Acquisition

The measurement of metabolites with MR spectroscopy is generally limited by sensitivity considerations, as these molecules are typically present at concentrations approximately 10,000 times lower than the water and lipid signals imaged with MR imaging. The most obvious factor affecting measurement sensitivity is field strength. The majority of breast MR spectroscopy studies performed to date have used standard 1.5 T MR scanners. There have been no published reports of in vivo breast MR spectroscopy with lower-field MR scanners. Several recent publications have used 3 T MR scanners, which offer approximately twice the signal-to-noise ratio (SNR) of a 1.5 T system. The higher field strength also increases the spectral resolution, making it easier to distinguish between closely overlapping resonances in the spectral domain. There are some potential disadvantages of the higher field, which tend to increase the number of experimental corrections that are required to perform unbiased quantitative spectroscopy (eg, corrections for T ₁ , T ₂ , transmit, and receive efficiency). Balancing advantages and disadvantages, the higher field strength is generally thought of as beneficial for MR spectroscopy applications. Research studies from even higher-field MR systems have helped accelerate the development of techniques for MR spectroscopy of the breast. MR imaging and spectroscopy of the breast at 7 T in particular may have a role in future clinical applications, but the currently available 1.5 T and 3 T systems are both suitable for breast MR spectroscopy studies in clinical research.

In addition to field strength, the design of the breast receive coil can have a large impact on sensitivity. There is a variety of breast coils currently available on the market, varying in ergonomics, number of receive channels, and biopsy capability. The higher channel-count coils can provide increased sensitivity but with decreased homogeneity, which can complicate analysis of MR spectroscopy. The increase in parallel imaging performance provided by these coils is not typically exploited in breast MR spectroscopy, although it can have some advantage when used with fast spectroscopic imaging techniques.

Two distinct localization approaches have been used for breast MR spectroscopy. Single-voxel spectroscopy (SVS) has been most widely used. SVS uses a STEAM (Stimulated Echo Acquisition Mode) or PRESS (Point-Resolved Spectroscopy) pulse sequence to select the MR signal from a single cuboid volume called a voxel. A single spectrum is produced, which represents the average chemical signal from the voxel. Sequences for SVS are widely available, and some manufacturers provide specific SVS protocols optimized for breast MR spectroscopy. An alternative localization technique is chemical-shift imaging or MR spectroscopic imaging. In this technique, a larger volume is excited, and 2D or 3D phase encoding is used to produce a spatially resolved grid of spectra.

The sensitivity of MR spectroscopic imaging and SVS are the same, which means that for a given voxel size and acquisition time they both produce the same SNR in each voxel. In that time, however, SVS produces a single spectrum from one region, whereas MR spectroscopic imaging produces a matrix of spectra over a larger region. However, MR spectroscopic imaging generally requires more time to acquire because the full phase encoding must be sampled before reconstruction. Of note, some breast MR spectroscopic imaging studies have used a phase-encoding scheme with weighted averaging to increase SNR and reduce the leakage of signals between adjacent voxels in the MR spectroscopic imaging grid, but this also causes blurring. Commonly these studies only report the nominal voxel size, but in terms of SNR the effective voxel size is substantially larger than the nominal size, and this should be considered when comparing studies.

SVS and MR spectroscopic imaging offer distinct advantages and disadvantages for breast MR spectroscopy. SVS can generally produce better spectral quality, as it has better localization performance, and the scanner calibrations (B ₀ shim, flip angle, water and fat suppression) can be better optimized over the smaller region. Furthermore, SVS is less sensitive to subject motion during the scan, and is more easily used for quantitative spectroscopy analyses. However, SVS requires that the voxel placement be performed while the patient is in the scanner. Some expertise is required to perform this quickly and consistently, and it can be difficult to integrate into the clinical workflow.

MR spectroscopic imaging has the advantage of producing a grid of spectra providing information about how the chemical content varies in space. This grid can be used to produce metabolite maps that show the spatial variation of metabolites throughout the breast. Having the spatial information also allows the reviewer to select the region of interest retrospectively, thus reducing the need for real-time expertise during the MR scan and improving the workflow for MR spectroscopy acquisition. The additional spatial information opens the door to a variety of analysis approaches: it is possible to characterize a lesion using the worst-case spectrum, taking an average over the lesion with or without retrospective grid shifting, measuring the heterogeneity over the lesion, or comparing the lesion with adjacent normal glandular tissue. Finally, although MR spectroscopic imaging requires more time than SVS to acquire a water-reference scan for quality control or quantification purposes, recent work using fast encoding and optimized acquisition protocols have shown that it is possible to acquire reference spectra in acceptable measurement times.

