Diagnostic performance of time-of-flight PET/CT for evaluating nodal metastasis of the axilla in breast cancer

Increased lesion detectability in patients with locally advanced breast cancer-A pilot study using dynamic whole-body [18F]FDG PET/CT

BACKGROUND

Accurate diagnosis of axillary lymph node (ALN) metastases is essential for prognosis and treatment planning in breast cancer. Evaluation of ALN is done by ultrasound, which is limited by inter-operator variability, and by sentinel lymph node biopsy and/or ALN dissection, none of which are without risks and/or long-term complications. It is known that conventional 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) has limited sensitivity for ALN metastases. However, a recently developed dynamic whole-body (D-WB) [18F]FDG PET/CT scanning protocol, allowing for imaging of tissue [18F]FDG metabolic rate (MRFDG), has been shown to have the potential to increase lesion detectability. The study purpose was to examine detectability of malignant lesions in D-WB [18F]FDG PET/CT compared to conventional [18F]FDG PET/CT.

RESULTS

This study prospectively included ten women with locally advanced breast cancer who were referred for an [18F]FDG PET/CT as part of their diagnostic work-up. They all underwent D-WB [18F]FDG PET/CT, consisting of a 6 min single bed dynamic scan over the chest region started at the time of tracer injection, a 64 min dynamic WB PET scan consisting of 16 continuous bed motion passes, and finally a contrast-enhanced CT scan, with generation of MRFDG parametric images. Lesion visibility was assessed by tumor-to-background and contrast-to-noise ratios using volumes of interest isocontouring tumors with a set limit of 50% of SUVmax and background volumes placed in the vicinity of tumors. Lesion visibility was best in the MRFDG images, with target-to-background values 2.28 (95% CI: 2.04-2.54) times higher than target-to-background values in SUV images, and contrast-to-noise values 1.23 (95% CI: 1.12-1.35) times higher than contrast-to-noise values in SUV images. Furthermore, five imaging experts visually assessed the images and three additional suspicious lesions were found in the MRFDG images compared to SUV images; one suspicious ALN, one suspicious parasternal lymph node, and one suspicious lesion located in the pelvic bone.

CONCLUSIONS

D-WB [18F]FDG PET/CT with MRFDG images show potential for improved lesion detectability compared to conventional SUV images in locally advanced breast cancer. Further validation in larger cohorts is needed.

CLINICAL TRIAL REGISTRATION

The trial is registered in clinicaltrials.gov, NCT05110443, https://www.

CLINICALTRIALS

gov/study/NCT05110443?term=NCT05110443&rank=1 .

Deep Learning-Based Image Quality Improvement in Digital Positron Emission Tomography for Breast Cancer

We investigated whether ¹⁸F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography images restored via deep learning (DL) improved image quality and affected axillary lymph node (ALN) metastasis diagnosis in patients with breast cancer. Using a five-point scale, two readers compared the image quality of DL-PET and conventional PET (cPET) in 53 consecutive patients from September 2020 to October 2021. Visually analyzed ipsilateral ALNs were rated on a three-point scale. The standard uptake values SUV_max and SUV_peak were calculated for breast cancer regions of interest. For "depiction of primary lesion", reader 2 scored DL-PET significantly higher than cPET. For "noise", "clarity of mammary gland", and "overall image quality", both readers scored DL-PET significantly higher than cPET. The SUV_max and SUV_peak for primary lesions and normal breasts were significantly higher in DL-PET than in cPET (p < 0.001). Considering the ALN metastasis scores 1 and 2 as negative and 3 as positive, the McNemar test revealed no significant difference between cPET and DL-PET scores for either reader (p = 0.250, 0.625). DL-PET improved visual image quality for breast cancer compared with cPET. SUV_max and SUV_peak were significantly higher in DL-PET than in cPET. DL-PET and cPET exhibited comparable diagnostic abilities for ALN metastasis.

Proposal to Improve the Image Quality of Short-Acquisition Time-Dedicated Breast Positron Emission Tomography Using the Pix2pix Generative Adversarial Network

This study aimed to evaluate the ability of the pix2pix generative adversarial network (GAN) to improve the image quality of low-count dedicated breast positron emission tomography (dbPET). Pairs of full- and low-count dbPET images were collected from 49 breasts. An image synthesis model was constructed using pix2pix GAN for each acquisition time with training (3776 pairs from 16 breasts) and validation data (1652 pairs from 7 breasts). Test data included dbPET images synthesized by our model from 26 breasts with short acquisition times. Two breast radiologists visually compared the overall image quality of the original and synthesized images derived from the short-acquisition time data (scores of 1−5). Further quantitative evaluation was performed using a peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the visual evaluation, both readers revealed an average score of >3 for all images. The quantitative evaluation revealed significantly higher SSIM (p < 0.01) and PSNR (p < 0.01) for 26 s synthetic images and higher PSNR for 52 s images (p < 0.01) than for the original images. Our model improved the quality of low-count time dbPET synthetic images, with a more significant effect on images with lower counts.

