18.1 seconds.
MR images were obtained during end-inspiration breath-holding. The T1-weighted
turbo spin-echo sequence was performed with the following parameters: TR
range/TE range, 330–1,000/12–15; echo-train length, 5–7;
matrix size, 208–224 x 256–512; SENSE reduction factor, 1.8;
field of view, 25 x 25 cm; number of signals acquired, 1–2;
section thickness, 5–6 mm; section gap, 0.5–1 mm; number of
sections acquired, 9–40; and acquisition time, 17–30 seconds. MR
images were obtained during end-inspiration breath-holding after one or two
breaths.
The subsequent DWI sequence was performed with the following parameters: TR/TE range, infinite/50–70; b factors, 0 and 1,000 s/mm2; STIR; matrix size, 256 x 128; half scan factor, 0.6; SENSE reduction factor, 2; field of view, 30–40 x 30–40 cm; number of signals acquired, 10; section thickness, 4 mm; section gap, –1 mm (overlap); number of transverse sections acquired, 50–80; and imaging time, 193–343 seconds. MR images were obtained during free breathing. The motion-probing gradients were placed in three axial directions. The echoplanar imaging factor was 45, and water–fat shift was 8.583 pixels.
MRI Analysis
Two radiologists, with 9 and 6 years' experience, respectively, worked
together to retrospectively evaluate the signal intensity of lung nodules on
DW images (b factor = 1,000 s/mm2) and T2-weighted images (b factor
= 0 s/mm2) in a transverse plane using a 5-point rank scale without
knowledge of patient CT features and clinical data; final decisions regarding
the scale were reached by consensus. We evaluated T2-weighted images to
examine how they may affect DW images of lung nodules
[19,
20].
The scale for DW images was based on the following scores: 1, nearly no signal intensity, as seen in an almost normal lung; 2, signal intensity between 1 and 3; 3, signal intensity almost equal to that of the spinal cord at the thoracic spine [15]; 4, higher signal intensity than that of the spinal cord; and 5, much higher signal intensity than that of the spinal cord. The interval between 3 and 4 was nearly the same as the interval between 2 and 3. Wang et al. [15] suggested that the spinal cord should replace the CSF as a reference on DW images [21].
The scale for T2-weighted images was based on the following scores: 1, nearly no signal intensity, as seen in an almost normal lung; 2, signal intensity almost equal to that of the dorsal muscles; 3, lower signal intensity between 2 and 5; 4, higher signal intensity between 2 and 5; and 5, signal intensity almost equal to that of CSF at the thoracic spine [15] or a saline bag on the opposite side of a pulmonary nodule that was detected on CT. CSF has been used as a reference on echo-planar MR images by some researchers [15, 21]. However, we used a saline bag together with CSF beginning in February 2005 because, as discussed by Wang et al. [15], subarachnoid spaces of the thoracic spine were sometimes difficult to evaluate as a reference in some patients in an imaged area that was less than 5 mm in diameter. Apparent diffusion coefficient (ADC) maps of lung nodules were not available because of their susceptibility artifacts.
In this study, nodules of 5 mm or larger in diameter were included. The diameter was calculated using the mean of the long- and short-axis diameters of nodules or masses on T1-weighted images. The anatomic distribution of pulmonary nodules was classified as the upper or lower lung zone from the carina.
Final Diagnosis
The final diagnoses were made histologically or clinically. Without
knowledge of the results of the 5-point rank scale, one pathologist
interpreted the histologic diagnoses of specimens from surgery or biopsy.
Clinical diagnoses were made by pulmonologists who were unaware of the results
of the 5-point rank scale using clinical data and results of radiologic
follow-up studies. Nodules or masses were classified as granulomas if a
diagnosis was confirmed histologically or bacteriologically (e.g.,
tuberculoma) or if there was radiologic evidence of no growth during at least
2 years of follow-up [7]. The
diagnoses of pulmonary nodules were classified as benign if the nodules were
established with radiologic follow-up studies that revealed disappearance or
significant regression of the nodules after initiation of antibacterial or
steroid therapy [15].