Breast MR spectroscopy protocols typically use water suppression to reduce the size of the water peak in the spectrum, which can introduce baseline distortions if left unsuppressed. Lipid suppression is also sometimes used for the same purpose. It can be advantageous, however, to leave some residual water and/or lipid resonances for use in performing frequency correction, phase correction, and referencing. If lipids are left unsuppressed, echo-time averaging can be used to reduce sideband artifacts. The size of the sideband artifacts can vary substantially between MR scanners, and most clinical systems have smaller sidebands than were reported originally at 4 T.

Both SVS and MR spectroscopic imaging techniques produce better quality spectra if the B ₀ field is uniform across the region of interest. A uniform B ₀ field leads to narrow spectral line widths, which increases SNR, provides better separation of different chemical resonances, and improves fitting of spectral peaks. In MR spectroscopic imaging, an inhomogeneous B ₀ field also increases signal leakage between voxels and subsequently causes baseline distortions. The scanner’s B ₀ field is typically very uniform when empty, but introducing a body into the scanner produces distortions of the B ₀ field caused by differences in magnetic susceptibility of the various tissues.

The distortions are largest at the interface between different materials, such as between adipose and glandular tissues or between skin and air. These distortions can be partially corrected by “shimming” the B ₀ field, which consists of measuring the B ₀ field variations and adjusting electrical currents in the compensating shim coils. The shimming capabilities vary between different scanner models, but most systems can reasonably correct macroscopic B ₀ distortions using automated shimming techniques. In the breast, there are also microscopic B ₀ distortions generated at each interface between water and fat. These distortions are not correctable with shim coils, and lead to spectra with larger line widths than are found in brain or prostate spectra. The best spectral resolution is obtained in highly uniform regions, such as cysts and focal masses with no adipose tissue. With practical voxel sizes, most voxels include a mixture of lesion, gland, and adipose tissues, and regions with more adipose content will produce spectra with larger line widths. Spectral resolution is an important quality metric for breast MR spectroscopy, with typically reported full-width at half-maximum (FWHM) of approximately 0.25 ppm (16 Hz at 1.5 T, 32 Hz at 3 T) for the unsuppressed water resonance. If the spectral resolution is poor after automated shimming, manual adjustment of shim currents can often give better results but requires expertise and a minute or two of time.

Analysis

Software packages provided by MR system vendors can be used for processing breast spectra, but spectroscopy software such as jMRUI or custom-built code are also commonly used. Preprocessing of breast spectroscopy data should be minimal and consistent. Light filtering is common, but using excessive filtering can smooth out spectral noise and create artificial resonances that can be misinterpreted. Frequency referencing and phasing are often necessary to compensate for scanner miscalibration or motion during the scan. Frequency referencing should be done relative to the unsuppressed water peak, as the water-lipid frequency difference can vary with B ₀ shim quality. A subjective quality assessment should be performed by a reviewer with experience in spectroscopy to confirm successful preprocessing and identify spectral artifacts. Objective quality metrics should also be calculated, most importantly the unsuppressed water FWHM to assess shim quality and the unsuppressed water SNR to assess sensitivity.

Detection is a critical part of all spectral analyses, and in many studies the detection of a tCho peak itself has been used as the primary outcome of the measurement. Detection can be assessed subjectively by one or more reviewers with experience in spectroscopy. More objectively, detection can be defined as a tCho peak above a predetermined SNR threshold, most commonly SNR ≥ 2 or greater. Note that even SNR-based detection can be somewhat subjective if performed manually, as the baseline correction (if used) can influence the result. Furthermore, the SNR measurement will vary with different acquisition parameters and filtering, and several different definitions of SNR are still commonly used.

Many experimental factors can affect the measurement sensitivity and, thus, the SNR of the tCho peak, including field strength, receive coil sensitivity profile, system electronics, and numerous sequence parameters such as voxel size, averaging, flip angle, and readout bandwidth. Quantitative analysis methods seek to compensate for all of the experimental factors and produce a measurement of the metabolite concentration in absolute units. Using a quantitative metric enables comparison of results across different systems, field strengths, and vendors, and potentially with ex vivo assays.

