Fapi Pet-ct in Detecting Minimal Residual Disease and Subclinical Metastatic Sites in Post-treatment Breast Cancer

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Kambanda, Bright A. Sangiwa, Christina V. Malichewe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7336464/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Breast cancer has become the most common type of cancer, surpassing lung cancer, and is the leading cause of cancer-related deaths among women worldwide. Ga-68 FAPI PET-CT has currently evolved in multiple aspects in breast cancer assisting in diagnosis, initial staging, re-staging, suspected recurrence, and evaluating therapeutic response. It has also shown a role in other malignancies like sarcoma, esophageal cancer, cholangiocarcinoma, and lung cancer. Methods A retrospective analysis of Ga-68 FAPI PET-CT scans of forty-five patients aged eighteen and older with confirmed breast cancer who have undergone various treatments (surgery, chemotherapy, radiotherapy) was performed. The role Ga-68 FAPI PET–CT imaging in the detection of minimal residual disease and subclinical metastatic sites in breast cancer patients after initial treatment was analyzed. Results A total of 45 patients with histologically confirmed breast cancer and post treatment underwent Ga-68 FAPI PET-CT and Conventional CT and /or MRI. Ga-68 FAPI PET-CT showed 100% sensitivity and 82.5% specificity in detecting minimal residual disease, significantly outperforming conventional imaging, which identified lesions in only 11.1% of patients compared to 26.7% with PET-CT. Notably, Ga-68 FAPI PET-CT was better at detecting liver metastases (15.6% vs. 6.7%) and axillary metastases (11.1% vs. 4.4%). All patients with residual primary disease detected by Ga-68 FAPI PET-CT experienced recurrence (100%). However, those without residual primary disease, only 9.1% experienced recurrence. Recurrence-free survival was significantly longer in patients without residual disease (58.6 vs. 12.4 months, P < 0.001). Conclusion Ga-68 FAPI PET-CT has shown to be a probably sensitive and specific imaging modality that can effectively detect minimal residual disease and subclinical metastases in breast cancer patients. This study may potentially help in earlier detection of breast cancer recurrences hence timely interventions and improved patient outcomes. Oncology PET FAPI Breast Cancer residual disease subclinical metastases Figures Figure 1 Figure 2 BACKGROUND Breast cancer is the most prevalent cancer diagnosed in women globally, and its incidence has been increasing over recent decades [ 1 , 2 ]. In 2020, breast cancer accounted for the highest number of cancer diagnoses among women, with an estimated 2.3 million new cases reported worldwide and approximately 685,000 fatalities attributed to the disease [ 2 ]. Projections suggest that by 2050, the global incidence of female breast cancer could escalate to around 3.2 million new cases annually [ 2 ]. It is the most commonly diagnosed cancer and the second leading cause of cancer-related deaths in sub-Saharan Africa [ 3 ]. This region has the highest age-standardized incidence rate, which is 17.3 cases per 100,000 women per year. Country-specific prevalence rates indicate that breast cancer affects 15.3% of women in the Central African Republic, 4.6% in Rwanda, and 3.3% in Sierra Leone [ 3 , 4 ]. The tumor microenvironment (TME) has recently been recognized as a significant therapeutic target in the fields of cancer imaging and treatment [ 4 ]. It is composed of the extracellular matrix, various stromal cells—including fibroblasts, mesenchymal stromal cells, as well as the networks of blood and lymphatic vessels [ 5 , 6 ]. Additionally, the TME encompasses a diverse array of immune cells, including T and B lymphocytes, natural killer cells, and tumor-associated macrophages [ 6 ]. Fibroblast activation protein (FAP) is predominantly expressed in cancer-associated fibroblasts (CAFs) in over 90% of epithelial carcinomas [ 7 ]. The use of FAP-targeted molecular imaging has emerged as a promising strategy for the detection of tumor stroma [ 7 ]. This approach facilitates a better understanding of the tumor microenvironment and may enhance the diagnosis and treatment of cancer [ 8 ]. In 2018, a group of studies from the University of Heidelberg reported the use of DOTA-based fibroblast activation protein inhibitors (FAPI) in combination with Gallium-68 to perform PET imaging of a variety of tumors, including breast, colorectal, lung, and pancreatic cancers [ 7 , 9 , 10 ]. FAPI PET imaging serves multiple purposes, including initial staging, re-staging, evaluation of therapeutic response, and comprehensive assessment of target expression throughout the body to inform therapy selection [ 11 ]. In the context of FAPI imaging, tumors can be classified into three distinct categories, two caterogies that express high tumor FAPI uptake include desmoplastic tumors characterized by a high concentration of cancer-associated fibroblasts (CAFs) [ 11 ] and tumors that express FAP on both the tumor stroma and the tumor cells [ 12 ]. The third category are tumors with minimal desmoplastic reaction which do not exhibit significant desmoplastic features therefore mininal FAPI uptake is seen in these tumours. Breast cancer is in the category of desmoplastic tumors characterized by a high concentration of cancer-associated fibroblast [ 11 ]. Areas of increased radiotracer uptake are identified and region of interest drawn to automatically quantify the maximum standard uptake (SUVmax) and make a diagnosis of residual tumor and/ or metastasis [ 8 ]. Lesions are deemed malignant when non-physiologic foci of increased radiotracer uptake appear on PET images.The high diagnostic performance of Ga-68 FAPI PET-CT in detecting minimal residual tumors is attributed to the higher tracer uptake in breast cancer and a favorable low tumor-to-background ratio [ 9 ]. This combination allows for optimal tumor delineation. In patients with apparently confined breast cancer who are candidates for loco-regional therapy, additional Ga-68 FAPI PET-CT can identify unexpected metastases, thereby upstaging patients from M0 to M + and altering their treatment planning [ 9 ]. In breast cancer, there is an increased uptake of fibroblast activation protein (FAP) ligand that occurs independently of histological phenotype—whether lobular or ductal [ 13 ]. The background uptake of radiolabeled FAPI in the brain, liver, and oral mucosa is considerably lower than that of F-18 FDG, which makes it a more precise tool for staging breast cancer [ 14 ]. METHODS Study design This was a retrospective cross-sectional study of all histologically confirmed breast cancer patients who underwent Ga-68 FAPI PET-CT after initial treatment at Nuclear medicine and PET-CT centre at Ocean road Cancer Institute for evaluation of minimal residual disease and subclinical metastases, between July 2024 to December 2024. Ga-68 FAPI PET PET images were acquired 10 to 30 min after the administration of 5.5 to 8.46 mCi of Ga-68 FAPI. A 3D PET/CT scan was performed from vertex to mid-thigh on a SIEMENS BIOGRAPH MCT-64 slice PET/CT scanner. Multiplanar reformations were then performed on a dedicated station. Notably, patients were not required to fast prior to the examination, unlike with FDG-PET/CT. The PET images were evaluated by a nuclear medicine physician and the principal investigator. Quantitative assessment of tracer uptake in active areas was performed by measuring the maximum standardized uptake value (SUVmax) within regions of interest. Study population This study was conducted in forty-five patients with breast tumour and post initial treatment, who had Ga-68 FAPI PET-CT scan between July 2024 and December 2024. Female of 18 years and above who had histologically confirmed breast cancer, completed initial treatment, with documented conventional imaging results and had undergone Ga-68 FAPI PET CT studies were included. The study excluded male patients with breast cancer and those who were not eligible for Ga-68 FAPI PET-CT. Data Collection A standardized case report form with four sections was designed to include patient characteristics, sensitivity and specificity of Ga-68 FAPI PET-CT in detecting minimal residual disease in breast cancer patients after initial treatment, subclinical metastatic sites of breast cancer compared to conventional imaging methods (MRI and / or CT) and association