Statistical Analysis
The Mann-Whitney U test was used to calculate the difference in
the median score on the 5-point rank scale of DW images and T2-weighted images
between malignant and benign nodules. A p value of less than 0.05 was
considered to indicate a significant difference. We used the receiver
operating characteristic (ROC) curve to evaluate the diagnostic capability of
the 5-point rank scale for differentiation between malignant and benign
lesions. We determined the threshold score showing the highest accuracy.
Scores equal to the threshold and higher were considered to indicate malignant
pulmonary nodules, and scores below the threshold were considered to indicate
benign lung nodules. Statistical analyses were performed with SPSS software
(version 13.0, SPSS).
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The diagnoses of the 54 nodules are listed in the Table 1. Thirty-six nodules of 34 patients were malignant and 18 nodules of 18 patients were benign. One patient had one malignant nodule and one benign nodule.
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MRI Analysis
The scores on the 5-point rank scale used to evaluate malignant and benign
pulmonary nodules on DW images were 4.03 ± 1.16 and 2.50 ± 1.47
(mean ± SD), respectively (Figs.
1A,
1B,
1C,
1D,
2A,
2B,
2C, and
2D). The scores on the 5-point
rank scale used to evaluate malignant and benign pulmonary nodules on
T2-weighted images were 3.36 ± 0.64 and 2.94 ± 0.94
respectively. The mean nodular size was 33.8 ± 23.7 mm. Twenty-five
pulmonary nodules were located in the upper lung zone from the carina, whereas
29 nodules were in the lower lung zone.
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On T2-weighted images, the scores on the 5-point rank scale of malignant pulmonary nodules (3.36 ± 0.639) were not significantly higher (p = 0.083) than those of benign nodules (2.94 ± 0.938).
On DW images, no significant difference in scores was found between upper and lower lung zones in terms of malignant nodules (4.28 ± 1.10 and 3.89 ± 1.20, respectively; p = 0.334) or benign nodules (2.38 ± 1.51 and 2.80 ± 1.55, respectively; p = 0.756).
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Swensen et al. [7] reported that distinguishing between malignant and benign solitary pulmonary nodules on contrast-enhanced CT images showed an average area under the ROC curve of 0.831 or 0.785 (the Shiga cohort). In contrast, our results from DWI data alone showed the average area under the ROC curve to be 0.796. Diagnosis of the solitary pulmonary nodule is a difficult task when attempting to do so primarily from a visual interpretation of the imaging data alone. Our results indicate that interpretation using DWI performed with a b factor of 1,000 s/mm2 has the potential to distinguish malignant from benign pulmonary nodules.
According to Wang et al. [15], DW images obtained with a b factor of 1,000 s/mm2 may be used to characterize head and neck lesions. Although the area under the ROC curve for use in differentiating malignancies from benign lesions was 0.87 in their results, which is higher than ours (0.796), this difference could be explained, at least in part, by several factors. First, Wang et al. excluded patients who had a local distortion that affected the lesions and had ADC maps that were suboptimal because of susceptibility artifacts. In contrast, almost all of our patients had local distortion between the pulmonary nodules and surrounding aerated lungs due to susceptibility artifacts. Second, breathing artifacts were minimal in head and neck lesions in their study, whereas these artifacts could not be avoided in pulmonary nodules because patients were free-breathing. Third, benign cystic lesions were common in head and neck lesions in their study, and their mean ADC was significantly larger than that of carcinomas, whereas there were no benign cystic pulmonary nodules in our study group.
The interpretation by signal intensity using DW images of nonsolid neoplasms and active inflammatory pulmonary nodules was difficult in our study. The differences in signal intensities may reflect differences in histopathologic features; malignant tumors generally have enlarged cells and show hypercellularity [22]. Bronchioloalveolar carcinoma, however, did not reveal such large cells and did not show hypercellularity. Lung abscesses and active tuberculosis may have had numerous inflammatory cells gathering in the nodules and resultant higher signal intensities, even though they were benign pulmonary nodules.