Diagnosis

The most established use of breast MR spectroscopy is to distinguish between benign and malignant lesions in the diagnostic setting using the elevated tCho level as an indicator of malignancy. MR imaging is now established as the most accurate imaging modality for diagnosing breast cancer, but although it has high sensitivity (92%), its specificity is lower (78%) and more variable. MR spectroscopy has the potential for improving the accuracy of an MR scan by offering better specificity. A substantial body of work has investigated the diagnostic performance of MR spectroscopy in the breast. A recent meta-analysis by Baltzer and Dietzel compiled the results from 19 studies and found that MR spectroscopy alone had combined sensitivity of 73% and specificity of 88%. Specificity of MR spectroscopy was also relatively consistent across studies, whereas the sensitivity was variable: a seemingly ideal complement to the diagnostic performance of MR imaging. This level of performance is remarkable considering the large variation in methods used across these studies, including both SVS and MR spectroscopic imaging acquisitions, and analyses ranging from detection to absolute quantification.

The first report measuring tCho in the human breast was by Roebuck and colleagues in 1998. In this work 17 subjects were studied with single-voxel MR spectroscopy, and tCho levels were quantified using an external referencing method. Although the tCho concentrations themselves were not different between the benign and malignant groups, it was noted that a tCho resonance was more likely to be detected in malignant lesions. The investigators therefore proposed using the detectability of a tCho peak as a marker of malignancy, and showed good diagnostic performance (sensitivity 70%, specificity 86%). Several subsequent articles adopted the detectability approach and reported similar results. Katz-Brull and colleagues performed a meta-analysis of 5 studies, all using comparable acquisition methods and qualitative tCho detection as a marker of malignancy, and found a combined sensitivity/specificity of 83%/85%. Tse and colleagues later imposed the criterion of SNR of 2 or greater to make the tCho detection more objective, an improvement that has been widely adopted and has produced comparable diagnostic performance.

Of note, all of the aforementioned studies using detection as a criterion of malignancy used a variable voxel size to best match the lesion geometry. If the voxel size is adjusted to match the lesion size, the larger lesions are measured with greater sensitivity than are smaller lesions, and lower concentrations of tCho can be detected. Some studies have reported that in the diagnostic setting, malignant lesions are larger than benign lesions, although some studies have reported no difference in size. Therefore lesion size is a potential confounder in that a larger mass is more likely to exhibit detectable tCho than is a smaller mass with the same tCho concentration. To control for this effect, Tozaki and Fukuma performed an MR spectroscopy study using detection as the criterion for malignancy, but using a fixed voxel size (3.375 mL). This approach resulted in specificity (85%) that was comparable to the variable-voxel studies, but with a notably lower sensitivity (44%). These results suggest that using variable voxel size can potentially improve the diagnostic performance of the MR spectroscopy measurement, but it should be recognized that this may reflect lesion size as well as metabolism.

Using tCho detectability as an indicator of malignancy has been very successful to date. However, with the greater sensitivity provided by newer breast coil designs and higher-field MR scanners, it is now well established that tCho can be detected in normal fibroglandular tissues and many different types of benign lesion. Under these circumstances, diagnosis can be performed using quantitative and semiquantitative measurements, combined with a ROC-curve analysis selecting an optimal threshold for distinguishing between benign and malignant lesions.