between Ga-68 FAPI PET-CT findings and clinical outcomes, specifically recurrence-free survival (RFS) in patients treated for breast cancer. Data Analysis The Statistical Package for Social Sciences (SPSS) version 24 was used to store and analyze the collected data. Before analysis, the data was cleaned, coded, and entered into SPSS. Means and standard deviations were used to summarize continuous data while categorical data were summarized using frequencies and percentages. Ethical Consideration The study had approval of MUHAS Research and Ethics Committee (Ref. No. DA.282/298/01.C/2844). A waiver of informed consent was granted as a retrospective study that impose no risk to the subjects. RESULTS Patient characteristics The majority of patients, 21/45 (46.7%), were aged between 50 and 70 years. The overall age, ranged from 34 to 86 years, with a mean age of 58.8 ± 13.7 years. Most participants, 32/45 (71.1%), were postmenopausal. The most common immunohistochemistry biomarker found in breast cancer among the study participants was estrogen receptor positive (ER+) observed in 62.2% of participants, followed by progesterone receptor positive (PR+) in 22/45 (48.9%), HER-2 Positive in 13/45 (28.9%), and 12/45 (26.6%) had no biomarkers. Regarding immunohistochemistry subtypes, the majority had Luminal A (17/45, 37.8%), followed by Basal-Like/Triple Negative (12/45, 26.7%), Luminal B (11/45, 24.4%), and 5/45 (11.1%) had HER-2 Enriched. In terms of histopathological subtypes, invasive ductal carcinoma (IDC) was observed in 40/45(88.9%), patients and other subtypes were found in 5/45 (11.1%) patients. Chemotherapy was the most commonly used treatment modality, reported in 43/45 (95.6%) patients, followed by surgery in 40/45 (88.9%) and radiotherapy in 24/45 (53.3%), Table 1 . Table 1 Patient Characteristics Variable Categories Frequency Percent (%) Age 30–50 19 42.2 50–70 21 46.7 > 70 5 11.1 Postmenopausal state Yes 32 71.1 No 13 28.9 Immunohistochemistry PR+ 22 48.9 ER+ 28 62.2 HER-2 + 13 28.9 None 12 26.6 Immunohistochemistry subtypes Luminal A 17 37.8 Lumina B 11 24.4 Her-2 Enriched 5 11.1 Basal-like/Triple Negative 12 26.7 Histological subtypes IDC 40 88.9 ILC 0 0 Others 5 11.1 Breast cancer treatment received Surgery 40 88.9 Chemotherapy 43 95.6 Radiotherapy 24 53.3 Ga-68 FAPI PET-CT in detecting minimal residual disease after initial treatment In this study, Ga-68 FAPI PET-CT has demonstrated a sensitivity of 100%, and a specificity of 82.5% in detecting minimal residual disease in breast cancer patients after initial treatment, using conventional imaging methods such as MRI and / or CT as the reference standard as described in Table 2 . Table 2 Sensitivity and Specificity of Ga-68 FAPI PET-CT Residual Disease detected on CT and/or MRI Residual Disease detected on Ga-68 FAPI PET CT Positive Negative Total Positive 5( 100%) 7( 17.5%) 12( 26.6%) Negative 0 ( 0.0%) 33( 82.5%) 33(73.3 %) Total 5(100 %) 40 (100 %) 45 (100%) The maximum standardized uptake values (SUVmax) of residual disease detected on Ga-68 FAPI PET/CT were obtained at the region of interest. Data were available for all 12 patients (no missing values). The mean SUVmax was 11.49, with a standard deviation of 5.36, indicating moderate variability across the patient cohort. The median SUVmax was 10.00, suggesting a slightly right-skewed distribution. The SUVmax values ranged from a minimum of 5.77 to a maximum of 25.35. Ga-68 FAPI PET-CT in detecting subclinical metastatic sites compared to conventional imaging Our study showed that, Ga-68 FAPI PET-CT had significantly greater sensitivity in detecting subclinical metastatic lesions compared to conventional imaging modalities, including MRI and /or CT. Subclinical metastases were identified in 12/45 (26.7%), whereas MRI and / or CT identified only in 5/45 (11.1%). This corresponds to an absolute difference of 15.6%, which was statistically significant (P = 0.016), emphasizing the superior diagnostic performance of Ga-68 FAPI PET-CT. The most pronounced differences were observed in the detection of liver and axillary metastases. Ga-68 FAPI PET-CT identified liver metastases in 7/45 (15.6%) compared to 3 /45 (6.7%) using conventional imaging, yielding a difference of 8.9%. Similarly, axillary metastatic involvement was detected in 5/45 (11.1%) by Ga-68 FAPI PET-CT versus 2/45 (4.4%) by MRI and / or CT, with a difference of 6.7%. Figure 1 shows FAPI uptake in different metastatic sites. In contrast, both imaging modalities demonstrated comparable detection rates in the chest and brain regions, with each modality identifying metastatic lesions in 2/45 (4.4%). Table 3 summarizes the metastatic sites findings. Table 3 Ga-68 FAPI PET-CT compared to MRI and/or CT in identifying Subclinical metastatic sites Metastatic sites Subclinical metastatic sites detected on Ga-68 FAPI PET CT (Number of patients, %) Subclinical Metastatic sites detected on MRI and / or CT (Number of patients, %) Difference Chest 2(4.4%) 2 (4.4%) 0 (0%) Bone 6(13.3%) 4(8.9%) 2(4.4%) Brain 2(4.4%) 2(4.4%) 0 (0%) Axillary nodes 5(11.1%) 2(4.4%) 3 (6.7%) Lymphatic system 3(6.7%) 1(2.2%) 2 (4.4%) Liver 7(15.6%) 3(6.7%) 4(8.9%) Others 1(2.2%) 0(0.0%) 1(2.2%) Overall 12(26.7%) 5(11.1%) 7(15.6%) McNemar's Test P = 0.016 Among 12 patients, the maximum standardized uptake values (SUVmax) of detected subclinical metastatic disease had a mean SUVmax of 11.26, a median of 10.3 and a range from 4.81 to 20.80. Association between Ga-68 FAPI PET CT finding in detecting residual disease and clinical outcomes. All the patients found with residual disease detected on Ga-68 FAPI PET-CT reported to have breast cancer recurrence 12/12 (100%) compared to those with no residual disease 3/33 (9.1%). This association was statistically significant with Fisher's Exact Test P < 0.001. Association between Ga-68 FAPI PET CT findings and recurrence-free survival (RFS). The overall mean recurrence-free survival (RFS) time for the cohort was 38.2 ± 6.2 months. A significantly longer mean RFS was observed in patients without residual disease on Ga-68 FAPI PET-CT, with an average of 58.6 ± 7.7 months, compared to 12.4 ± 3.9 months in patients with residual disease. The overall median RFS was 24.0 ± 1.8 months. Among patients with residual disease, the median RFS was markedly lower at 6.0 ± 1.7 months. In contrast, the median RFS for patients without residual disease could not be estimated due to an insufficient number of recurrence events in this subgroup. The difference in recurrence-free survival between patients with and without residual disease detected on Ga-68 FAPI PET/CT was highly statistically significant (P < 0.001, Log-Rank test) as shown in Fig. 2 . DISCUSSION Our study evaluated the diagnostic performance and prognostic value of Ga-68 FAPI PET-CT in detecting residual and subclinical metastatic disease in breast cancer patient’s post-treatment. The findings showed that Ga-68 FAPI PET-CT offers significant advantages over conventional imaging modalities such as MRI and/or CT, both in identifying occult disease and in predicting clinical outcomes. The demographic characteristics of the patient cohort reveal a predominantly postmenopausal population, with mean age of 58.8 ± 13.7 years. A study done in 2021 in Tanzania, found the median age was 50 years (range: 30–93 years) among women with proven breast cancer [ 15 , 16 ]. This aligns with existing literature that suggests a higher prevalence of breast cancer in older women [ 8 , 15 ]. The immunohistochemistry profiles indicate a significant occurrence of estrogen receptors (ER), with 62.2% of patients testing positive. This is important as ER-positive breast cancer is generally associated with better prognoses and responsiveness to endocrine therapies [ 17 ]. FAPI uptake is not correlated with histopathological and molecular features, and it is equally increased in all types of breast cancer [ 18 ]. The distribution of immunohistochemical subtypes shows a predominance of (ER-Positive/PR-positive and HER-2 negative (Luminal A) tumors, suggesting a favorable prognosis in terms of treatment and survival outcomes. However, the presence of Basal-Like/Triple Negative tumors (26.7%) in our cohort underscores the need for more aggressive treatment strategies, as these subtypes are often more challenging to treat. In ductal carcinoma in situ, research indicates that ER-negative/PR-negative but HER2-positive cancers have a higher risk of recurrence