Relationship between Baseline [18F]FDG PET/CT Semiquantitative Parameters and BRCA Mutational Status and Their Prognostic Role in Patients with Invasive Ductal Breast Carcinoma

AIM

To assess the relationship between [¹⁸F]FDG PET/CT, breast cancer gene (BRCA) status, and their prognostic role in patients with ductal breast cancer (DBC).

METHODS

Forty-one women were included. PET/CT semiquantitative parameters such as standardized uptake value (SUV) body weight max (SUVmax), SUV body weight mean (SUVmean), SUV lean body mass (SUVlbm), SUV body surface area (SUVbsa), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ratio SUVmax/blood-pool (S-BP), and ratio SUVmax/liver (S-L) were also extracted. The relationship between these parameters, BRCA, and other clinicopathological features were evaluated. Kaplan-Meier, univariate, and multivariate analyses were performed to find independent prognosticators for progression free (PFS) and overall survival (OS).

RESULTS

Significant positive correlations between BRCA status and SUVmax (p-value 0.025), SUVlbm (p-value 0.016), and SUVbsa (p-value 0.018) were reported. Mean PFS was 53.90 months with relapse/progression of disease occurring in nine (22.0%) patients; mean OS was 57.48 months with death occurring in two (4.9%) patients. Survival curves revealed TLG, MTV, and BRCA status as prognosticator for PFS; BRCA was also a prognosticator for OS. Univariate and multivariate analyses did not confirm such insights.

CONCLUSION

We reported a correlation between some PET/CT parameters and BRCA status; some insights on their prognostic role have been underlined.

Comparison of 18F-fluorothymidine Positron Emission Tomography/Computed Tomography and 18F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Patients with Breast Cancer

The uptake of ¹⁸F-fluorothymidine (¹⁸F-FLT) depends on cells' proliferative rates. We compared the characteristics of ¹⁸F-FLT positron emission tomography/computed tomography (PET/CT) with those of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT for breast cancer. We prospectively diagnosed patients with breast cancer who underwent ¹⁸F-FLT PET/CT and ¹⁸F-FDG PET/CT. Subsequently, significant differences and correlation coefficients of the maximum standardized uptake value (SUVmax) in primary breast cancer and axillary lymph nodes were statistically evaluated. We enrolled eight patients with breast cancer. In six treatment-naive patients, the SUVmax for primary lesions showed a significant difference (mean, 2.1 vs. 4.1, p = 0.031) and a strong correlation (r = 0.969) between ¹⁸F-FLT and ¹⁸F-FDG. Further, although the SUVmax for the axillary lymph nodes did not show a significant difference between ¹⁸F-FLT and ¹⁸F-FDG (P = 0.246), there was a strong correlation between the two (r = 0.999). In a patient-by-patient study, there were cases in which only ¹⁸F-FDG uptake was observed in lymph nodes and normal breasts. Bone metastases demonstrated lower accumulation than bone marrow on the ¹⁸F-FLT PET/CT. In conclusion, a strong correlation was observed between the ¹⁸F-FLT PET/CT and ¹⁸F-FDG PET/CT uptake. Differences in the biochemical characteristics of ¹⁸F-FLT and ¹⁸F-FDG were reflected in the accumulation differences for breast cancer, metastatic lesions, and normal organs.

Focal Uptake in the Sternum on 18F-FDG-PET/CT Caused by G-CSF Therapy after Chemotherapy Mimicking Bone Metastasis of Breast Cancer

A woman in her 70s was diagnosed with left breast cancer and left axillary lymph node metastasis by an ultrasound-guided biopsy. ¹⁸F-FDG-PET/CT showed strong FDG accumulation in the tumor in the left breast and a left axillary lymph node. Neoadjuvant chemotherapy (NAC) was administered in combination with a G-CSF injection to prevent febrile neutropenia. The post-treatment ¹⁸F-FDG-PET/CT showed the disappearance of the left breast tumor and left axillary lymph node and revealed a solitary new area of strong FDG accumulation in the sternum. To rule out the possibility of sternal metastasis, a sternal biopsy was performed at the same time as surgery, which revealed no malignant findings. Although very rare, focal uptake on ¹⁸F-FDG-PET/CT performed after anticancer drug therapy with G-CSF may mimic a solitary bone metastasis. A bone biopsy may be a useful technique to avoid an immediate misdiagnosis of bone metastasis.