The most widely used fully quantitative approach is the internal reference technique. The initial studies performed with this technique on a 4 T system found that malignant lesions had a higher average [tCho] (2.2 mmol/kg) than benign lesions (0.2 mmol/kg), and using a cutoff of 1.0 mmol/kg produced sensitivity of 61% and specificity of 83%. Subsequent studies have been performed using water internal referencing on 1.5 T clinical MR scanners. Thakur and colleagues reported sensitivity/specificity of 96%/93%, Baek and colleagues reported sensitivity/specificity of 66%/92%, and Sah and colleagues reported sensitivity/specificity of 76%/75%. Across these studies, the mean [tCho] in malignant lesions ranged from 2.7 to 5.3 mmol/kg, whereas in benign lesions the mean [tCho] ranged from 0.1 to 1.6 mmol/kg. Dorrius and colleagues also used water as an internal reference, but assumed a fixed tissue water concentration (82%) to report volumetric concentrations, with proportionally smaller numerical values. With this metric, they found the highest [tCho] in malignant lesions averaged 4.1 mM while benign lesions averaged 1.2 mM, and these could be distinguished with 100% accuracy using a cutoff of a 1.5 mM. Diagnostic results with external referencing have only been reported by 2 groups, but have found concentrations comparable with internal referencing results. Roebuck and colleagues found malignancies with tCho concentrations from 0.4 to 2.0 mM but, because of a single high-concentration benign lesion (tubular adenoma 5.8 mM), did not find the quantitative results diagnostic. Mizukoshi and colleagues more recently used external referencing methods for a large diagnostic study of 208 cases and found sensitivity/specificity of 68%/70%, with malignant lesions averaging 1.1 mmol/kg and benign lesions averaging 0.4 mmol/kg. Across these quantitative studies the concentrations are reasonably consistent, but there are variations in concentration levels, optimal cutoff, and diagnostic performance.

The most common semiquantitative approach is to use the tCho SNR as an indirect indicator of the tCho concentration. Lipnick and colleagues used a single-voxel 2D localized correlated spectroscopy (L-COSY) technique to measure both tCho and fat peaks, and found that with a threshold of 2 the tCho SNR gave nearly 100% accuracy with a 1-mL voxel size. Jacobs and colleagues and Baek and colleagues both used 2D MR spectroscopic imaging at 1.5 T with 1-mL nominal voxel sizes, and found similar SNR thresholds (4 and 3.6) and similar sensitivity/specificities of 85%/85% and 81/78%, respectively. Gruber and colleagues used 3D MR spectroscopic imaging at 3 T and found that an SNR threshold of 2.6 led to sensitivity/specificity of 97%/84%. Rather than tCho SNR, Sardanelli and colleagues used the peak integral from their spectral processing software as a semiquantitative metric, used SVS with a variable voxel size, and explored the impact of normalizing the integral by the voxel size. Unexpectedly they found that the raw tCho integral, which reflects both tCho concentration and lesion size, gave better diagnostic performance (sensitivity/specificity 90%/92%) than normalized integral (sensitivity/specificity 84%/89%).

All three analysis approaches, namely detection, absolute quantification, and semiquantitative metrics, have been used successfully for diagnosing breast lesions. In the meta-analysis by Baltzer and Dietzel, no statistically significant difference in performance was found between the different analysis approaches, although there appears to be a trend that the fully quantitative methods have somewhat lower performance than the total pooled result. This seems to be a paradox, as the quantitative methods should in theory provide a more direct measure of the lesion metabolism, and therefore provide better specificity for distinguishing benign from malignant lesions. One likely contributing factor is that the corrections used in quantitative methods add noise to the measurements, thus decreasing the overall performance. This drawback potentially adds to the complexity of quantitative methods, and future work is required to measure and minimize the impact of these corrections. Another explanation is that lesion size and homogeneity affects the tCho SNR and improves its performance via mechanisms that are corrected with quantitative methods. In addition to the previously mentioned size bias in studies with variable voxel sizes, a large, homogeneous lesion can also produce a higher tCho SNR than a smaller lesion with the same concentration, even when measured with methods using a fixed voxel size, owing to better B ₀ shim quality, reduced partial volume, and (with MR spectroscopic imaging) point-spread function effects. These factors are at least partially corrected with the quantitative methods.

Treatment Response

MR spectroscopic measurements of tCho have also been used to monitor response to neoadjuvant chemotherapy (NCT) in breast cancer. While MR imaging is commonly used for assessing residual disease, there remains a need for imaging biomarkers that can identify response early in the course of therapy so that treatment can be modified for the best possible outcome. Contrast-enhanced MR imaging has also shown promise as an early response indicator, particularly when using volumetric measurements that can distinguish responders from nonresponders before the second cycle of therapy. The tCho concentration within a tumor has also been proposed as an early response indicator, based on the idea that therapy-induced changes in cell proliferation should logically precede anatomic changes.

The first observation regarding tCho and therapy response was by Kvistad and colleagues, who observed in a single subject that a tumor that had a detectable tCho peak before treatment exhibited no tCho after treatment. A subsequent work by Jagannathan and colleagues observed that a tCho peak either decreased or disappeared in 10 subjects receiving chemotherapy, indicating that tCho levels were sensitive to treatment. Since these early studies there have been a dozen published reports of studies using tCho for monitoring therapy response in breast cancer, reviewed recently by Sharma and colleagues. These studies, however, are highly variable in methodology used for measuring tCho, timing of the monitoring scans, and the response outcome.