compared to ER-positive/PR-positive/HER2-negative cancers [ 19 ]. Among the 45 patients included in the study, Ga-68 FAPI PET-CT demonstrated a high sensitivity (100%) and specificity (82.5%) for detecting residual disease, using MRI/CT as the reference standard. Preliminary data reported by Eshet et al. indicate that FAPI PET is more effective than conventional CT in detecting lesions in seven women diagnosed with lobular breast cancer, demonstrating the ability to identify numerous lesions across various distant organs [ 20 ].These findings concur with a related finding which had compared roles of Ga-68 FAPI-PET-CT and F-18 FDG PET-CT where the sensitivity and specificity of FAPI in detecting residual breast lesions were 100% and 95.6% respectively [ 8 , 21 , 22 ]. FAPI has the capability to identify lesions within the first month following the completion of chemotherapy [ 23 ].This suggests that Ga-68 FAPI PET-CT is a highly reliable imaging modality for identifying minimal residual disease (MRD).FAP-targeted imaging modalities, especially positron emission tomography (PET), have demonstrated high sensitivity and specificity in detecting tumors that express fibroblast activation protein (FAP) and potentially enhance tumor detection, improve staging accuracy, and monitor treatment responses effectively [ 24 ]. Furthermore, Ga-68 FAPI PET-CT was notably superior in detecting subclinical metastases. It identified metastatic lesions in 26.7% of patients, compared to only 11.1% detected by MRI/CT. The statistically significant difference (P = 0.016) reinforces the enhanced sensitivity of Ga-68 FAPI PET-CT, especially in challenging anatomical regions. The most pronounced differences were observed in the liver and axillary nodes, where FAPI PET-CT detected nearly twice as many metastatic sites. In a clinical study involving patients with metastasized breast cancer, Ga-68 FAPI PET-CT exhibited high-contrast imaging capabilities, demonstrating significant tracer uptake in metastatic lesions while exhibiting minimal uptake in normal tissues [ 22 ]. These findings are consistent with existing literature suggesting that Ga-68 FAPI PET-CT is more effective in identifying small, metabolically active lesions due to its ability to target cancer-associated fibroblasts, which are abundant in the tumor microenvironment. Recent scientific advancements in breast cancer research have significantly improved the chances of disease-free survival for patients diagnosed at an early stage, when the cancer is still confined to the breast [ 17 ]. However, once breast cancer metastasizes to other organs, treatment options become very limited, and the success rate of managing these patients decreases substantially [ 17 ]. From a prognostic standpoint, our results indicate that the presence of residual disease on Ga-68 FAPI PET-CT is strongly associated with poorer outcomes. Breast cancers that are localized to the primary breast site and are treated in the early stages may still experience relapse [ 25 ]. This can occur due to the presence of cancer stem cells or the transformation of cancer cells into a more aggressive phenotype [ 17 , 25 ]. All patients with residual disease experienced disease recurrence (100%), whereas recurrence occurred in only 9.1% of those without residual disease but due to distant metastasis, a highly significant association (P < 0.001). A study conducted by Brewester et al on breast cancer recurrent post treatment found that a 5-year residual risks of recurrence for patients with stage I, II, and III breast cancer increased as staging increases [ 26 ]. Moreover, recurrence-free survival (RFS) was significantly shorter in patients with residual disease. Breast cancer recurrence is a critical indicator of tumor progression and is the primary cause of mortality associated with this disease [ 27 ]. The mean RFS for the patients in this study was 12.4 months, compared to 58.6 months for those without residual disease. The median RFS was similarly shorter (6.0 months vs. not estimable), and the difference was statistically significant (P < 0.001). Recurrent breast cancers are typically marked by high percentage of aggressive cells [ 17 ]. These findings underline the potential of Ga-68 FAPI PET-CT not only as a diagnostic tool but also as a prognostic biomarker that can aid in risk stratification and post-treatment surveillance. The analysis of standardized uptake values (SUVmax) further supports the biological relevance of the detected lesions. A study by Hadebe B. et al [ 22 ] demonstrated that Ga-68 FAPI PET-CT offers significant advantages in the detection of both primary and metastatic tumors, attributable to its high sensitivity and increased SUVmax [ 18 , 22 ]. The mean SUVmax of residual lesions in this study was 11.49, with a range from 5.77 to 25.35, indicating varying degrees of FAPI uptake. A systematic review conducted between 2017 and 2023 also observed that the maximum standardized uptake value (SUVmax) in primary tumors ranged from 2.6 to 17.0 [ 18 , 28 ]. Additionally, increased uptake values were consistently reported across all metastatic sites, including lymph nodes, lungs, liver, and bone [ 18 , 20 ]. This variability may reflect differences in tumor aggressiveness, fibroblast activation, or treatment response. CONCLUSION This study reinforces the role of Ga-68 FAPI PET-CT as a critical tool in the diagnosis and management of breast cancer. The high sensitivity and specificity of this imaging technique found in this study is comparable to what has been reported on Ga-68 FAPI PET-CT. This modality provides clinicians with a powerful resource to identify residual disease and subclinical metastases, ultimately improving patient outcomes. Future studies should explore the integration of Ga-68 FAPI PET-CT into standard practice guidelines for breast cancer management, particularly for patients at high risk of recurrence. Limitations This study is limited by its relatively small sample size that lowers the statistical power and generalizability The retrospective nature of the design is prone to selection bias and poor quality data as it relies on already available data. Lack of histopathological confirmation for all FAPI avid lesions may introduce a risk of overestimation of the burden of disease. Recommendations Larger, prospective studies are recommended to confirm the diagnostic accuracy and clinical utility of Ga-68 FAPI PET-CT in breast cancer particularly for the detection of residual and subclinical metastatic disease. Future studies should aim to incorporate histopathological validation of FAPI-avid lesions wherever feasible to better characterize false positives and improve specificity. Declarations Ethics approval and consent to participate Ethics approval and consent to participate, the study had approval of MUHAS Research and Ethics Committee (Ref. No. DA.282/298/01.C/2844). A waiver of informed consent was granted as a retrospective study that impose no risk to the subjects. Competing interests The authors declare no competing interests. Funding Non-funded study Author contributions Allan B. Kambanda was responsible for study design, data collection, analysis, interpretation, and manuscript writing. Bright A. Sangiwa and Christina V. Malichewe were responsible for study design, analysis, interpretation, and manuscript editing. Bright A. Sangiwa was a correspnding author for the manuscript submission. All the authors have read and agreed to the final manuscript. Acknowledgment Sincere thanks for guidance, directives, unconditional support, encouragement, and motivation from my supervisors, Dr. Christina V. Malichewe and Dr. Bright A. Sangiwa for their unwavering support. The same appreciations go to all the specialists in Radiology department (MUHAS and ORCI), with special thanks to Dr. Revelian Iramu for support in image interpretation. 