The diagnostic information provided by DW images and ADC maps is not identical. The signal intensity on DW images is mainly influenced by T2 relaxation and the ADC [19, 20]. Increases in T2, such as those typically seen with brain infarcts, cause an increased signal intensity of lesions on DW images [19, 20, 23]. This may be explained by a simultaneous increase in cytotoxic and vasogenic neuronal edema [24]. Clinically, the increase in mean signal intensity on T2-weighted images corresponds well with the typical development of brain swelling. However, in our study, the signal intensity on T2-weighted MR images could not be used to distinguish malignancy from benign pulmonary nodules. Unlike brain infarcts, the T2 effect may not substantially influence DW images in lung nodule differentiation. Although we cannot fully explain this difference between brain infarcts and lung neoplasms in our results, the main reason may be that lung neoplasms contain little edema or scant tissue swelling.
Takahara et al. [17] reported on whole-body DWI using a background body-signal suppression technique. This technique used free breathing, STIR, and a high-resolution 3D display. They compared their DWI technique with a technique involving a sequence of breath-holding with 2 excitations and a chemical shift–selective pulse and concluded that free breathing with 10 excitations and STIR had a higher contrast-to-noise ratio than the other technique and had good fat suppression [17, 18]. However, further study may be required to confirm their conclusions.
The differences in mean signal intensities between malignant and benign pulmonary nodules were slightly closer in the lower lung zone than those in the upper lung zone. These results indicate that breathing artifacts, mainly caused by diaphragmatic motion during free breathing, could close the difference in signal intensity between malignant and benign pulmonary nodules. We recommend obtaining DW images using respiratory gating, especially if there is a nodule in the lower lung zone.
When the score of 3, which was a nodule with a signal intensity with nearly
the same signal intensity as the spinal cord, was considered as a threshold,
the maximum accuracy obtained was 79.6%, which is not particularly high. This
accuracy is low because our study group had comparatively many benign
pulmonary nodules (n = 18). For example, when the pulmonary nodules
were confined to more than 20 mm in diameter, the number of benign lung
nodules decreased from 18 to six (malignancy, from 36 to 28), and the accuracy
increased from 79.6% to 88.2%. However, the area under the ROC curve was
similar (0.796 vs 0.773). It can be shown that accuracy is equivalent to
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There are several limitations to this study. First, avoiding susceptibility artifacts on DWI of pulmonary nodules is difficult. This is the reason we used the 5-point rank scale rather than ADC maps. Wang et al. [15] reported that they were unable to measure ADC values of lesions located adjacent to air-containing organs because of susceptibility artifacts. In our study, these artifacts may have made it difficult to interpret pulmonary nodules, resulting in a reduction of the area under the ROC curve and of diagnostic accuracy. Second, in our final diagnosis, histologic and bacteriologic confirmations were made in only 83.3% (45/54) of patients, and the remaining cases (benignancy, n = 9) had clinical data and radiologic follow-up confirmation. However, not all benign pulmonary nodules need histologic confirmation. We introduced clinical data and radiologic follow-up confirmation to avoid a selection bias that would exclude mainly benign pulmonary nodules from the study sample. If the study group includes fewer benign pulmonary nodules, it is difficult to analyze benign nodules that mimic malignancies on DWI, which was one of the aims of our study.
In conclusion, the signal intensity of pulmonary nodules may be useful for malignant and benign differentiation on DW images. However, the interpretation of signal intensity of small metastatic pulmonary nodules, nonsolid adenocarcinoma, some granulomas, and active inflammatory lung nodules should be treated with caution. Unlike conventional MR sequences, DWI is the only sequence that may be used to help in distinguishing malignant from benign pulmonary nodules. Further elucidation of the relationship between signal intensity on DWI and pulmonary nodules and reduction of susceptibility and motion artifacts will be required in the future.
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