Deep learning for image classification in dedicated breast positron emission tomography (dbPET)

OBJECTIVE

This study aimed to investigate and determine the best deep learning (DL) model to predict breast cancer (BC) with dedicated breast positron emission tomography (dbPET) images.

METHODS

Of the 1598 women who underwent dbPET examination between April 2015 and August 2020, a total of 618 breasts on 309 examinations for 284 women who were diagnosed with BC or non-BC were analyzed in this retrospective study. The Xception-based DL model was trained to predict BC or non-BC using dbPET images from 458 breasts of 109 BCs and 349 non-BCs, which consisted of mediallateral and craniocaudal maximum intensity projection images, respectively. It was tested using dbPET images from 160 breasts of 43 BC and 117 non-BC. Two expert radiologists and two radiology residents also interpreted them. Sensitivity, specificity, and area under the receiver operating characteristic curves (AUCs) were calculated.

RESULTS

Our DL model had a sensitivity and specificity of 93% and 93%, respectively, while radiologists had a sensitivity and specificity of 77-89% and 79-100%, respectively. Diagnostic performance of our model (AUC = 0.937) tended to be superior to that of residents (AUC = 0.876 and 0.868, p = 0.073 and 0.073), although not significantly different. Moreover, no significant differences were found between the model and experts (AUC = 0.983 and 0.941, p = 0.095 and 0.907).

CONCLUSIONS

Our DL model could be applied to dbPET and achieve the same diagnostic ability as that of experts.

Deep Learning Using Multiple Degrees of Maximum-Intensity Projection for PET/CT Image Classification in Breast Cancer

Deep learning (DL) has become a remarkably powerful tool for image processing recently. However, the usefulness of DL in positron emission tomography (PET)/computed tomography (CT) for breast cancer (BC) has been insufficiently studied. This study investigated whether a DL model using images with multiple degrees of PET maximum-intensity projection (MIP) images contributes to increase diagnostic accuracy for PET/CT image classification in BC. We retrospectively gathered 400 images of 200 BC and 200 non-BC patients for training data. For each image, we obtained PET MIP images with four different degrees (0°, 30°, 60°, 90°) and made two DL models using Xception. One DL model diagnosed BC with only 0-degree MIP and the other used four different degrees. After training phases, our DL models analyzed test data including 50 BC and 50 non-BC patients. Five radiologists interpreted these test data. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. Our 4-degree model, 0-degree model, and radiologists had a sensitivity of 96%, 82%, and 80–98% and a specificity of 80%, 88%, and 76–92%, respectively. Our 4-degree model had equal or better diagnostic performance compared with that of the radiologists (AUC = 0.936 and 0.872–0.967, p = 0.036–0.405). A DL model similar to our 4-degree model may lead to help radiologists in their diagnostic work in the future.

Sentinel lymph node detection by combining nonradioactive techniques with contrast agents: State of the art and prospects

The status of sentinel lymph nodes (SLNs) has a substantial prognostic value because these nodes are the first place where cancer cells accumulate along their spreading route. Routine SLN biopsy ("gold standard") involves peritumoral injections of radiopharmaceuticals, such as technetium-99m, which has obvious disadvantages. This review examines the methods used as "gold standard" analogs to diagnose SLNs. Nonradioactive preoperative and intraoperative methods of SLN detection are analyzed. Promising photonic tools for SLNs detection are reviewed, including NIR-I/NIR-II fluorescence imaging, photoswitching dyes for SLN detection, in vivo photoacoustic detection, imaging and biopsy of SLNs. Also are discussed methods of SLN detection by magnetic resonance imaging, ultrasonic imaging systems including as combined with photoacoustic imaging, and methods based on the magnetometer-aided detection of superparamagnetic nanoparticles. The advantages and disadvantages of nonradioactive SLN-detection methods are shown. The review concludes with prospects for the use of conservative diagnostic methods in combination with photonic tools.

The new perspective of PET/CT for axillary nodal staging in early breast cancer patients according to ACOSOG Z0011 trial PET/CT axillary staging according to Z0011

OBJECTIVE

Post Z0011 trial, axillary lymph node dissections (ALNDs) can be performed in patients with ≥3 positive axillary lymph nodes (ALNs). We investigated the diagnostic performance of 18F-fluorodeoxyglucose PET/computed tomography (FDG PET/CT) to predict ≥3 metastasis [high nodal burden (HNB)].