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Eur J Nucl Med Mol Imaging 48(12):4089–4100 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7336464","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498197503,"identity":"7bdb0f21-1bd5-442f-a795-56498707cfba","order_by":0,"name":"Allan B. Kambanda","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences (MUHAS)","correspondingAuthor":false,"prefix":"","firstName":"Allan","middleName":"B.","lastName":"Kambanda","suffix":""},{"id":498197504,"identity":"3081904e-74bd-4702-87fc-5bfdf73895ed","order_by":1,"name":"Bright A. Sangiwa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYBACAwbGBmYIk7GBgaECSDMzNxChJQGm5QxICyMhLUA1EC0gXW0wvXiAufTh5teFP+rkzfkXt0n8nFcbzd8O1PKjYhtOLZZ9iW3WMxIOG+6c8bBNsnfb8dwZhxkbGHvO3MbtsDOMbcY8CQcYN9w42HaDd9ux3AagFmbGNoJa6uxBWm7+nXMsdz4RWpof8yQwJ24439h2m7ehJncDIS2WPYxtzDxph5M33GBs/y1z7EDuRqCWg/j8Ys7D/vgzj02d7Ybzxx8bvqmpy513/vDBBz8qcGsBAjYJMCWRACIPg9kH8KkHAuYPYIofrK6OgOJRMApGwSgYiQAAjgdjc1zsFdcAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-1874-3561","institution":"Ocean road Cancer Institute","correspondingAuthor":true,"prefix":"","firstName":"Bright","middleName":"A.","lastName":"Sangiwa","suffix":""},{"id":498197505,"identity":"b562ad99-0051-4a59-ab34-27f45a46e75c","order_by":2,"name":"Christina V. Malichewe","email":"","orcid":"https://orcid.org/0000-0002-7567-1437","institution":"Muhimbili University of Health and Allied Sciences (MUHAS)","correspondingAuthor":false,"prefix":"","firstName":"Christina","middleName":"V.","lastName":"Malichewe","suffix":""}],"badges":[],"createdAt":"2025-08-10 02:53:55","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7336464/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7336464/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88893419,"identity":"2bda340c-9f5b-4c40-a7e3-61185eedd3bc","added_by":"auto","created_at":"2025-08-12 12:56:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93250,"visible":true,"origin":"","legend":"\u003cp\u003e51-Year-old female known with right breast cancer, post right radical mastectomy, Chest radiotherapy, and chemotherapy. (\u003cstrong\u003eA\u003c/strong\u003e) Contrasted axial chest CT at the level of the exposed liver shows bilateral mild pleural effusion, and the liver appears normal. Image (\u003cstrong\u003eB\u003c/strong\u003e and \u003cstrong\u003eC\u003c/strong\u003e) FUSED PET CT (\u003cstrong\u003eB\u003c/strong\u003e) and PET (\u003cstrong\u003eC\u003c/strong\u003e), at the same level, show multiple FAP-avid lesions in the liver not seen on conventional CT. Image (\u003cstrong\u003eD\u003c/strong\u003e and \u003cstrong\u003eE\u003c/strong\u003e) FUSED PET CT (\u003cstrong\u003eD\u003c/strong\u003e) and PET (\u003cstrong\u003eE\u003c/strong\u003e), in the same patient, showed FAP-avid lesions in the left breast and ipsilateral axilla. Tissue biopsies (liver, left breast, left axilla node) were histologically confirmed to be malignant lesions.\u003c/p\u003e","description":"","filename":"Figure1Image.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7336464/v1/126db19d6caf6df4fe3917ba.jpg"},{"id":88895437,"identity":"8e648504-3163-46da-b71b-d972b0c81f5d","added_by":"auto","created_at":"2025-08-12 13:04:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46826,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRecurrence–free survival according to residual disease detected on Ga-68 FAPI PET CT\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2image.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7336464/v1/c123638f04d50667489662e7.jpg"},{"id":88897292,"identity":"f3ac365b-cf02-48e0-8e6f-a257d2b1c852","added_by":"auto","created_at":"2025-08-12 13:12:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1088535,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7336464/v1/81600243-42a0-4669-ad23-27f5086bf972.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eFapi Pet-ct in Detecting Minimal Residual Disease and Subclinical Metastatic Sites in Post-treatment Breast Cancer\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eBreast cancer is the most prevalent cancer diagnosed in women globally, and its incidence has been increasing over recent decades [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 2020, breast cancer accounted for the highest number of cancer diagnoses among women, with an estimated 2.3\u0026nbsp;million new cases reported worldwide and approximately 685,000 fatalities attributed to the disease [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Projections suggest that by 2050, the global incidence of female breast cancer could escalate to around 3.2\u0026nbsp;million new cases annually [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is the most commonly diagnosed cancer and the second leading cause of cancer-related deaths in sub-Saharan Africa [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This region has the highest age-standardized incidence rate, which is 17.3 cases per 100,000 women per year. Country-specific prevalence rates indicate that breast cancer affects 15.3% of women in the Central African Republic, 4.6% in Rwanda, and 3.3% in Sierra Leone [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe tumor microenvironment (TME) has recently been recognized as a significant therapeutic target in the fields of cancer imaging and treatment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is composed of the extracellular matrix, various stromal cells\u0026mdash;including fibroblasts, mesenchymal stromal cells, as well as the networks of blood and lymphatic vessels [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Additionally, the TME encompasses a diverse array of immune cells, including T and B lymphocytes, natural killer cells, and tumor-associated macrophages [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Fibroblast activation protein (FAP) is predominantly expressed in cancer-associated fibroblasts (CAFs) in over 90% of epithelial carcinomas [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The use of FAP-targeted molecular imaging has emerged as a promising strategy for the detection of tumor stroma [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This approach facilitates a better understanding of the tumor microenvironment and may enhance the diagnosis and treatment of cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn 2018, a group of studies from the University of Heidelberg reported the use of DOTA-based fibroblast activation protein inhibitors (FAPI) in combination with Gallium-68 to perform PET imaging of a variety of tumors, including breast, colorectal, lung, and pancreatic cancers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFAPI PET imaging serves multiple purposes, including initial staging, re-staging, evaluation of therapeutic response, and comprehensive assessment of target expression throughout the body to inform therapy selection [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In the context of FAPI imaging, tumors can be classified into three distinct categories, two caterogies that express high tumor FAPI uptake include desmoplastic tumors characterized by a high concentration of cancer-associated fibroblasts (CAFs) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and tumors that express FAP on both the tumor stroma and the tumor cells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The third category are tumors with minimal desmoplastic reaction which do not exhibit significant desmoplastic features therefore mininal FAPI uptake is seen in these tumours. Breast cancer is in the category of desmoplastic tumors characterized by a high concentration of cancer-associated fibroblast [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAreas of increased radiotracer uptake are identified and region of interest drawn to automatically quantify the maximum standard uptake (SUVmax) and make a diagnosis of residual tumor and/ or metastasis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Lesions are deemed malignant when non-physiologic foci of increased radiotracer uptake appear on PET images.The high diagnostic performance of Ga-68 FAPI PET-CT in detecting minimal residual tumors is attributed to the higher tracer uptake in breast cancer and a favorable low tumor-to-background ratio [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This combination allows for optimal tumor delineation. In patients with apparently confined breast cancer who are candidates for loco-regional therapy, additional Ga-68 FAPI PET-CT can identify unexpected metastases, thereby upstaging patients from M0 to M\u0026thinsp;+\u0026thinsp;and altering their treatment planning [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn breast cancer, there is an increased uptake of fibroblast activation protein (FAP) ligand that occurs independently of histological phenotype\u0026mdash;whether lobular or ductal [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The background uptake of radiolabeled FAPI in the brain, liver, and oral mucosa is considerably lower than that of F-18 FDG, which makes it a more precise tool for staging breast cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eThis was a retrospective cross-sectional study of all histologically confirmed breast cancer patients who underwent Ga-68 FAPI PET-CT after initial treatment at Nuclear medicine and PET-CT centre at Ocean road Cancer Institute for evaluation of minimal residual disease and subclinical metastases, between July 2024 to December 2024.