Pathologic response is a widely used outcome for assessing the efficacy of NCT. The majority of the studies comparing MR spectroscopy with pathologic outcome support the finding that early decreases in tCho are associated with pathologic response. Baek and colleagues found that decreases in the tCho concentration were larger in pathologic complete responders, but only at their second follow-up time point (69 days); at their earliest follow-up scan (20 days) there was no difference between responders and nonresponders. Tozaki and colleagues reported that using quantitative external referencing, pathologic responders showed a larger drop in [tCho] than nonresponders after 2 cycles of chemotherapy. A subsequent report from the same group found in a small study (7 patients) that a decrease in the semiquantitative tCho integral after the first cycle of chemotherapy was associated with pathologic response. As part of a multiparametric imaging study that included MR spectroscopic imaging, Jacobs and colleagues showed a significant decrease in tCho SNR for pathologic complete responders after one cycle of chemotherapy, and no significant difference for nonresponders. By contrast, Bathen and colleagues observed that both pathologic responders and nonresponders showed decreased tCho SNR after once cycle of chemotherapy, with no significant difference between the groups.

Other studies have compared MR spectroscopy measurements with clinical outcomes based on imaging size measurements or palpation. Meisamy and colleagues used quantitative internal referencing, and found that a decrease in [tCho] measured 1 day after the initial treatment was associated with a size response at the end of chemotherapy, based on modified Response Evaluation Criteria in Solid Tumors (RECIST). Their initial study demonstrated 100% accuracy in 13 subjects, whereas a follow-up report including 28 cases showed 82% accuracy in distinguishing responders from nonresponders. Baek and colleagues also compared quantitative internal referencing with RECIST-based size changes, and found that a tCho decrease after one cycle was associated with response. Using an MR spectroscopic imaging protocol, Danishad and colleagues found that decreases in tCho SNR after one cycle of therapy were associated with response based on bidimensional palpation.

Looking across all these studies, it appears that early tCho decreases are likely to indicate successful therapy. Three of these studies also tried to determine whether MR spectroscopy could identify responders earlier than MR imaging size measurements. These findings were inconclusive: in each study MR imaging was also able to distinguish response as early as MR spectroscopy. Several studies also assessed whether pretreatment tCho levels were associated with response. Only one study found that responders had a higher pretreatment tCho than nonresponders, with the other 5 studies finding no difference between the groups.

Most of these studies applied MR imaging and MR spectroscopy after the first or second cycle of therapy, which can be very practical, as the scanning can be done when the patient returns to the clinic to begin the next treatment cycle. An exception is the study design of Meisamy and colleagues, in which patients were scanned 1 day after receiving the first course of treatment. No subsequent studies using this early time point have yet been reported, although the ACRIN 6657 extension study, which assessed response with MR spectroscopy 1 to 4 days after starting therapy, has completed accrual, and results are expected soon. One advantage of this very early time point is that it minimizes the potentially confounding effect of anatomic response, as shown in the example of Fig. 1 . In this patient with invasive ductal carcinoma, [tCho] decreased 1 day after beginning neoadjuvant chemotherapy while breast MR imaging demonstrated no anatomic changes. As in the diagnostic setting, the various methods for measuring tCho can be affected by lesion size and heterogeneity, and it may be challenging to separate the effects of metabolic and anatomic changes. The analysis methodology, combined with the voxel sizing strategy, can affect these relative contributions. In some studies the voxel size was modified to match the changing lesion size over the course of therapy. In this case, the semiquantitative methods may reflect both metabolic and anatomic changes, which introduces bias but may lead to better performance.

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related posts:

Breast Magnetic Resonance Imaging Technique at 1.5 T and 3 T Updates and Revisions to the BI-RADS Magnetic Resonance Imaging Lexicon Screening MR Imaging Versus Screening Ultrasound BI-RADS 3 for Magnetic Resonance Imaging Evaluation of Breast Silicone Implants Magnetic Resonance Imaging–Guided Biopsy of the Breast

Stay updated, free articles. Join our Telegram channel

Join