METHODS

We retrospectively analyzed preoperative FDG PET/CT from January 2010 to June 2012. Patients had clinical T1-2N0 primary invasive breast cancer and underwent breast-conserving surgery with sentinel lymph node biopsy ± ALND. All suspicious ALNs were counted considering FDG-avidity with morphologic changes. Images were considered positive if the axillary basin took up more FDG than the surrounding tissue. On CT, abnormal ALNs were round/ovoid or had cortical thickening with contrast enhancement. PET/CT results were compared with the histology and follow-up findings.

RESULTS

In total, 221 females with 224 axillae were enrolled; 161 had negative, 53 had 1-2 metastasis [low nodal burden (LNB)] and 10 had HNB. The sensitivity, specificity, negative predictive value and positive predictive value of PET/CT for HNB were 70, 100, 98.6 and 100%, respectively. There was a correlation between the number of suspicious ALNs on PET/CT and the metastatic nodes on final histology. There were no significant differences in age, tumor size and FDG-avidity between patients with negative or LNB and HNB. During follow-up, 25 patients had a recurrence. The three false-negative patients did not show recurrence.

CONCLUSION

Preoperative PET/CT predicts HNB with high accuracy and is useful for evaluating clinical T1-2N0 invasive breast cancer.

Virtual Navigator Real-Time Ultrasound Fusion Imaging with Positron Emission Tomography/Computed Tomography for Preoperative Breast Cancer

We used virtual navigator real-time ultrasound (US) fusion imaging with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) to identify a lesion that could not be detected on the US alone in a preoperative breast cancer patient. Of the patient’s two lesions of breast cancer, the calcified lesion could not be identified by US alone. By fusing US with 18F-FDG PET/CT, which had been performed in advance, the location of the lesion could be estimated and marked, which benefited planning an appropriate surgery. The fusion of US and 18F-FDG PET/CT was a simple and noninvasive method for identifying the lesions detected by 18F-FDG PET/CT.

Relationship between Prognostic Stage in Breast Cancer and Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography

This retrospective study examined the relationship between the standardized uptake value max (SUVmax) of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and the prognostic stage of breast cancer. We examined 358 breast cancers in 334 patients who underwent ¹⁸F-FDG PET/CT for initial staging between January 2016 and December 2019. We extracted data including SUVmax of ¹⁸F-FDG PET and pathological biomarkers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and nuclear grade. Anatomical and prognostic stages were determined per the American Joint Committee on Cancer (eighth edition). We examined whether there were statistical differences in SUVmax between each prognostic stage. The mean SUVmax values for clinical prognostic stages were as follow: stage 0, 2.2 ± 1.4; stage IA, 2.6 ± 2.1; stage IB, 4.2 ± 3.5; stage IIA, 5.2 ± 2.8; stage IIB, 7.7 ± 6.7; and stage III + IV, 7.0 ± 4.5. The SUVmax values for pathological prognostic stages were as follows: stage 0, 2.2 ± 1.4; stage IA, 2.8 ± 2.2; stage IB, 5.4 ± 3.6; stage IIA, 6.3 ± 3.1; stage IIB, 9.2 ± 7.5, and stage III + IV, 6.2 ± 5.2. There were significant differences in mean SUVmax between clinical prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). There were also significant differences in mean SUVmax between pathological prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). In conclusion, mean SUVmax increased with all stages up to prognostic stage IIB, and there were significant differences between several stages. The SUVmax of ¹⁸F-FDG PET/CT may contribute to prognostic stage stratification, particularly in early cases of breast cancers.

Sensitivity, Specificity and the Diagnostic Accuracy of PET/CT for Axillary Staging in Patients With Stage I-III Cancer: A Systematic Review of The Literature

BACKGROUND/AIM

Axillary lymph node (ALN) status plays a key role in the staging of breast cancer. Positron Emission Tomography/Computed Tomography (PET/CT) using 18-Fluorodeoxyglucose (¹⁸FDG) can visualise ALN metastasis. However, its utility compared to current methods is unclear. We systematically reviewed the role of ¹⁸FDG PET/CT in breast cancer staging.

MATERIALS AND METHODS

PubMed, Ovid and Cochrane were searched systematically up until August 2020. Included papers had true positive (TP), false positive (FP), true negative (TN) and false negative (FN) rates, sensitivity, specificity, accuracy, positive (PPV) and negative predictive value (NPV).

RESULTS

Nine studies (n=1486) were included, showing: i) sensitivity=52.2%, ii) specificity=91.6%, iii) PPV=77.8%, iv) NPV=77.2, and v) accuracy=77.3%.

CONCLUSION

¹⁸FDG-PET/CT has a low sensitivity but high specificity for ALN disease. Therefore, ultrasound-guided biopsy could be considered in a positive CT/PET. Modest accuracy prohibits the use of ¹⁸FDG-PET/CT alone in axillary staging. Prospective research using standardised protocols and quantitative cut-off points is warranted.