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGa-68 FAPI PET\u003c/h3\u003e\n\u003cp\u003ePET images were acquired 10 to 30 min after the administration of 5.5 to 8.46 mCi of Ga-68 FAPI. A 3D PET/CT scan was performed from vertex to mid-thigh on a SIEMENS BIOGRAPH MCT-64 slice PET/CT scanner. Multiplanar reformations were then performed on a dedicated station. Notably, patients were not required to fast prior to the examination, unlike with FDG-PET/CT. The PET images were evaluated by a nuclear medicine physician and the principal investigator. Quantitative assessment of tracer uptake in active areas was performed by measuring the maximum standardized uptake value (SUVmax) within regions of interest.\u003c/p\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in forty-five patients with breast tumour and post initial treatment, who had Ga-68 FAPI PET-CT scan between July 2024 and December 2024. Female of 18 years and above who had histologically confirmed breast cancer, completed initial treatment, with documented conventional imaging results and had undergone Ga-68 FAPI PET CT studies were included. The study excluded male patients with breast cancer and those who were not eligible for Ga-68 FAPI PET-CT.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eA standardized case report form with four sections was designed to include patient characteristics, sensitivity and specificity of Ga-68 FAPI PET-CT in detecting minimal residual disease in breast cancer patients after initial treatment, subclinical metastatic sites of breast cancer compared to conventional imaging methods (MRI and / or CT) and association between Ga-68 FAPI PET-CT findings and clinical outcomes, specifically recurrence-free survival (RFS) in patients treated for breast cancer.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eThe Statistical Package for Social Sciences (SPSS) version 24 was used to store and analyze the collected data. Before analysis, the data was cleaned, coded, and entered into SPSS. Means and standard deviations were used to summarize continuous data while categorical data were summarized using frequencies and percentages.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eEthical Consideration\u003c/h2\u003e\u003cp\u003e The study had approval of MUHAS Research and Ethics Committee (Ref. No. DA.282/298/01.C/2844). A waiver of informed consent was granted as a retrospective study that impose no risk to the subjects.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003ePatient characteristics\u003c/h2\u003e\u003cp\u003eThe majority of patients, 21/45 (46.7%), were aged between 50 and 70 years. The overall age, ranged from 34 to 86 years, with a mean age of 58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7 years. Most participants, 32/45 (71.1%), were postmenopausal.\u003c/p\u003e\u003cp\u003eThe most common immunohistochemistry biomarker found in breast cancer among the study participants was estrogen receptor positive (ER+) observed in 62.2% of participants, followed by progesterone receptor positive (PR+) in 22/45 (48.9%), HER-2 Positive in 13/45 (28.9%), and 12/45 (26.6%) had no biomarkers. Regarding immunohistochemistry subtypes, the majority had Luminal A (17/45, 37.8%), followed by Basal-Like/Triple Negative (12/45, 26.7%), Luminal B (11/45, 24.4%), and 5/45 (11.1%) had HER-2 Enriched. In terms of histopathological subtypes, invasive ductal carcinoma (IDC) was observed in 40/45(88.9%), patients and other subtypes were found in 5/45 (11.1%) patients.\u003c/p\u003e\u003cp\u003eChemotherapy was the most commonly used treatment modality, reported in 43/45 (95.6%) patients, followed by surgery in 40/45 (88.9%) and radiotherapy in 24/45 (53.3%), Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient Characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u0026ndash;70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePostmenopausal state\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eImmunohistochemistry\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePR+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHER-2 +\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eImmunohistochemistry subtypes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLuminal A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLumina B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHer-2 Enriched\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBasal-like/Triple Negative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eHistological subtypes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIDC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eILC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eBreast cancer treatment received\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSurgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChemotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRadiotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eGa-68 FAPI PET-CT in detecting minimal residual disease after initial treatment\u003c/h2\u003e\u003cp\u003eIn this study, Ga-68 FAPI PET-CT has demonstrated a sensitivity of 100%, and a specificity of 82.5% in detecting minimal residual disease in breast cancer patients after initial treatment, using conventional imaging methods such as MRI and / or CT as the reference standard as described in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSensitivity and Specificity of Ga-68 FAPI PET-CT\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eResidual Disease detected on CT and/or MRI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eResidual Disease detected on Ga-68 FAPI PET CT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(\u003cb\u003e100%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(\u003cb\u003e17.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12(\u003cb\u003e26.6%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (\u003cb\u003e0.0%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33(\u003cb\u003e82.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33(73.3\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(100\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (100\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45 \u003cb\u003e(100%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe maximum standardized uptake values (SUVmax) of residual disease detected on Ga-68 FAPI PET/CT were obtained at the region of interest. Data were available for all 12 patients (no missing values). The mean SUVmax was 11.49, with a standard deviation of 5.36, indicating moderate variability across the patient cohort. The median SUVmax was 10.00, suggesting a slightly right-skewed distribution. The SUVmax values ranged from a minimum of 5.77 to a maximum of 25.35.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eGa-68 FAPI PET-CT in detecting subclinical metastatic sites compared to conventional imaging\u003c/h2\u003e\u003cp\u003eOur study showed that, Ga-68 FAPI PET-CT had significantly greater sensitivity in detecting subclinical metastatic lesions compared to conventional imaging modalities, including MRI and /or CT. Subclinical metastases were identified in 12/45 (26.7%), whereas MRI and / or CT identified only in 5/45 (11.1%). This corresponds to an absolute difference of 15.6%, which was statistically significant (P\u0026thinsp;=\u0026thinsp;0.016), emphasizing the superior diagnostic performance of Ga-68 FAPI PET-CT.\u003c/p\u003e\u003cp\u003eThe most pronounced differences were observed in the detection of liver and axillary metastases. Ga-68 FAPI PET-CT identified liver metastases in 7/45 (15.6%) compared to 3 /45 (6.7%) using conventional imaging, yielding a difference of 8.9%. Similarly, axillary metastatic involvement was detected in 5/45 (11.1%) by Ga-68 FAPI PET-CT versus 2/45 (4.4%) by MRI and / or CT, with a difference of 6.7%. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows FAPI uptake in different metastatic sites.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn contrast, both imaging modalities demonstrated comparable detection rates in the chest and brain regions, with each modality identifying metastatic lesions in 2/45 (4.4%). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the metastatic sites findings.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGa-68 FAPI PET-CT compared to MRI and/or CT in identifying Subclinical metastatic sites\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetastatic sites\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSubclinical metastatic sites detected on Ga-68 FAPI PET CT\u003c/p\u003e\u003cp\u003e(Number of patients, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSubclinical Metastatic sites detected on MRI and / or CT\u003c/p\u003e\u003cp\u003e(Number of patients, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDifference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChest\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2(4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBone\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6(13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(4.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBrain\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2(4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAxillary nodes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5(11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLymphatic system\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLiver\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(15.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(8.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOthers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1(2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(2.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12(26.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(15.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMcNemar's Test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAmong 12 patients, the maximum standardized uptake values (SUVmax) of detected subclinical metastatic disease had a mean SUVmax of 11.26, a median of 10.3 and a range from 4.81 to 20.80.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation between Ga-68 FAPI PET CT finding in detecting residual disease and clinical outcomes.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll the patients found with residual disease detected on Ga-68 FAPI PET-CT reported to have breast cancer recurrence 12/12 (100%) compared to those with no residual disease 3/33 (9.1%). This association was statistically significant with Fisher's Exact Test P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation between Ga-68 FAPI PET CT findings and recurrence-free survival (RFS).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe overall mean recurrence-free survival (RFS) time for the cohort was 38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2 months. A significantly longer mean RFS was observed in patients without residual disease on Ga-68 FAPI PET-CT, with an average of 58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7 months, compared to 12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 months in patients with residual disease. The overall median RFS was 24.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 months. Among patients with residual disease, the median RFS was markedly lower at 6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 months. In contrast, the median RFS for patients without residual disease could not be estimated due to an insufficient number of recurrence events in this subgroup. The difference in recurrence-free survival between patients with and without residual disease detected on Ga-68 FAPI PET/CT was highly statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Log-Rank test) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study evaluated the diagnostic performance and prognostic value of Ga-68 FAPI PET-CT in detecting residual and subclinical metastatic disease in breast cancer patient\u0026rsquo;s post-treatment. The findings showed that Ga-68 FAPI PET-CT offers significant advantages over conventional imaging modalities such as MRI and/or CT, both in identifying occult disease and in predicting clinical outcomes.\u003c/p\u003e\u003cp\u003eThe demographic characteristics of the patient cohort reveal a predominantly postmenopausal population, with mean age of 58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7 years. A study done in 2021 in Tanzania, found the median age was 50 years (range: 30\u0026ndash;93 years) among women with proven breast cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This aligns with existing literature that suggests a higher prevalence of breast cancer in older women [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The immunohistochemistry profiles indicate a significant occurrence of estrogen receptors (ER), with 62.2% of patients testing positive. This is important as ER-positive breast cancer is generally associated with better prognoses and responsiveness to endocrine therapies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. FAPI uptake is not correlated with histopathological and molecular features, and it is equally increased in all types of breast cancer [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe distribution of immunohistochemical subtypes shows a predominance of (ER-Positive/PR-positive and HER-2 negative (Luminal A) tumors, suggesting a favorable prognosis in terms of treatment and survival outcomes. However, the presence of Basal-Like/Triple Negative tumors (26.7%) in our cohort underscores the need for more aggressive treatment strategies, as these subtypes are often more challenging to treat. In ductal carcinoma in situ, research indicates that ER-negative/PR-negative but HER2-positive cancers have a higher risk of recurrence compared to ER-positive/PR-positive/HER2-negative cancers [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong the 45 patients included in the study, Ga-68 FAPI PET-CT demonstrated a high sensitivity (100%) and specificity (82.5%) for detecting residual disease, using MRI/CT as the reference standard. Preliminary data reported by Eshet et al. indicate that FAPI PET is more effective than conventional CT in detecting lesions in seven women diagnosed with lobular breast cancer, demonstrating the ability to identify numerous lesions across various distant organs [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].These findings concur with a related finding which had compared roles of Ga-68 FAPI-PET-CT and F-18 FDG PET-CT where the sensitivity and specificity of FAPI in detecting residual breast lesions were 100% and 95.6% respectively [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. FAPI has the capability to identify lesions within the first month following the completion of chemotherapy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].This suggests that Ga-68 FAPI PET-CT is a highly reliable imaging modality for identifying minimal residual disease (MRD).FAP-targeted imaging modalities, especially positron emission tomography (PET), have demonstrated high sensitivity and specificity in detecting tumors that express fibroblast activation protein (FAP) and potentially enhance tumor detection, improve staging accuracy, and monitor treatment responses effectively [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, Ga-68 FAPI PET-CT was notably superior in detecting subclinical metastases. It identified metastatic lesions in 26.7% of patients, compared to only 11.1% detected by MRI/CT. The statistically significant difference (P\u0026thinsp;=\u0026thinsp;0.016) reinforces the enhanced sensitivity of Ga-68 FAPI PET-CT, especially in challenging anatomical regions. The most pronounced differences were observed in the liver and axillary nodes, where FAPI PET-CT detected nearly twice as many metastatic sites. In a clinical study involving patients with metastasized breast cancer, Ga-68 FAPI PET-CT exhibited high-contrast imaging capabilities, demonstrating significant tracer uptake in metastatic lesions while exhibiting minimal uptake in normal tissues [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These findings are consistent with existing literature suggesting that Ga-68 FAPI PET-CT is more effective in identifying small, metabolically active lesions due to its ability to target cancer-associated fibroblasts, which are abundant in the tumor microenvironment.\u003c/p\u003e\u003cp\u003eRecent scientific advancements in breast cancer research have significantly improved the chances of disease-free survival for patients diagnosed at an early stage, when the cancer is still confined to the breast [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, once breast cancer metastasizes to other organs, treatment options become very limited, and the success rate of managing these patients decreases substantially [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. From a prognostic standpoint, our results indicate that the presence of residual disease on Ga-68 FAPI PET-CT is strongly associated with poorer outcomes. Breast cancers that are localized to the primary breast site and are treated in the early stages may still experience relapse [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This can occur due to the presence of cancer stem cells or the transformation of cancer cells into a more aggressive phenotype [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. All patients with residual disease experienced disease recurrence (100%), whereas recurrence occurred in only 9.1% of those without residual disease but due to distant metastasis, a highly significant association (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A study conducted by Brewester et al on breast cancer recurrent post treatment found that a 5-year residual risks of recurrence for patients with stage I, II, and III breast cancer increased as staging increases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, recurrence-free survival (RFS) was significantly shorter in patients with residual disease. Breast cancer recurrence is a critical indicator of tumor progression and is the primary cause of mortality associated with this disease [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The mean RFS for the patients in this study was 12.4 months, compared to 58.6 months for those without residual disease. The median RFS was similarly shorter (6.0 months vs. not estimable), and the difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Recurrent breast cancers are typically marked by high percentage of aggressive cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These findings underline the potential of Ga-68 FAPI PET-CT not only as a diagnostic tool but also as a prognostic biomarker that can aid in risk stratification and post-treatment surveillance.\u003c/p\u003e\u003cp\u003eThe analysis of standardized uptake values (SUVmax) further supports the biological relevance of the detected lesions. A study by Hadebe B. et al [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] demonstrated that Ga-68 FAPI PET-CT offers significant advantages in the detection of both primary and metastatic tumors, attributable to its high sensitivity and increased SUVmax [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The mean SUVmax of residual lesions in this study was 11.49, with a range from 5.77 to 25.35, indicating varying degrees of FAPI uptake. A systematic review conducted between 2017 and 2023 also observed that the maximum standardized uptake value (SUVmax) in primary tumors ranged from 2.6 to 17.0 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Additionally, increased uptake values were consistently reported across all metastatic sites, including lymph nodes, lungs, liver, and bone [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This variability may reflect differences in tumor aggressiveness, fibroblast activation, or treatment response.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study reinforces the role of Ga-68 FAPI PET-CT as a critical tool in the diagnosis and management of breast cancer. The high sensitivity and specificity of this imaging technique found in this study is comparable to what has been reported on Ga-68 FAPI PET-CT. This modality provides clinicians with a powerful resource to identify residual disease and subclinical metastases, ultimately improving patient outcomes. Future studies should explore the integration of Ga-68 FAPI PET-CT into standard practice guidelines for breast cancer management, particularly for patients at high risk of recurrence.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eThis study is limited by its relatively small sample size that lowers the statistical power and generalizability\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe retrospective nature of the design is prone to selection bias and poor quality data as it relies on already available data.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLack of histopathological confirmation for all FAPI avid lesions may introduce a risk of overestimation of the burden of disease.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eRecommendations\u003c/h2\u003e\u003cp\u003eLarger, prospective studies are recommended to confirm the diagnostic accuracy and clinical utility of Ga-68 FAPI PET-CT in breast cancer particularly for the detection of residual and subclinical metastatic disease.\u003c/p\u003e\u003cp\u003eFuture studies should aim to incorporate histopathological validation of FAPI-avid lesions wherever feasible to better characterize false positives and improve specificity.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e Ethics approval and consent to participate, the study had approval of MUHAS Research and Ethics Committee (Ref. No. DA.282/298/01.C/2844). A waiver of informed consent was granted as a retrospective study that impose no risk to the subjects.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNon-funded study\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eAllan B. Kambanda was responsible for study design, data collection, analysis, interpretation, and manuscript writing. Bright A. Sangiwa and Christina V. Malichewe were responsible for study design, analysis, interpretation, and manuscript editing. Bright A. Sangiwa was a correspnding author for the manuscript submission. All the authors have read and agreed to the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e\u003cp\u003eSincere thanks for guidance, directives, unconditional support, encouragement, and motivation from my supervisors, Dr. Christina V. Malichewe and Dr. Bright A. Sangiwa for their unwavering support. The same appreciations go to all the specialists in Radiology department (MUHAS and ORCI), with special thanks to Dr. Revelian Iramu for support in image interpretation. To all consultants, specialists, residents, and all other staff in the Nuclear Medicine, Oncology, and Medical Records departments at Ocean Road Cancer Institute for the assistance from development to completion of this manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eData is available upon special request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M et al (2022) Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast 66:15\u0026ndash;23\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTao Z, Shi A, Lu C, Song T, Zhang Z, Zhao J (2015) Breast Cancer: Epidemiology and Etiology. Cell Biochem Biophys 72(2):333\u0026ndash;338\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdewale Adeoye P (2023) Epidemiology of Breast Cancer in Sub-Saharan Africa. In: S\u0026ouml;zen S, Emir S, editors. Breast Cancer Updates. IntechOpen\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalekouzou A, Yin P, Pamatika CM, Bishwajit G, Nambei SW, Djeintote M et al (2016) Epidemiology of breast cancer: retrospective study in the Central African Republic. BMC Public Health 16(1):1230\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoma-Rodrigues C, Mendes R, Baptista PV, Fernandes AR (2019) Targeting Tumor Microenvironment for Cancer Therapy. Int J Mol Sci 20(4):840\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDadgar H, Norouzbeigi N, Assadi M, Al-balooshi B, Al-Ibraheem A, Haidar M et al (2023) Initial Clinical Experience using \u003csup\u003e68\u003c/sup\u003eGa-FAPI-46 PET/CT for Detecting Various Cancer Types\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMori Y, Kratochwil C, Haberkorn U, Giesel FL (2023) Fibroblast Activation Protein Inhibitor Theranostics. PET Clin 18(3):419\u0026ndash;428\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo W, Xu W, Fan C, Fu H, Meng T, Pang Y et al (2022) Gallium-68-Labelled Fibroblast Activation Protein Inhibitor PET/CT in the clinical diagnosis and management of breast cancer. Comparison with [18F]FDG PET/CT\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTaralli S, Lorusso M, Perrone E, Perotti G, Zagaria L, Calcagni ML (2023) PET/CT with Fibroblast Activation Protein Inhibitors in Breast Cancer: Diagnostic and Theranostic Application\u0026mdash;A. Literature Rev Cancers 15(3):908\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHamson EJ, Keane FM, Tholen S, Schilling O, Gorrell MD (2014) Understanding fibroblast activation protein (FAP): Substrates, activities, expression and targeting for cancer therapy. Proteom \u0026ndash; Clin Appl 8(5\u0026ndash;6):454\u0026ndash;463\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHope TA, Calais J, Goenka AH, Haberkorn U, Konijnenberg M, McConathy J et al (2024) SNMMI Procedure Standard/EANM Practice Guideline for Fibroblast Activation Protein (FAP) PET. J Nucl Med. ; jnumed.124.269002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhatcott CJ, Diep CH, Jiang P, Watanabe A, LoBello J, Sima C et al (2015) Desmoplasia in Primary Tumors and Metastatic Lesions of Pancreatic Cancer. Clin Cancer Res 21(15):3561\u0026ndash;3568\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBackhaus P, Burg MC, Roll W, B\u0026uuml;ther F, Breyholz HJ, Weigel S et al (2022) Simultaneous FAPI PET/MRI Targeting the Fibroblast-Activation Protein for Breast Cancer. Radiology 302(1):39\u0026ndash;47\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiesel FL, Kratochwil C, Schlittenhardt J, Dendl K, Eiber M, Staudinger F et al (2021) Head-to-head intra-individual comparison of biodistribution and tumor uptake of \u003csup\u003e68\u003c/sup\u003eGa-FAPI and \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in cancer patients. Eur J Nucl Med Mol Imaging 48(13):4377\u0026ndash;4385\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSood R, Masalu N, Connolly RM, Chao CA, Faustine L, Mbulwa C et al (2021) Invasive breast Cancer treatment in Tanzania: landscape assessment to prepare for implementation of standardized treatment guidelines. BMC Cancer 21(1):527\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShiner A, Kiss A, Saednia K, Jerzak KJ, Gandhi S, Lu FI et al (2023) Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning. Genes 14(9):1768\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmad A (2013) Pathways to Breast Cancer Recurrence. ISRN Oncol. ; 2013:1\u0026ndash;16\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEvangelista L, Filippi L, Schillaci O (2023) What radiolabeled FAPI pet can add in breast cancer? A systematic review from literature. Ann Nucl Med 37(8):442\u0026ndash;450\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang SY, Shamliyan T, Virnig BA, Kane R (2011) Tumor characteristics as predictors of local recurrence after treatment of ductal carcinoma in situ: a meta-analysis. Breast Cancer Res Treat 127(1):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEshet Y, Tau N, Apter S, Nissan N, Levanon K, Bernstein-Molho R et al (2023) The Role of \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT in Detection of Metastatic Lobular Breast Cancer. Clin Nucl Med 48(3):228\u0026ndash;232\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026ouml;mek H, Can C, G\u0026uuml;zel Y, Oru\u0026ccedil; Z, G\u0026uuml;ndoğan C, Yildirim \u0026Ouml;A et al (2021) \u003csup\u003e68\u003c/sup\u003eGa-FAPI-04 PET/CT, a new step in breast cancer imaging: a comparative pilot study with the 18F-FDG PET/CT. Ann Nucl Med 35(6):744\u0026ndash;752\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHadebe B, Harry L, Ebrahim T, Pillay V, Vorster M (2023) The Role of PET/CT in Breast Cancer. Diagnostics 13(4):597\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBackhaus P, Burg MC, Asmus I, Pixberg M, B\u0026uuml;ther F, Breyholz HJ et al (2023) Initial Results of \u003csup\u003e68\u003c/sup\u003eGa-FAPI-46 PET/MRI to Assess Response to Neoadjuvant Chemotherapy in Breast Cancer. J Nucl Med 64(5):717\u0026ndash;723\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKiani M, Jokar S, Hassanzadeh L, Behnammanesh H, Bavi O, Beiki D et al (2024) Recent Clinical Implications of FAPI: Imaging and Therapy. Clin Nucl Med 49(11):e538\u0026ndash;e556\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaphner T, Tormey DC, Gray R (1996) Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol Off J Am Soc Clin Oncol 14(10):2738\u0026ndash;2746\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrewster AM, Hortobagyi GN, Broglio KR, Kau SW, Santa-Maria CA, Arun B et al (2008) Residual Risk of Breast Cancer Recurrence 5 Years After Adjuvant Therapy. JNCI J Natl Cancer Inst 100(16):1179\u0026ndash;1183\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoody SE, Perez D, Pan T, chi, Sarkisian CJ, Portocarrero CP, Sterner CJ et al (2005) The transcriptional repressor Snail promotes mammary tumor recurrence. Cancer Cell 8(3):197\u0026ndash;209\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDendl K, Koerber SA, Finck R, Mokoala KMG, Staudinger F, Schillings L et al (2021) \u003csup\u003e68\u003c/sup\u003eGa-FAPI-PET/CT in patients with various gynecological malignancies. Eur J Nucl Med Mol Imaging 48(12):4089\u0026ndash;4100\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Ocean Road Cancer Institute","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PET, FAPI, Breast Cancer, residual disease, subclinical metastases","lastPublishedDoi":"10.21203/rs.3.rs-7336464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7336464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBreast cancer has become the most common type of cancer, surpassing lung cancer, and is the leading cause of cancer-related deaths among women worldwide. Ga-68 FAPI PET-CT has currently evolved in multiple aspects in breast cancer assisting in diagnosis, initial staging, re-staging, suspected recurrence, and evaluating therapeutic response. It has also shown a role in other malignancies like sarcoma, esophageal cancer, cholangiocarcinoma, and lung cancer.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA retrospective analysis of Ga-68 FAPI PET-CT scans of forty-five patients aged eighteen and older with confirmed breast cancer who have undergone various treatments (surgery, chemotherapy, radiotherapy) was performed. The role Ga-68 FAPI PET\u0026ndash;CT imaging in the detection of minimal residual disease and subclinical metastatic sites in breast cancer patients after initial treatment was analyzed.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 45 patients with histologically confirmed breast cancer and post treatment underwent Ga-68 FAPI PET-CT and Conventional CT and /or MRI. Ga-68 FAPI PET-CT showed 100% sensitivity and 82.5% specificity in detecting minimal residual disease, significantly outperforming conventional imaging, which identified lesions in only 11.1% of patients compared to 26.7% with PET-CT. Notably, Ga-68 FAPI PET-CT was better at detecting liver metastases (15.6% vs. 6.7%) and axillary metastases (11.1% vs. 4.4%). All patients with residual primary disease detected by Ga-68 FAPI PET-CT experienced recurrence (100%). However, those without residual primary disease, only 9.1% experienced recurrence. Recurrence-free survival was significantly longer in patients without residual disease (58.6 vs. 12.4 months, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGa-68 FAPI PET-CT has shown to be a probably sensitive and specific imaging modality that can effectively detect minimal residual disease and subclinical metastases in breast cancer patients. This study may potentially help in earlier detection of breast cancer recurrences hence timely interventions and improved patient outcomes.\u003c/p\u003e","manuscriptTitle":"Fapi Pet-ct in Detecting Minimal Residual Disease and Subclinical Metastatic Sites in Post-treatment Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 12:56:20","doi":"10.21203/rs.3.rs-7336464/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0779d0e1-502e-4922-86f0-67fee6171025","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53038105,"name":"Oncology"}],"tags":[],"updatedAt":"2025-08-12T12:56:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 12:56:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7336464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7336464","identity":"rs-7336464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}